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Sample records for earthquake swarm final

  1. Structural Preconditions of West Bohemia Earthquake Swarms

    Science.gov (United States)

    Novotný, M.; Špičák, A.; Weinlich, F. H.

    2013-07-01

    swarms. The sealed focal domains retain ascending magmatic fluids until their critical pressure and volumes accumulated cause rock micro-fractures perceived as single earthquake bursts. During a swarm period, the focal depths of these sequential events become shallower while their magnitudes grow. We assume that coalescence of the induced micro-fractures forms temporary permeability zones in the final swarm phase and the accumulated fluids release into the overburden via the adjacent fault systems. The fluid release usually occurs after the shallowest events with the strongest magnitudes ML > 3. The seasonal summer declines of hydrostatic pressure in the Cheb Basin aquifer system seem to facilitate and trigger the fluid escape as happened for the 2000, 2008, and 2011 earthquake swarms. The temporary fluid release, known as the valve-fault action, influences the surface aquifer systems in various manners. In particular, we found three quantities, the strain, mantle-derived 3He content in CO2 surface sources and ground water levels, which display a 3-5 months decline before and then a similar restoration after each peak earthquake during the swarm activities. The revealed structure features are particularly important since the main Nový Kostel earthquake swarm area is proposed as a site for the ICDP project, `Eger Rift Drilling'.

  2. Global volcanic earthquake swarm database and preliminary analysis of volcanic earthquake swarm duration

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    S. R. McNutt

    1996-06-01

    Full Text Available Global data from 1979 to 1989 pertaining to volcanic earthquake swarms have been compiled into a custom-designed relational database. The database is composed of three sections: 1 a section containing general information on volcanoes, 2 a section containing earthquake swarm data (such as dates of swarm occurrence and durations, and 3 a section containing eruption information. The most abundant and reliable parameter, duration of volcanic earthquake swarms, was chosen for preliminary analysis. The distribution of all swarm durations was found to have a geometric mean of 5.5 days. Precursory swarms were then separated from those not associated with eruptions. The geometric mean precursory swarm duration was 8 days whereas the geometric mean duration of swarms not associated with eruptive activity was 3.5 days. Two groups of precursory swarms are apparent when duration is compared with the eruption repose time. Swarms with durations shorter than 4 months showed no clear relationship with the eruption repose time. However, the second group, lasting longer than 4 months, showed a significant positive correlation with the log10 of the eruption repose period. The two groups suggest that different suites of physical processes are involved in the generation of volcanic earthquake swarms.

  3. The precursory earthquake swarm in Greece

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    D. Rhoades

    2000-06-01

    Full Text Available The Hellenic subduction region displays the same precursory swarm phenomenon as has been found in comparable regions of New Zealand and Japan. In the earthquake catalogue of the Aristotle University of Thessaloniki, 10 past sequences of precursory swarms and related major mainshock events have been identified. These correlate, in respect of location, magnitude and time, with the 9 sequences previously identified in New Zealand, and 9 in Japan, bringing the total of sequences to 28, and the totals of related events (allowing for clustering to 56 precursory swarms and 42 mainshock events. The results add strength to the hypothesis that swarms are long-range predictors of mainshock events. A close similarity between the swarm and aftershock magnitudes in a given sequence is also confirmed in Greece, supporting the proposal that swarms are an integral part of the seismogenic process in subduction regions. Further, the modelling of swarms as part of an overall increase in seismicity, the onset of which marks the onset of seismogenesis, is well illustrated from past sequences in Greece. Formal tests are being carried out in Greece, in parallel with New Zealand and Japan, to ascertain the performance of the hypothesis as a basis for long-range synoptic forecasting.

  4. Frog Swarms: Earthquake Precursors or False Alarms?

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    Rachel A. Grant

    2013-10-01

    Full Text Available In short-term earthquake risk forecasting, the avoidance of false alarms is of utmost importance to preclude the possibility of unnecessary panic among populations in seismic hazard areas. Unusual animal behaviour prior to earthquakes has been reported for millennia but has rarely been scientifically documented. Recently large migrations or unusual behaviour of amphibians have been linked to large earthquakes, and media reports of large frog and toad migrations in areas of high seismic risk such as Greece and China have led to fears of a subsequent large earthquake. However, at certain times of year large migrations are part of the normal behavioural repertoire of amphibians. News reports of “frog swarms” from 1850 to the present day were examined for evidence that this behaviour is a precursor to large earthquakes. It was found that only two of 28 reported frog swarms preceded large earthquakes (Sichuan province, China in 2008 and 2010. All of the reported mass migrations of amphibians occurred in late spring, summer and autumn and appeared to relate to small juvenile anurans (frogs and toads. It was concluded that most reported “frog swarms” are actually normal behaviour, probably caused by juvenile animals migrating away from their breeding pond, after a fruitful reproductive season. As amphibian populations undergo large fluctuations in numbers from year to year, this phenomenon will not occur on a yearly basis but will depend on successful reproduction, which is related to numerous climatic and geophysical factors. Hence, most large swarms of amphibians, particularly those involving very small frogs and occurring in late spring or summer, are not unusual and should not be considered earthquake precursors. In addition, it is likely that reports of several mass migration of small toads prior to the Great Sichuan Earthquake in 2008 were not linked to the subsequent M = 7.9 event (some occurred at a great distance from the epicentre

  5. Can hydroseismicity explain recurring earthquake swarms in NW-Bohemia?

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    Heinicke, Jens; Woith, Heiko; Alexandrakis, Catherine; Buske, Stefan; Telesca, Luciano

    2018-01-01

    Fluid driven seismicity has been observed worldwide. The occurrence of intraplate seismicity triggered by pore pressure perturbations is a widely accepted process. Past analysis of earthquake swarms in the NW-Bohemia/Vogtland region provided evidence for the diffusion of pore pressure fronts during the migration of earthquakes within each swarm. Here, we test the hypothesis whether the diffusion of hydraulically induced pore pressure perturbations from the surface to the hypocentral depth could be a valid trigger mechanism. We test this hypothesis for the earthquake swarms in the Nový Kostel focal zone based on the analysis of 121 earthquake swarms and microswarms which occurred between 1992 and 2016.

  6. Scaling and spatial complementarity of tectonic earthquake swarms

    KAUST Repository

    Passarelli, Luigi

    2017-11-10

    Tectonic earthquake swarms (TES) often coincide with aseismic slip and sometimes precede damaging earthquakes. In spite of recent progress in understanding the significance and properties of TES at plate boundaries, their mechanics and scaling are still largely uncertain. Here we evaluate several TES that occurred during the past 20 years on a transform plate boundary in North Iceland. We show that the swarms complement each other spatially with later swarms discouraged from fault segments activated by earlier swarms, which suggests efficient strain release and aseismic slip. The fault area illuminated by earthquakes during swarms may be more representative of the total moment release than the cumulative moment of the swarm earthquakes. We use these findings and other published results from a variety of tectonic settings to discuss general scaling properties for TES. The results indicate that the importance of TES in releasing tectonic strain at plate boundaries may have been underestimated.

  7. Scaling and spatial complementarity of tectonic earthquake swarms

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    Passarelli, Luigi; Rivalta, Eleonora; Jónsson, Sigurjón; Hensch, Martin; Metzger, Sabrina; Jakobsdóttir, Steinunn S.; Maccaferri, Francesco; Corbi, Fabio; Dahm, Torsten

    2018-01-01

    Tectonic earthquake swarms (TES) often coincide with aseismic slip and sometimes precede damaging earthquakes. In spite of recent progress in understanding the significance and properties of TES at plate boundaries, their mechanics and scaling are still largely uncertain. Here we evaluate several TES that occurred during the past 20 years on a transform plate boundary in North Iceland. We show that the swarms complement each other spatially with later swarms discouraged from fault segments activated by earlier swarms, which suggests efficient strain release and aseismic slip. The fault area illuminated by earthquakes during swarms may be more representative of the total moment release than the cumulative moment of the swarm earthquakes. We use these findings and other published results from a variety of tectonic settings to discuss general scaling properties for TES. The results indicate that the importance of TES in releasing tectonic strain at plate boundaries may have been underestimated.

  8. 2014 mainshock-aftershock activity versus earthquake swarms in West\

    Czech Academy of Sciences Publication Activity Database

    Jakoubková, Hana; Horálek, Josef; Fischer, T.

    2018-01-01

    Roč. 175, č. 1 (2018), s. 109-131 ISSN 0033-4553 R&D Projects: GA ČR GAP210/12/2336; GA MŠk(CZ) LM2015079 Institutional support: RVO:67985530 Keywords : West Bohemia/Vogtland * earthquake swarms * mainshock-aftershock sequence * total seismic moment * statistical characteristics of earthquake activities Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 1.591, year: 2016

  9. Subduction megathrust segmentation correlated with earthquake swarm locations appears to be caused by increased stress heterogeneity

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    Holtkamp, S.; Brudzinski, M. R.

    2011-12-01

    For each Mw≥8.5 earthquake with a publicly available finite fault rupture model, we find slip is closely bounded along-strike by earthquake swarms, either prior or subsequent. These earthquake swarms tend to have much larger spatial extents than their cumulative moment would suggest, arguing against a static stress triggering mechanism. In Japan, Chile, Sumatra, and Alaska, earthquake swarms correlate with regions of the plate interface that exhibit low interseismic strain accumulation. This low fault coupling could be a result of aseismic slip during swarms or stress heterogeneity that leads to both swarm occurrence and great earthquake termination. Geodetic studies of earthquake swarms are limited but show several cases with no evidence for aseismic slip during swarms. Moreover, the 1964 Alaska and 2010 Maule earthquakes ruptured through regions with lower coupling than where they terminated, arguing that a factor other than small pre-stress controls where large earthquakes terminate. Large variations in coupling over small spatial scales could produce a fragmented set of small asperities conducive for generating a swarm of smaller earthquakes (Figure). Great earthquakes would be unlikely to rupture through that region as homogeneity of fault zone properties seems to be conducive for generating the largest megathrust earthquakes. Earthquake swarms are one of the better proxies for along-strike segmentation of subduction megathrusts, thereby potentially providing an new method for finding margins with the potential for devastating Mw~9 scale earthquakes. Figure: Cartoon illustrating our preferred hypothesis that increased stress heterogeneity causes earthquake swarm activity and stops large earthquake rupture propagation. Stress on the fault is in grayscale with black being high fault pre-stress. In this model, the heterogeneous stress distribution fosters swarm activity by limiting the size to which an earthquake can grow (leading to a high b

  10. The 2005 volcano-tectonic earthquake swarm in the Andaman Sea: Triggered by the 2004 great Sumatra-Andaman earthquake

    Digital Repository Service at National Institute of Oceanography (India)

    Kundu, B.; Legrand, D.; Gahalaut, K.; Gahalaut, V.K.; Mahesh, P.; KameshRaju, K.A.; Catherine, J.K.; Ambikapthy, A.; Chadha, R.K.

    A 6 day duration earthquakes swarm occurred in the Andaman Sea, 31 days after the giant 2004 Sumatra-Andaman earthquake (Mw 9.2). The swarm occurred less than 100 km from the eastern edge of the 2004 earthquake rupture and is the most energetic ever...

  11. Subsurface imaging across the 2001 Spokane, Washington earthquake swarm

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    Finn, S.; Stephenson, W. J.; Wicks, C. W.; Pratt, T. L.; Odum, J. K.; Angster, S. J.

    2012-12-01

    We acquired 4 km of minivibe reflection seismic data in Spokane, Washington, to image subsurface deformation associated with the 2001 swarm of shallow (collected by USGS as part of ongoing earthquake hazards investigations in the area. In 2001 unexplained earthquake ground shaking as well as audible "booms" were reported over a span of six months (June to November) in the Emerson-Garfield and West Central neighborhoods of Spokane.; the area has since been seismically quiescent. Seismograph recordings of the earthquake swarm suggest shallow depths of hypocenters, yet the local subsurface geology is not well known. Although the source region of this swarm is poorly constrained within Spokane due to sparse seismic station coverage in the area at that time, recent InSAR data analysis has revealed a zone of surface deformation that may be related to the earthquake swarm. This surface deformation consists of an elliptical area about 3 km across that had as much as 15 mm of uplift during 2001. Preliminary processing of the two new seismic profiles provides the first subsurface images of the upper 500 m within the Spokane area across the inferred source region. One seismic profile through downtown Spokane shows a three-layer structure of Holocene valley fill and Quaternary Lake Missoula flood deposits underlain by Tertiary Columbia River basalts. We observe a Columbia River basalt bedrock high of 100 m located between seismic profiles and verified by geologic and aeromagnetic maps. The seismic data also image a paleochannel showing the migration of the Spokane River through time. An inflection within the Quaternary basin sediment reflections suggests uplift from faulting that is consistent with the sense of deformation observed in the InSAR data.

  12. Fluid Induced Earthquakes: From KTB Experiments to Natural Seismicity Swarms.

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    Shapiro, S. A.

    2006-12-01

    ), both heterogeneously distributed in rocks. The results of the analysis of the most significant and best studied (year 2000) earthquake swarm support this concept. Using a numerical model, where spatially correlated diffusivity and criticalit y patches (where patches with higher diffusivity are assumed to be less stable) are considered, we successfully simulate a general seismicity pattern of the swarms, including the spatio-temporal clustering of events and the migration of seismic activity. Therefore, in some cases spontaneously triggered natural seismicity, like earthquake swarms, also shows diffusion-typical signatures mentioned above. However, it seems that there are also some principle differences. They are emphasized in this presentation.

  13. Seismic sequences, swarms, and large earthquakes in Italy

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    Amato, Alessandro; Piana Agostinetti, Nicola; Selvaggi, Giulio; Mele, Franco

    2016-04-01

    In recent years, particularly after the L'Aquila 2009 earthquake and the 2012 Emilia sequence, the issue of earthquake predictability has been at the center of the discussion in Italy, not only within the scientific community but also in the courtrooms and in the media. Among the noxious effects of the L'Aquila trial there was an increase of scaremongering and false alerts during earthquake sequences and swarms, culminated in a groundless one-night evacuation in northern Tuscany in 2013. We have analyzed the Italian seismicity of the last decades in order to determine the rate of seismic sequences and investigate some of their characters, including frequencies, min/max durations, maximum magnitudes, main shock timing, etc. Selecting only sequences with an equivalent magnitude of 3.5 or above, we find an average of 30 sequences/year. Although there is an extreme variability in the examined parameters, we could set some boundaries, useful to obtain some quantitative estimates of the ongoing activity. In addition, the historical catalogue is rich of complex sequences in which one main shock is followed, seconds, days or months later, by another event with similar or higher magnitude We also analysed the Italian CPT11 catalogue (Rovida et al., 2011) between 1950 and 2006 to highlight the foreshock-mainshock event couples that were suggested in previous studies to exist (e.g. six couples, Marzocchi and Zhuang, 2011). Moreover, to investigate the probability of having random foreshock-mainshock couples over the investigated period, we produced 1000 synthetic catalogues, randomly distributing in time the events occured in such period. Preliminary results indicate that: (1) all but one of the the so-called foreshock-mainshock pairs found in Marzocchi and Zhuang (2011) fall inside previously well-known and studied seismic sequences (Belice, Friuli and Umbria-Marche), meaning that suggested foreshocks are also aftershocks; and (2) due to the high-rate of the italian

  14. A fluid-driven earthquake swarm on the margin of the Yellowstone caldera

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    Shelly, David R.; Hill, David P.; Massin, Frederick; Farrell, Jamie; Smith, Robert B.; Taira, Taka'aki

    2013-01-01

    Over the past several decades, the Yellowstone caldera has experienced frequent earthquake swarms and repeated cycles of uplift and subsidence, reflecting dynamic volcanic and tectonic processes. Here, we examine the detailed spatial-temporal evolution of the 2010 Madison Plateau swarm, which occurred near the northwest boundary of the Yellowstone caldera. To fully explore the evolution of the swarm, we integrated procedures for seismic waveform-based earthquake detection with precise double-difference relative relocation. Using cross-correlation of continuous seismic data and waveform templates constructed from cataloged events, we detected and precisely located 8710 earthquakes during the three-week swarm, nearly four times the number of events included in the standard catalog. This high-resolution analysis reveals distinct migration of earthquake activity over the course of the swarm. The swarm initiated abruptly on January 17, 2010 at about 10 km depth and expanded dramatically outward (both shallower and deeper) over time, primarily along a NNW-striking, ~55º ENE-dipping structure. To explain these characteristics, we hypothesize that the swarm was triggered by the rupture of a zone of confined high-pressure aqueous fluids into a pre-existing crustal fault system, prompting release of accumulated stress. The high-pressure fluid injection may have been accommodated by hybrid shear and dilatational failure, as is commonly observed in exhumed hydrothermally affected fault zones. This process has likely occurred repeatedly in Yellowstone as aqueous fluids exsolved from magma migrate into the brittle crust, and it may be a key element in the observed cycles of caldera uplift and subsidence.

  15. InSAR Analysis of the 2011 Hawthorne (Nevada) Earthquake Swarm: Implications of Earthquake Migration and Stress Transfer

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    Zha, X.; Dai, Z.; Lu, Z.

    2015-12-01

    The 2011 Hawthorne earthquake swarm occurred in the central Walker Lane zone, neighboring the border between California and Nevada. The swarm included an Mw 4.4 on April 13, Mw 4.6 on April 17, and Mw 3.9 on April 27. Due to the lack of the near-field seismic instrument, it is difficult to get the accurate source information from the seismic data for these moderate-magnitude events. ENVISAT InSAR observations captured the deformation mainly caused by three events during the 2011 Hawthorne earthquake swarm. The surface traces of three seismogenic sources could be identified according to the local topography and interferogram phase discontinuities. The epicenters could be determined using the interferograms and the relocated earthquake distribution. An apparent earthquake migration is revealed by InSAR observations and the earthquake distribution. Analysis and modeling of InSAR data show that three moderate magnitude earthquakes were produced by slip on three previously unrecognized faults in the central Walker Lane. Two seismogenic sources are northwest striking, right-lateral strike-slip faults with some thrust-slip components, and the other source is a northeast striking, thrust-slip fault with some strike-slip components. The former two faults are roughly parallel to each other, and almost perpendicular to the latter one. This special spatial correlation between three seismogenic faults and nature of seismogenic faults suggest the central Walker Lane has been undergoing southeast-northwest horizontal compressive deformation, consistent with the region crustal movement revealed by GPS measurement. The Coulomb failure stresses on the fault planes were calculated using the preferred slip model and the Coulomb 3.4 software package. For the Mw4.6 earthquake, the Coulomb stress change caused by the Mw4.4 event increased by ~0.1 bar. For the Mw3.9 event, the Coulomb stress change caused by the Mw4.6 earthquake increased by ~1.0 bar. This indicates that the preceding

  16. The West Bohemian 2008-earthquake swarm: When, where, what size and data

    Czech Academy of Sciences Publication Activity Database

    Horálek, Josef; Fischer, Tomáš; Boušková, Alena; Michálek, Jan; Hrubcová, Pavla

    2009-01-01

    Roč. 53, č. 3 (2009), s. 351-358 ISSN 0039-3169 Institutional research plan: CEZ:AV0Z30120515 Keywords : West Bohemia/Vogtland * earthquake swarm * WEBNET Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 1.000, year: 2009

  17. Evidence from the AD 2000 Izu islands earthquake swarm that stressing rate governs seismicity

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    Toda, Shinji; Stein, Ross S.; Sagiya, Takeshi

    2002-09-01

    Magma intrusions and eruptions commonly produce abrupt changes in seismicity far from magma conduits that cannot be associated with the diffusion of pore fluids or heat. Such `swarm' seismicity also migrates with time, and often exhibits a `dog-bone'-shaped distribution. The largest earthquakes in swarms produce aftershocks that obey an Omori-type (exponential) temporal decay, but the duration of the aftershock sequences is drastically reduced, relative to normal earthquake activity. Here we use one of the most energetic swarms ever recorded to study the dependence of these properties on the stress imparted by a magma intrusion. A 1,000-fold increase in seismicity rate and a 1,000-fold decrease in aftershock duration occurred during the two-month-long dyke intrusion. We find that the seismicity rate is proportional to the calculated stressing rate, and that the duration of aftershock sequences is inversely proportional to the stressing rate. This behaviour is in accord with a laboratory-based rate/state constitutive law, suggesting an explanation for the occurrence of earthquake swarms. Any sustained increase in stressing rate-whether due to an intrusion, extrusion or creep event-should produce such seismological behaviour.

  18. Monitoring the West Bohemian earthquake swarm in 2008/2009 by a temporary small-aperture seismic array

    DEFF Research Database (Denmark)

    Hiemer, Stefan; Rössler, Dirk; Scherbaum, Frank

    2012-01-01

    The most recent intense earthquake swarm in West Bohemia lasted from 6 October 2008 to January 2009. Starting 12 days after the onset, the University of Potsdam monitored the swarm by a temporary small-aperture seismic array at 10 km epicentral distance. The purpose of the installation was a comp...

  19. Earthquake swarm activity in the Oaxaca segment of Middle American Subduction Zone

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    Brudzinski, M. R.; Cabral, E.; Arciniega-Ceballos, A.

    2013-05-01

    An outstanding question in geophysics is the degree to which the newly discovered family of slow fault slip behaviors is related to more traditional earthquakes, especially since theoretical predictions indicate slip in the deeper transitional zone promotes failure in the shallower seismogenic zone. The Oaxacan segment of the Middle American Subduction zone is a natural region to pursue detailed studies of the spectrum of fault slip due to the unusually shallow subduction angle and short trench-to-coast distances that bring broad portions of the seismogenic and transitional zones of the plate interface inland. A deployment of broadband seismometers in this region has improved the network coverage to ~70 km station spacing since 2006, providing new opportunities to investigate smaller seismic phenomena. While characterization of tectonic tremor has been a prominent focus of this deployment, the improved network has also revealed productive earthquake swarms, whose sustained periods of similar magnitude earthquakes are also thought to be driven by slow slip. We identify a particularly productive earthquake swarm in July 2006 (~600 similar earthquakes detected), which occurred during a week-long episode of tectonic tremor and geodetically detected slow slip. Using a multi-station "template matching" waveform cross correlation technique, we have been able to detect and locate swarm earthquakes several orders of magnitude smaller than that of traditional processing, particularly during periods of increased background activity, because the detector is finely tuned to events with similar hypocentral location and focal mechanism. When we scan for repeats of the event families detected in the July 2006 sequence throughout the 6+ years since, we find these families were also activated during several other slow slip episodes, which indicates a link between slow slip in the transition zone and earthquakes at the downdip end of the seismogenic portion of the megathrust.

  20. IDENTIFICATION OF EARTHQUAKE AFTERSHOCK AND SWARM SEQUENCES IN THE BAIKAL RIFT ZONE

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    N. A. Radziminovich

    2015-09-01

    Full Text Available The catalog of earthquakes (КR³6.6 which occurred in the Baikal rift zone (BRZ was declastered, and the results are presented in the article. Aftershocks of seismic events (КR³12.5 were determined by the software developed by V.B. Smirnov (Lomonosov Moscow State University with application of the algorithm co-authored by G.M. Molchan and O.E. Dmitrieva. To ensure proper control of the software application, aftershocks were also selected manually. The results of declustering show that aftershocks of the earthquakes (КR³12.5 account for about 25 per cent of all seismic events in the regional catalog. Aftershocks accompanied 90 per cent of all the earthquakes considered as main shocks. Besides, earthquake swarms, including events with КR³11, were identified. The results of this study show that, in the BRZ, the swarms and strong events with aftershocks are not spatially separated, and this conclusion differs from the views of the previous studies that reviewed data from a shorter observation period. Moreover, it is noted that the swarms may consist of several main shocks accompanied by aftershocks. The data accumulated over the last fifty years of instrumental observations support the conclusion made earlier that the swarms in BRZ occur mainly in the north-eastward direction from Lake Baikal and also confirm the trend of a small number of aftershocks accompanying earthquakes in the south-western part of the Baikal rift zone.

  1. Rushan earthquake swarm in eastern China and its indications of fluid-triggered rupture

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    Zheng, Jian-Chang; Li, Dong-Mei; Li, Cui-Qin; Wang, Peng; Xu, Chang-Peng

    2017-12-01

    An extraordinary earthquake swarm occurred at Rushan on the Jiaodong Peninsula from October 1, 2013, onwards, and more than 12,000 aftershocks had been detected by December 31, 2015. All the activities of the whole swarm were recorded at the nearest station, RSH, which is located about 12 km from the epicenter. We examine the statistical characteristics of the Rushan swarm in this paper using RSH station data to assess the arrival time difference, t_{{{S} - {P}}} , of Pg and Sg phases. A temporary network comprising 18 seismometers was set up on May 6, 2014, within the area of the epicenter; based on the data from this network and use of the double difference method, we determine precise hypocenter locations. As the distribution of relocated sources reveals migration of seismic activity, we applied the mean-shift cluster method to perform clustering analysis on relocated catalogs. The results of this study show that there were at least 16 clusters of seismic activities between May 6, 2014, and June 30, 2014, and that each was characterized by a hypocenter spreading process. We estimated the hydraulic diffusivity, D, of each cluster using envelope curve fitting; the results show that D values range between 1.2 and 3.5 m2/d and that approximate values for clusters on the edge of the source area are lower than those within the central area. We utilize an epidemic-type aftershock sequence (ETAS) model to separate external triggered events from self-excited aftershocks within the Rushan swarm. The estimated parameters for this model suggest that α = 1.156, equivalent to sequences induced by fluid-injection, and that the forcing rate (μ) implies just 0.15 events per day. These estimates indicate that around 3% of the events within the swarm were externally triggered. The fact that variation in μ is synchronous with swarm activity implies that pulses in fluid pressure likely drove this series of earthquakes.

  2. The geological manifestation of earthquake swarms: Evidence from the Adamello Batholith in the Southern Italian Alps

    Science.gov (United States)

    Dempsey, E. D.; Holdsworth, R. E.; Di Toro, G.; Bistacchi, A.

    2012-12-01

    Earthquake swarms are often characterised by clusters of seismic events with highly variable earthquake focal mechanisms, irrespective of whether or not they are associated with a main shock event. Our current understanding of how such multiple seismic events manifest themselves in the geological record is based largely on the Hill (1977) and Sibson (1996) 'fracture mesh' models. Whilst these simple models are theoretically sound for homogeneous isotropic rock masses, they do not account for the effects of variably oriented pre-existing mechanical anisotropies and how these may lead to a more complex fracture evolution and geologic strain. Interconnected networks of faults and veins filled with zeolites and other hydrothermal minerals are widespread in many orogenic terrains, including deformed granitic plutons and regions of metamorphic basement. Typically the fracture fills formed late in the tectonic history, at relatively low temperatures (e.g. stress loading and reactivation of widely distributed pre-existing structures (contacts, joints, shear zone fabrics, faults). The differing orientations of the pre-existing structures relative to the far-field and near-field stresses lead to the simultaneous development of interlinked reverse, strike-slip and extensional faults. The kinematic complexity and cyclic nature of the hydraulically-induced fracturing provides compelling evidence that the mineralised fracture systems represent a geologic manifestation of foreshock-aftershock swarm development. Our proposal highlights the key role of crustal fluids during earthquake swarm development and the inherent geometrical complexities that may result from the reactivation of pre-existing anisotropies in rocks.

  3. Hydraulically-induced earthquake swarms: Geological evidence from the Adamello Batholith in the Southern Italian Alps.

    Science.gov (United States)

    Dempsey, Eddie; Holdsworth, Bob; DiToro, Giulio; Bistacchi, Andrea

    2013-04-01

    Earthquake swarms are often characterised by clusters of seismic events with highly variable earthquake focal mechanisms, irrespective of whether or not they are associated with a main shock event. Our current understanding of how such events manifest themselves in the geological record is based largely on the Hill (1977) and Sibson (1996) 'fracture mesh' models. Whilst these simple models are theoretically sound for homogeneous isotropic rock masses, they do not account for the effects of variably oriented pre-existing mechanical anisotropies and how these may lead to a more complex fracture evolution and geologic strain. Interconnected networks of faults and veins filled with zeolites and other hydrothermal minerals are widespread in many orogenic terrains, including deformed granitic plutons and regions of metamorphic basement. Typically the fracture fills formed late in the tectonic history, at relatively low temperatures (e.g. stress loading and reactivation of widely distributed pre-existing structures (contacts, joints, shear zone fabrics, faults). The differing orientations of the pre-existing structures relative to the far-field and near-field stresses lead to the simultaneous development of interlinked reverse, strike-slip and extensional faults. The kinematic complexity and cyclic nature of the hydraulically-induced fracturing provides compelling evidence that the mineralised fracture systems represent a geologic manifestation of foreshock-aftershock swarm development. Our proposal highlights the key role of crustal fluids during earthquake swarm development and the inherent geometrical complexities that may result from the reactivation of pre-existing anisotropies in rocks.

  4. Swarms of repeating long-period earthquakes at Shishaldin Volcano, Alaska, 2001-2004

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    Petersen, Tanja

    2007-01-01

    During 2001–2004, a series of four periods of elevated long-period seismic activity, each lasting about 1–2 months, occurred at Shishaldin Volcano, Aleutian Islands, Alaska. The time periods are termed swarms of repeating events, reflecting an abundance of earthquakes with highly similar waveforms that indicate stable, non-destructive sources. These swarms are characterized by increased earthquake amplitudes, although the seismicity rate of one event every 0.5–5 min has remained more or less constant since Shishaldin last erupted in 1999. A method based on waveform cross-correlation is used to identify highly repetitive events, suggestive of spatially distinct source locations. The waveform analysis shows that several different families of similar events co-exist during a given swarm day, but generally only one large family dominates. A network of hydrothermal fractures may explain the events that do not belong to a dominant repeating event group, i.e. multiple sources at different locations exist next to a dominant source. The dominant waveforms exhibit systematic changes throughout each swarm, but some of these waveforms do reappear over the course of 4 years indicating repeatedly activated source locations. The choked flow model provides a plausible trigger mechanism for the repeating events observed at Shishaldin, explaining the gradual changes in waveforms over time by changes in pressure gradient across a constriction within the uppermost part of the conduit. The sustained generation of Shishaldin's long-period events may be attributed to complex dynamics of a multi-fractured hydrothermal system: the pressure gradient within the main conduit may be regulated by temporarily sealing and reopening of parallel flow pathways, by the amount of debris within the main conduit and/or by changing gas influx into the hydrothermal system. The observations suggest that Shishaldin's swarms of repeating events represent time periods during which a dominant source

  5. Principal Earthquakes: Theory and Observations from the 2008 West Bohemia Swarm

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    Vavrycuk, V.

    2011-12-01

    Earthquakes that occur on optimally oriented fault planes with respect to the tectonic stress regime display two distinct focal mechanisms and are fundamental characteristics of each seismically active region. These earthquakes, which we term 'principal', need not coincide with the strongest earthquakes or need not occur along the major active faults in the region. Theoretical stability analysis of diversely oriented fault planes under a given stress reveals that the focal mechanisms connected with unstable fault planes should not be very distinct from those of the principal earthquakes. The P/T axes form clusters with a typical two-wing or butterfly pattern. This pattern is particularly visible when constructing the failure curves defined as a projection of the Mohr-Coulomb failure criterion in the Mohr's diagram onto the focal sphere. The position, shape and size of the failure curves depend on the stress orientation, shape ratio, friction and on the size of the instability area in the Mohr's diagram. The theoretical analysis is tested using accurately determined focal mechanisms of 99 micro-earthquakes that occurred during the 2008 earthquake swarm in the West Bohemia/Vogtland region. The distribution of P/T axes reveals the butterfly wing pattern predicted in numerical modelling. The activated fault planes concentrate in the area of validity of the Mohr-Coulomb failure criterion. The average friction of faults is 0.5 and corresponds to a deviation of 32° of the principal faults from the σ1 axis. The left-lateral strike-slip principal fault was the most active fault during the swarm. It shows little geological expression at the surface but it is clearly defined by a linear cluster of hypocentres at depth. The right-lateral strike-slip principal fault was less active but it is geologically well manifested on the Earth's surface.

  6. Seismotectonics of the Nicobar Swarm and the geodynamic implications for the 2004 Great Sumatran Earthquake

    Science.gov (United States)

    Lister, Gordon

    2017-04-01

    The Great Sumatran Earthquake took place on 26th December 2004. One month into the aftershock sequence, a dense swarm of earthquakes took place beneath the Andaman Sea, northeast of the Nicobar Islands. The swarm continued for ˜11 days, rapidly decreasing in intensity towards the end of that period. Unlike most earthquake swarms, the Nicobar cluster was characterised by a large number of shocks with moment magnitude exceeding five. This meant that centroid moment tensor data could be determined, and this data in turn allows geometric analysis of inferred fault plane motions. The classification obtained using program eQuakes shows aftershocks falling into distinct spatial groups. Thrusts dominate in the south (in the Sumatran domain), and normal faults dominate in the north (in the Andaman domain). Strike-slip faults are more evenly spread. They occur on the Sumatran wrench system, for example, but also on the Indian plate itself. Orientation groups readily emerge from such an analysis. Temporal variation in behaviour is immediately evident, changing after ˜12 months. Orientation groups in the first twelve months are consistent with margin perpendicular extension beneath the Andaman Sea (i.e. mode II megathrust behaviour) whereas afterward the pattern of deformation appears to have reverted to that expected in consequence of relative plate motion. In the first twelve months, strike-slip motion appears to have taken place on faults that are sub-parallel to spreading segments in the Andaman Sea. By early 2006 however normal fault clusters formed that showed ˜N-S extension across these spreading segments had resumed, while the overall density of aftershocks in the Andaman segment had considerably diminished. Throughout this entire period the Sumatran segment exhibited aftershock sequences consistent with ongoing Mode I megathrust behaviour. The Nicobar Swarm marks the transition from one sort of slab dynamics to the other. The earthquake swarm may have been

  7. The October-November 2008 earthquake swarm in Vogtland/NW-Bohemia: first results of focal mechanism determinations

    Science.gov (United States)

    Plenefisch, T.

    2009-04-01

    Vogtland/NW-Bohemia, an area at the border between Germany and Czech Republic, is known as one of the most interesting earthquake swarm regions in Europe. This special type of seismicity is expressed by the accumulation of a huge number of events of similar magnitude and their episodic reoccurrence. During a swarm hundreds or thousands of earthquakes without a distinct main shock occur spatially and temporally clustered. The most recent swarm of 2008 occurred between the 6th of October and the middle of November. With more than 20000 detectable events and magnitudes up to 4 it is the most prominent one since the big swarm in 1985/86. Due to the strength of the swarm and the increased number of stations in the Vogtland/NW-Bohemia region the swarm of 2008 offers various possibilities to investigate the peculiarities of swarms and the special seismotectonic situation of the Vogtland/NW-Bohemia region. This study concentrates on the determination of earthquake focal mechanisms. Mechanisms for all events with magnitudes ML ≥ 2.7 have been calculated. The ensemble of focal mechanism is analysed with respect to variations within the swarm as well as changes with respect to the mechanisms of the former swarms of 2000 and 1985/86. For example, the focal mechanism of one of the strongest events (10.10.2008, 08:08 UT) represents a strike slip mechanism with a slight normal faulting component. It is similar to the mechanisms of the stronger events of 2000 and 1985/86. The strike direction of one nodal plane (almost N-S) reflects the strike of the Marianske Lazne fault zone and parallel striking fault systems. The focal mechanisms are used to invert for the regional stress field which then is compared to the stress field in Central Europe.

  8. Modeling the Interaction between Fluid Pressure and Faulting in an Earthquake Swarm at Long Valley Caldera

    Science.gov (United States)

    Hsieh, P. A.; Shelly, D. R.; Hill, D. P.

    2016-12-01

    Rapid migration of hypocenters during the 2014 Long Valley Caldera, California, earthquake swarm suggests that the activity was initiated and sustained by fluids, composed primarily of water and carbon dioxide, exsolved from underlying magma (Shelly et al., 2016, JGR, doi:10.1002/2015JB012719). To investigate how fluid pressure and faulting may co-evolve, we develop a simulation model that couples fluid flow with mechanical stress, while treating earthquakes with the "static/dynamic friction" approach developed by McClure and Horne (2010, Geotherm. Resour. Counc. Trans., 34, 381-396). We set up the model to represent a vertical, permeable fault (divided into a grid of elements) bounded by impermeable rock in a strike-slip tectonic environment. At the start of the simulation, a high-pressure source is introduced at depth to represent the injection of magmatic-derived fluids along the fault. The fluid flow component of the model simulates diffusion of the source pressure into the fault, and halts when the pressure increase at a fault element is sufficient to cause failure (slip). Next, the mechanical stress component of the model calculates the stress changes that result from the slip. Because these stress changes could induce surrounding elements to slip, the model iterates through this chain-reaction process until a stable configuration is achieved (i.e., slipped elements do not induce further slips).The patch of slipped elements represents an earthquake in the model. The permeability of the patch is increased to represent the effect of shear displacement, and the pressure diffusion simulation resumes. Although this model implements a simplified representation of the earthquake mechanism, it is able to mimic (using reasonable rock properties) the overall character of a local swarm of approximately 1000 earthquakes (-0.9 < M < 2.8) that occurred during 7 July 2014 in Long Valley Caldera.

  9. Earthquake statistics, spatiotemporal distribution of foci and source mechanisms as a key to understanding of causes leading to the West Bohemia/Vogtland earthquake swarms

    Science.gov (United States)

    Horalek, Josef; Jakoubkova, Hana

    2017-04-01

    The origin of earthquake swarms is still unclear. The swarms typically occur at the plate margins but also in intracontinental areas. West Bohemia-Vogtland represents one of the most active intraplate earthquake-swarm areas in Europe. It is characterised by a frequent reoccurrence of ML exceptional non-swarm activity (mainshock-aftershock sequences) up to magnitudes ML = 4.5, stroke the region in May to August 2014, the events were also located in the NK swarm-focal belt. We analysed geometry of the NK focal zone applying the double-difference method to seismicity in the period 1997 - 2014. The swarms are located close to each other at depths between 6 and 13 km, the 2014 maishock-aftershock sequences among them. The 2000 and 2008 swarms were located on the same portion of the NK fault, similarly the swarms of 1997, 2011 and 2013 also occurred on the same fault segment. Other fault segment hosted three mainshock-aftershock sequences of 2014. The individual swarms differ considerably in their evolution, mainly in the rate of the seismic-moment release and foci migration. The frequency-magnitude distributions of all the swarms show bimodal-like character: the most events obey the b-value = 1.0 distribution, however, a group of the largest events ( ML > 2.8) depart significantly from it. Furthermore, we disclose that all the ML > 2.8 swarm events, which occurred in the given time span, are located in a few dense clusters. It implies that the most of seismic energy in the individual swarms has been released in step by step rupturing of one or a few asperities. The source mechanisms have been retrieved in the full moment-tensor description (MT). The mechanism patters of the individual swarms indicate their complexity. All the swarms exhibit both oblique-normal and oblique-thrust faulting but the former prevails. We found a several families of mechanisms, which fit well geometry of respective fault segments being determined by means of the double-difference location. MTs

  10. Long-Span Continuous Self-Potential Measurements Around Earthquake Swarms for Monitoring Crustal Activity

    Science.gov (United States)

    Yoshimura, R.; Oshiman, N.; Yamazaki, K.; Uyeshima, M.; Ogawa, T.

    2008-12-01

    Earthquake swarm activity has been continuously observed around the southeastern flank of Ontake stratovolcano since 1976. A large earthquake with the depth about 2 km and a magnitude of 6.8 occurred in 1984 in the southeastern flank of the volcano. Recently, Kimata et al. (2004) revealed uplift ground deformation above the earthquake swarm area by using repeated leveling. Furthermore, MagnetoTelluric (MT) soundings estimated a low resistivity region with the depth about 2km beneath the uplift area (Kasaya et al., 2002). In order to investigate a relationship between tectonic movements and subsurface low resistivity zone, Yoshimura et al. (2007) carried out self-potential (SP) measurements from 2003 to 2005 around the earthquake swarm areas. As the result of SP measurements, a torus-shape positive SP anomaly has been detected at the eastern part of the survey profile. This anomaly is located between recent active clusters of earthquakes and near the ground uplift detected by Kimata et al. (2004). Given that the obtained anomaly delineates the subsurface fluid"fs motion due to thermal or crustal activities, it could be expected that the anomaly varies in association with fluctuation of crustal activities. In February 2007, we established a continuous SP observation network with the aim of monitoring the crustal/hydrothermal activity by reference to the obtained SP distribution. This network consists of 8 Pb- PbCl2 electrodes and uses metallic telephone lines as insulated cables for measuring SP. Voltage differences between electrodes are measured at an interval of 1 sec. This observation technique, called "Network-MT", has been developed to determine large-scale electrical conductivity structure and the spatial distribution of the telluric potentials (Uyeshima, 2007). As a preliminary result of longitudinal data analysis, night time daily median values showed remarkable stepwise SP time variations with relaxation time about 15 days in August 2007. Additionally

  11. Earthquake swarm of Himachal Pradesh in northwest Himalaya and its seismotectonic implications

    Science.gov (United States)

    Singh, Rakesh; Prasath, R. Arun; Paul, Ajay; Kumar, Naresh

    2018-02-01

    On the 27th of August 2016, a seismic swarm activity consisting of 58 earthquakes (1.5 ≤ ML ≤ 4.4), which occurred in Rampur area of the Kullu-Rampur Tectonic window of Himachal Pradesh in Northwest Himalaya. The epicenters of these events are located at the northern front of the Berinag Thrust in its hanging wall. To better understand the seismotectonics of this region, we analyzed the spectral source parameters and source mechanism of this swam activity. Spectral analysis shows the low stress drop values (from 0.05 to 28.9 bars), suggesting that the upper crust has low strength to withstand accumulated strain energy in this region. The Moment Tensor solutions of 12 earthquakes (≥2.7ML) obtained by waveform inversion yield the shallow centroid depths between 5 and 10 km. All these events are of dominantly thrust fault mechanism having an average dip angle of ∼30°. The P-axes and the maximum horizontal compressive stresses are NE-SW oriented; the relative motion of the Indian Plate. The present study reveals that the swarm activity in the Himachal region of NW Himalaya is related to the out-of-sequence thrusting or the Lesser Himalayan Duplex system.

  12. Earthquake swarm associated with volcanic eruption, CuraCoa Reef Area, Northern Tonga, July 1973

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    G. K. SUTTON

    1974-06-01

    Full Text Available A submarine volcanic eruption near Curagoa Reef, first observed on 12 J u l y 1973 (U.T. f r om Tafalii Island, northern Tonga, was associated with an e a r t h q u a k e swarm in t h e same area. The swarm began about 03'1 on I I J u l y and died away gradually about 07'' on 13 J u l y , ft comprised 504 events of magnitude Mi, „2= 3.4, the largest being of magnitude Ml = 5.1. The swarm area for these comparatively low magnitude earthquakes was abnormally large The v a r i a t i o n in r a t e of e a r t h q u a k e occurrence during t h e s w a rm shows two distinct stages, one similar to t h a t in a foresliock sequence, and t h e other like t h a t in a n a f t e r s h o c k sequence, with t h e largest events occurring between t h e two. The average value of b, defining t h e f r e q u e n c y - m a g n i t u d e relationship, was high: 1.77 ± 0.15. Furthermore, this p a r a m e t e r varied during the course of t h e swarm, a decrease in t h e b value f r om 1.8 to 1.1 being followed by a sharp increase to 2.5 a f t e r t h e largest earthquakes and principal volcanic eruption. Values of seismic moment were obtained from A B for 118 e a r t h q u a k es which were well recorded by long-period seismographs. Other source charact e r i s t i c s were determined from the difference between t h e l o g a r i t hm of seismic moment and the local magnitude. The source sizes were found to he u n u s u a l l y large. There was a t i m e variation of source properties during the swarm. The v a r i a t i o n of t h e displacement shows an inverse correlation with t h e variation of the coefficient b. The swarm produced very d i s t i n c t i v e T phases, well recorded at a hydrophone near Wake Island and at seismograph stations s i t u a t e d on t h e oceanic side of the Tonga Trench: these were not recorded at seismograph stations within the island arcs.

  13. Modeling crustal deformation and rupture processes related to upwelling of deep CO2-rich fluids during the 1965-1967 Matsushiro Earthquake Swarm in Japan

    Energy Technology Data Exchange (ETDEWEB)

    Cappa, F.; Rutqvist, J.; Yamamoto, K.

    2009-05-15

    In Matsushiro, central Japan, a series of more than 700,000 earthquakes occurred over a 2-year period (1965-1967) associated with a strike-slip faulting sequence. This swarm of earthquakes resulted in ground surface deformations, cracking of the topsoil, and enhanced spring-outflows with changes in chemical compositions as well as carbon dioxide (CO{sub 2}) degassing. Previous investigations of the Matsushiro earthquake swarm have suggested that migration of underground water and/or magma may have had a strong influence on the swarm activity. In this study, employing coupled multiphase flow and geomechanical modelling, we show that observed crustal deformations and seismicity can have been driven by upwelling of deep CO{sub 2}-rich fluids around the intersection of two fault zones - the regional East Nagano earthquake fault and the conjugate Matsushiro fault. We show that the observed spatial evolution of seismicity along the two faults and magnitudes surface uplift, are convincingly explained by a few MPa of pressurization from the upwelling fluid within the critically stressed crust - a crust under a strike-slip stress regime near the frictional strength limit. Our analysis indicates that the most important cause for triggering of seismicity during the Matsushiro swarm was the fluid pressurization with the associated reduction in effective stress and strength in fault segments that were initially near critically stressed for shear failure. Moreover, our analysis indicates that a two order of magnitude permeability enhancement in ruptured fault segments may be necessary to match the observed time evolution of surface uplift. We conclude that our hydromechanical modelling study of the Matsushiro earthquake swarm shows a clear connection between earthquake rupture, deformation, stress, and permeability changes, as well as large-scale fluid flow related to degassing of CO{sub 2} in the shallow seismogenic crust. Thus, our study provides further evidence of the

  14. Shallow earthquake swarms in southern Ryukyu area: manifestation of dynamics of fluid and/or magma plumbing system revealed by teleseismic and regional datasets

    Czech Academy of Sciences Publication Activity Database

    Špičák, Aleš; Vaněk, Jiří

    2017-01-01

    Roč. 106, č. 3 (2017), s. 959-965 ISSN 1437-3254 Institutional support: RVO:67985530 Keywords : earthquake swarms * Southern Ryukyu * Wadati-Benioff zone Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 2.283, year: 2016

  15. Regional tectonic setting for the Trinidad earthquake swarms (2000-2012) from gravity and magnetic data

    Science.gov (United States)

    Finn, Carol A.; Kass, Mason A.; Smith, Bruce D.

    2015-01-01

    Earthquakes in the Raton basin near Trinidad, Colorado, (Figure 1) are located (Rubenstein et. al., 2014) near a major gravity and magnetic boundary. These earthquakes also occur in an area of hydrocarbon production that includes several high-capacity produced water injection wells. This presentation gives a very basic outline of the relation between the earthquakes, the potential field data, and possible basement structure.

  16. Fluid-faulting evolution in high definition: Connecting fault structure and frequency-magnitude variations during the 2014 Long Valley Caldera, California earthquake swarm

    Science.gov (United States)

    Shelly, David R.; Ellsworth, William L.; Hill, David P.

    2016-01-01

    An extended earthquake swarm occurred beneath southeastern Long Valley Caldera between May and November 2014, culminating in three magnitude 3.5 earthquakes and 1145 cataloged events on 26 September alone. The swarm produced the most prolific seismicity in the caldera since a major unrest episode in 1997-1998. To gain insight into the physics controlling swarm evolution, we used large-scale cross-correlation between waveforms of cataloged earthquakes and continuous data, producing precise locations for 8494 events, more than 2.5 times the routine catalog. We also estimated magnitudes for 18,634 events (~5.5 times the routine catalog), using a principal component fit to measure waveform amplitudes relative to cataloged events. This expanded and relocated catalog reveals multiple episodes of pronounced hypocenter expansion and migration on a collection of neighboring faults. Given the rapid migration and alignment of hypocenters on narrow faults, we infer that activity was initiated and sustained by an evolving fluid pressure transient with a low-viscosity fluid, likely composed primarily of water and CO2 exsolved from underlying magma. Although both updip and downdip migration were observed within the swarm, downdip activity ceased shortly after activation, while updip activity persisted for weeks at moderate levels. Strongly migrating, single-fault episodes within the larger swarm exhibited a higher proportion of larger earthquakes (lower Gutenberg-Richter b value), which may have been facilitated by fluid pressure confined in two dimensions within the fault zone. In contrast, the later swarm activity occurred on an increasingly diffuse collection of smaller faults, with a much higher b value.

  17. Some possible correlations between electro-magnetic emission and seismic activity during West Bohemia 2008 earthquake swarm

    Directory of Open Access Journals (Sweden)

    P. Kolář

    2010-10-01

    Full Text Available A potential link between electromagnetic emission (EME and seismic activity (SA has been the subject of scientific speculations for a long time. EME versus SA relations obtained during the 2008 earthquake swarm which occurred in West Bohemia are presented. First, a brief characterisation of the seismic region and then the EME recording method and data analysis will be described. No simple direct link between EME and SA intensity was observed, nevertheless a deeper statistical analysis indicates: (i slight increase of EME activity in the time interval 60 to 30 min before a seismic event with prevalent periods about 10 min, (ii some gap in EME activity approximately 2 h after the event, and (iii again a flat maximum about 4 h after the seismic events. These results qualitatively correspond with the observations from other seismically active regions (Fraser-Smith et al., 1990. The global decrease of EME activity correlating with the swarm activity decay was also observed. Due to the incomplete EME data and short observation time, these results are limited in reliability and are indicative only.

  18. The 2006 Bahía Asunción Earthquake Swarm: Seismic Evidence of Active Deformation Along the Western Margin of Baja California Sur, Mexico

    Science.gov (United States)

    Munguía, Luis; Mayer, Sergio; Aguirre, Alfredo; Méndez, Ignacio; González-Escobar, Mario; Luna, Manuel

    2016-10-01

    The study of the Bahía Asunción earthquake swarm is important for two reasons. First, the earthquakes are clear evidence of present activity along the zone of deformation on the Pacific margin of Baja California. The swarm, with earthquakes of magnitude M w of up to 5.0, occurred on the coastline of the peninsula, showing that the Tosco-Abreojos zone of deformation is wider than previously thought. Second, the larger earthquakes in the swarm caused some damage and much concern in Bahía Asunción, a small town located in the zone of epicenters. We relocated the larger earthquakes with regional and/or local seismic data. Our results put the earthquake sources below the urban area of Bahía Asunción, at 40-50 km to the north of the teleseismically determined epicenters. In addition, these new locations are in the area of epicenters of many smaller events that were located with data from local temporary stations. This area trends in an E-W direction and has dimensions of approximately 15 km by 10 km. Most earthquakes had sources at depths that are between 4 and 9 km. A composite focal mechanism for the smaller earthquakes indicated right-lateral strike-slip motion and pure-normal faulting occurred during this swarm. Interestingly, the ANSS earthquake catalog of the United States Geological Survey (USGS) reported each one of these faulting styles for two large events of the swarm, with one of these earthquakes occurring 2 days before the other one. We associate the earthquake with strike-slip mechanism with the San Roque Fault, and the earthquake with the normal faulting style with the Asunción Fault. However, there is need of further study to verify this possible relation between the faults and the earthquakes. In addition, we recorded peak accelerations of up to 0.63 g with an accelerometer installed in Bahía Asunción. At this site, an earthquake of M w 4.9 produced those high values at a distance of 4.1 km. We also used the acceleration dataset from this site

  19. Seismological mechanism analysis of 2015 Luanxian swarm, Hebei province,China

    Science.gov (United States)

    Tan, Yipei; Liao, Xu; Ma, Hongsheng; Zhou, Longquan; Wang, Xingzhou

    2017-04-01

    The seismological mechanism of an earthquake swarm, a kind of seismic burst activity, means the physical and dynamic process in earthquakes triggering in the swarm. Here we focus on the seismological mechanism of 2015 Luanxian swarm in Hebei province, China. The process of digital seismic waveform data processing is divided into four steps. (1) Choose the three components waveform of earthquakes in the catalog as templates, and detect missing earthquakes by scanning the continues waveforms with matched filter technique. (2) Recalibrate P and S-wave phase arrival time using waveform cross-correlation phase detection technique to eliminate the artificial error in phase picking in the observation report made by Hebei seismic network, and then we obtain a more complete catalog and a more precise seismic phase report. (3) Relocate the earthquakes in the swarm using hypoDD based on phase arrival time we recalibrated, and analyze the characteristics of swarm epicenter migration based on the earthquake relocation result. (4) Detect whether there are repeating earthquakes activity using both waveform cross-correlation standard and whether rupture areas can overlapped. We finally detect 106 missing earthquakes in the swarm, 66 of them have the magnitude greater than ML0.0, include 2 greater than ML1.0. Relocation result shows that the epicenters of earthquakes in the swarm have a strip distribution in NE-SW direction, which indicates the seismogenic structure may be a NE-SW trending fault. The spatial-temporal distribution variation of epicenters in the swarm shows a kind of two stages linear migration characteristics, in which the first stage has appeared with a higher migration velocity as 1.2 km per day, and the velocity of the second step is 0.0024 km per day. According to the three basic models to explain the seismological mechanism of earthquake swarms: cascade model, slow slip model and fluid diffusion model, repeating earthquakes activity is difficult to explain by

  20. Scenario-Based Multi-Objective Optimum Allocation Model for Earthquake Emergency Shelters Using a Modified Particle Swarm Optimization Algorithm: A Case Study in Chaoyang District, Beijing, China.

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    Xiujuan Zhao

    Full Text Available The correct location of earthquake emergency shelters and their allocation to residents can effectively reduce the number of casualties by providing safe havens and efficient evacuation routes during the chaotic period of the unfolding disaster. However, diverse and strict constraints and the discrete feasible domain of the required models make the problem of shelter location and allocation more difficult. A number of models have been developed to solve this problem, but there are still large differences between the models and the actual situation because the characteristics of the evacuees and the construction costs of the shelters have been excessively simplified. We report here the development of a multi-objective model for the allocation of residents to earthquake shelters by considering these factors using the Chaoyang district, Beijing, China as a case study. The two objectives of this model were to minimize the total weighted evacuation time from residential areas to a specified shelter and to minimize the total area of all the shelters. The two constraints were the shelter capacity and the service radius. Three scenarios were considered to estimate the number of people who would need to be evacuated. The particle swarm optimization algorithm was first modified by applying the von Neumann structure in former loops and global structure in later loops, and then used to solve this problem. The results show that increasing the shelter area can result in a large decrease in the total weighted evacuation time from scheme 1 to scheme 9 in scenario A, from scheme 1 to scheme 9 in scenario B, from scheme 1 to scheme 19 in scenario C. If the funding were not a limitation, then the final schemes of each scenario are the best solutions, otherwise the earlier schemes are more reasonable. The modified model proved to be useful for the optimization of shelter allocation, and the result can be used as a scientific reference for planning shelters in the

  1. Fractal analysis of the ULF geomagnetic data obtained at Izu Peninsula, Japan in relation to the nearby earthquake swarm of June–August 2000

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    K. Gotoh

    2003-01-01

    Full Text Available In our recent papers we applied fractal methods to extract the earthquake precursory signatures from scaling characteristics of the ULF geomagnetic data, obtained in a seismic active region of Guam Island during the large earthquake of 8 August 1993. We found specific dynamics of their fractal characteristics (spectral exponents and fractal dimensions before the earthquake: appearance of the flicker-noise signatures and increase of the time series fractal dimension. Here we analyze ULF geomagnetic data obtained in a seismic active region of Izu Peninsula, Japan during a swarm of the strong nearby earthquakes of June–August 2000 and compare the results obtained in both regions. We apply the same methodology of data processing using the FFT procedure, Higuchi method and Burlaga-Klein approach to calculate the spectral exponents and fractal dimensions of the ULF time series. We found the common features and specific peculiarities in the behavior of fractal characteristics of the ULF time series before Izu and Guam earthquakes. As a common feature, we obtained the same increase of the ULF time series fractal dimension before the earthquakes, and as specific peculiarity – this increase appears to be sharp for Izu earthquake in comparison with gradual increase of the ULF time series fractal dimension for Guam earthquake. The results obtained in both regions are discussed on the basis of the SOC (self-organized criticality concept taking into account the differences in the depths of the earthquake focuses. On the basis of the peculiarities revealed, we advance methodology for extraction of the earthquake precursory signatures. As an adjacent step, we suggest the combined analysis of the ULF time series in the parametric space polarization ratio – fractal dimension. We reason also upon the advantage of the multifractal approach with respect to the mono-fractal analysis for study of the earthquake preparation dynamics.

  2. Mantle-Crust Volcanics and Geodynamics of the Yellowstone Hotspot from Seismic and GPS Imaging and Earthquake Swarm Magmatic Interaction

    Science.gov (United States)

    Smith, R. B.; Farrell, J.; Puskas, C. M.

    2015-12-01

    The Yellowstone hotspot is the product of plume-plate interaction that has produced a large and active silicic volcanic field within the N. American Plate. Our newest research on Yellowstone includes: 1) A recent discovery by seismic imaging that the Yellowstone volcanic system extends as a connected magmatic system from at least 1000 km deep in the mantle with melt ascending upward in a WNW tilted plume to a newly discovered lower-crustal magma body at 20-45 km depth and 4x larger than the shallow crustal reservoir 5-15 km deep. Moreover the shallow 70 km NE-SW crustal magma body unexpectedly extends 15 km NE well beyond Yellowstone's volcanic field a distance that N. American Plate would advance in 640,000 years, i.e., the time of the last Yellowstone super eruption and hence reflecting plate motion over the Yellowstone mantle plume; 2) Yellowstone's giant mantle-crust connected magma system represents ~48,000 km3 with ~1800 km3 of melt that fuels Yellowstone's extraordinarily high heat flux of up to ~ 3 Watts/meter2 that in turn drives Yellowstone's world renown hydrothermal system; and 3) How migration of magma vertically into and laterally out of the crustal magma reservoir, measured by GPS and earthquake correlation, reveals the mechanics of Yellowstone's "natural volcano pressure relief valve" that retards volcanic eruptions for thousands of years, but that occasionally breach the brittle-ductile transition in volcanic eruptions. We will also discuss the most recent and largest earthquake in Yellowstone in over 30 years, a magnitude 4.8 event, on March 30, 2014 near Norris Geyser Basin. This earthquake was part of a larger sequence of swarm activity in the Norris area that began in September 2013 and continued into June 2014. GPS derived deformation at Norris revealed unusually high uplift rates at ~15 cm/yr. attaining 60 mm of uplift at the time of the MW4.8 event and that dramatically reversed to subsidence at rates of ~17 cm/yr. Notably, however the much

  3. Aseismic deformation associated with an earthquake swarm in the northern Apennines (Italy)

    Science.gov (United States)

    Gualandi, A.; Nichele, C.; Serpelloni, E.; Chiaraluce, L.; Anderlini, L.; Latorre, D.; Belardinelli, M. E.; Avouac, J.-P.

    2017-08-01

    Analyzing the displacement time series from continuous GPS (cGPS) with an Independent Component Analysis, we detect a transient deformation signal that correlates both in space and time with a seismic swarm activity (maximum Mw=3.69 ± 0.09) occurred in the hanging wall of the Altotiberina normal fault (Northern Apennines, Italy) in 2013-2014. The geodetic transient lasted ˜6 months and produced a NW-SE trending extension of ˜5.3 mm, consistent with the regional tectonic regime. The seismicity and the geodetic signal are consistent with slip on two splay faults in the Altotiberina fault (ATF) hanging wall. Comparing the seismic moment associated with the geodetic transient and the seismic events, we observe that seismicity accounts for only a fraction of the measured geodetic deformation. The combined seismic and aseismic slip decreased the Coulomb stress on the locked shallow portion of the ATF, while the transition region to the creeping section has been loaded.

  4. Geothermal Conceptual Model in Earthquake Swarm Area: Constrains from Physical Properties of Supercritical Fluids and Dissipative Theory

    Science.gov (United States)

    Wang, S. C.; Lee, C. S.

    2016-12-01

    In recent five years, geothermal energy became one of the most prosperous renewable energy in the world, but produces only 0.5% of the global electricity. Why this great potential of green energy cannot replace the fuel and nuclear energy? The necessity of complicated exploration procedures and precious experts in geothermal field is similar to that of the oil and gas industry. The Yilan Plain (NE Taiwan) is one of the hot area for geothermal development and research in the second phase of National Energy Program (NEP-II). The geological and geophysical studies of the area indicate that the Yilan Plain is an extension of the Okinawa Trough back arc rifting which provide the geothermal resource. Based on the new constrains from properties of supercritical fluids and dissipative structure theory, the geophysical evidence give confident clues on how the geothermal system evolved at depth. The geothermal conceptual model in NEP-II indicates that the volcanic intrusion under the complicate fault system is possibly beneath the Yilan Plain. However, the bottom temperature of first deep drilling and geochemical evidence in NEP-II imply no volcanic intrusion. In contrast, our results show that seismic activities in geothermal field observed self-organization, and are consistent with the brittle-ductile / brittle-plastic transition, which indicates that supercritical fluids triggered earthquake swarms. The geothermal gradient and geochemical anomalies in Yilan Plain indicate an open system far from equilibrium. Mantle and crust exchange energy and materials through supercritical fluids to generate a dissipative structure in geothermal fields and promote water-rock interactions and fractures. Our initial studies have suggested a dissipative structure of geothermal system that could be identified by geochemical and geophysical data. The key factor is the tectonic setting that triggered supercritical fluids upwelling from deep (possibly from the mantle or the upper crust). Our

  5. Aseismic transient during the 2010-2014 seismic swarm: evidence for longer recurrence of M ≥ 6.5 earthquakes in the Pollino gap (Southern Italy)?

    Science.gov (United States)

    Cheloni, Daniele; D'Agostino, Nicola; Selvaggi, Giulio; Avallone, Antonio; Fornaro, Gianfranco; Giuliani, Roberta; Reale, Diego; Sansosti, Eugenio; Tizzani, Pietro

    2017-04-12

    In actively deforming regions, crustal deformation is accommodated by earthquakes and through a variety of transient aseismic phenomena. Here, we study the 2010-2014 Pollino (Southern Italy) swarm sequence (main shock M W 5.1) located within the Pollino seismic gap, by analysing the surface deformation derived from Global Positioning System and Synthetic Aperture Radar data. Inversions of geodetic time series show that a transient slip, with the same mechanism of the main shock, started about 3-4 months before the main shock and lasted almost one year, evolving through time with acceleration phases that correlate with the rate of seismicity. The moment released by the transient slip is equivalent to M W 5.5, significantly larger than the seismic moment release revealing therefore that a significant fraction of the overall deformation is released aseismically. Our findings suggest that crustal deformation in the Pollino gap is accommodated by infrequent "large" earthquakes (M W  ≥ 6.5) and by aseismic episodes releasing a significant fraction of the accrued strain. Lower strain rates, relative to the adjacent Southern Apennines, and a mixed seismic/aseismic strain release are in favour of a longer recurrence for large magnitude earthquakes in the Pollino gap.

  6. Multi precursors analysis associated with the powerful Ecuador (MW = 7.8) earthquake of 16 April 2016 using Swarm satellites data in conjunction with other multi-platform satellite and ground data

    Science.gov (United States)

    Akhoondzadeh, Mehdi; De Santis, Angelo; Marchetti, Dedalo; Piscini, Alessandro; Cianchini, Gianfranco

    2018-01-01

    After DEMETER satellite mission (2004-2010), the launch of the Swarm satellites (Alpha (A), Bravo (B) and Charlie (C)) has created a new opportunity in the study of earthquake ionospheric precursors. Nowadays, there is no doubt that multi precursors analysis is a necessary phase to better understand the LAIC (Lithosphere Atmosphere Ionosphere Coupling) mechanism before large earthquakes. In this study, using absolute scalar magnetometer, vector field magnetometer and electric field instrument on board Swarm satellites, GPS (Global Positioning System) measurements, MODIS-Aqua satellite and ECMWF (European Centre for Medium-Range Weather Forecasts) data, the variations of the electron density and temperature, magnetic field, TEC (Total Electron Content), LST (Land Surface Temperature), AOD (Aerosol Optical Depth) and SKT (SKin Temperature) have been surveyed to find the potential seismic anomalies around the strong Ecuador (Mw = 7.8) earthquake of 16 April 2016. The four solar and geomagnetic indices: F10.7, Dst, Kp and ap were investigated to distinguish whether the preliminary detected anomalies might be associated with the solar-geomagnetic activities instead of the seismo-ionospheric anomalies. The Swarm satellites (A, B and C) data analysis indicate the anomalies in time series of electron density variations on 7, 11 and 12 days before the event; the unusual variations in time series of electron temperature on 8 days preceding the earthquake; the analysis of the magnetic field scalar and vectors data show the considerable anomalies 52, 48, 23, 16, 11, 9 and 7 days before the main shock. A striking anomaly is detected in TEC variations on 1 day before earthquake at 9:00 UTC. The analysis of MODIS-Aqua night-time images shows that LST increase unusually on 11 days prior to main shock. In addition, the AOD variations obtained from MODIS measurements reach the maximum value on 10 days before the earthquake. The SKT around epicentral region presents anomalous higher

  7. Drone Swarms

    Science.gov (United States)

    2017-05-25

    motion,” provides a method that combines situational awareness, elusiveness, mass, speed, mobility, and surprise to physically and cognitively overwhelm...Napoleon’s Great Army at Ulm, provide operational shock and cognitive dissonance to opposing military systems and personnel. In Swarming and the...Scythians, Alexander used similar anti-swarm methods that bottlenose dolphins use to catch swarming fish. In order to catch fish utilizing swarms

  8. SAFETY OF PASSIVE HOUSES SUBJECTED TO EARTHQUAKE, FINAL REPORT

    Directory of Open Access Journals (Sweden)

    Vojko Kilar

    2013-12-01

    Full Text Available he topic researched within the applied project. "Safety of passive houses subjected to earthquake" stemmed from two otherwise quite unrelated fields, i.e. seismic resistance and energy efficiency that in European countries do not frequently appear together. Just in Slovenia these two fields join each other, so identifying the problem and establishment of research right in Slovenia represents uniqueness and specificity. The majority of Slovenia is situated in area of moderate seismic risk. In order to ensure adequate mechanical resistance and stability of structures constructed in such area, the consideration of seismic effects is required by law. In Slovenia the number of passive houses and energy efficient buildings increases rapidly. However, for the time being the structural solutions that have been developed and broadly applied mainly in the areas with low seismicity (where the structural control to vertical static loads is sufficient are used. In earthquake-prone areas also adequate resistance to dynamic seismic effects have to be assured.

  9. Earthquakes

    Science.gov (United States)

    ... earthquake occurs in a populated area, it may cause property damage, injuries, and even deaths. If you live in a coastal area, there is the possibility of a tsunami. Damage from earthquakes can also lead to floods or fires. Although there are no guarantees of ...

  10. Earthquakes

    Science.gov (United States)

    Shedlock, Kaye M.; Pakiser, Louis Charles

    1998-01-01

    One of the most frightening and destructive phenomena of nature is a severe earthquake and its terrible aftereffects. An earthquake is a sudden movement of the Earth, caused by the abrupt release of strain that has accumulated over a long time. For hundreds of millions of years, the forces of plate tectonics have shaped the Earth as the huge plates that form the Earth's surface slowly move over, under, and past each other. Sometimes the movement is gradual. At other times, the plates are locked together, unable to release the accumulating energy. When the accumulated energy grows strong enough, the plates break free. If the earthquake occurs in a populated area, it may cause many deaths and injuries and extensive property damage. Today we are challenging the assumption that earthquakes must present an uncontrollable and unpredictable hazard to life and property. Scientists have begun to estimate the locations and likelihoods of future damaging earthquakes. Sites of greatest hazard are being identified, and definite progress is being made in designing structures that will withstand the effects of earthquakes.

  11. Analysis of Seismic Swarms at the Oceanic Crust South of the Islas Marias, MEXICO

    Science.gov (United States)

    Tinoco Villa, M. E.; Nunez-Cornu, F. J.; Escudero, C. R.

    2013-12-01

    We analyzed data recorded at the Red Sismica Acelerometrica de Jalisco (RESAJ) from November 2010 to August 2013, focus on the seismicity occurred within an area south of the Islas Marias (-105.7, 20.3; -107, 21.8) west of Bahia de Banderas. We observed seismic swarms and low magnitude. Within our data set we identified four seismic swarms episodes. September 14 to 15, 2010 that starts with an earthquake of M = 5.6 at 23:31 followed by approximately 27 events, also has six earthquakes whose magnitudes are between M = 4.0 and M = 5.6; November 11 to December 5, 2011 which contains more than 25 events; October 12 to November 17, 2012 with more than 35 events with an earthquake M = 4.7 occurred on October 29; and finally the swarm occurred between January 20 and February 14, 2013 with over 120 events and one of M = 4.7 occurred on January 22. The last seismic swarm also present activity along two additional areas, one toward the west and the other toward the east of active area previously identified. This seismic activity is associated with the northern edge of the Barra de Navidad Trench whose geometry is unknown. Tectonic structures associated with this seismicity can be tsunamigenic and could represent a danger to nearby populations.

  12. Using Internet reports for early estimates of the final death toll of earthquake-generated tsunami: the March 11, 2011, Tohoku, Japan, earthquake

    Directory of Open Access Journals (Sweden)

    Zhongliang Wu

    2011-06-01

    Full Text Available A retrospective case study was conducted for the March 11, 2011, earthquake that occurred off the east Pacific coast of Tohoku, Japan, with reference to the Sumatra-Andaman earthquake and Indian Ocean tsunami on December 26, 2004. The regularities of the temporal variations of the number of deaths reported through the Internet is used to make an early stage quick-and-rough estimate to assist in the emergency decision making, and to continue the revision of the estimate as new data comes in. The quick-and-rough estimate of the final fatalities that was obtained on the second day after the earthquake is shown to agree with the final reported fatalities to within an order of magnitude. This also has an added advantage over other estimation models, in that the estimates can be updated with new data as they become available.

  13. Analog Circuit Fault Diagnosis Approach Based on Improved Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Ming-Fang WANG

    2014-07-01

    Full Text Available The basic thought of particle swarm optimization is introduced firstly, then particle swarm optimization algorithm model is established. The application of the improved particle swarm optimization algorithm to power supply system fault diagnosis is analyzed in accordance with problem of the algorithm, and migration strategy is added to particle swarm optimization algorithm. Finally the parameters of the wide area damping controller are adjusted by the improved particle swarm optimization algorithm.

  14. First U.S.-Japan workshop on advanced research on earthquake engineering for dams. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Hynes, M.E.; Hall, R.; Baker, J.C.; Yamaguchi, Y.

    1998-07-01

    The First US-Japan Workshop on Advanced Research on Earthquake Engineering for Dams was held under the sponsorship of the US Army Engineer Waterways Experiment Station and the Public Works Research Institute of Japan (PWRI) under the auspices of Task Committee D, Earthquake Engineering for Dams, of the UJNR Panel on Wind and Seismic Effects, in Vicksburg, Mississippi, 12-14 November 1996. The workshop provided a valuable forum to exchange technical information on earthquake engineering for dams in both countries. The workshop was attended by 11 Japanese participants, 26 US participants, and 1 visitor from the United Kingdom. Four agencies and two universities were represented in the Japanese delegation. The US participants were drawn from the US Army Corps of Engineers and the US Bureau of Reclamation.

  15. Particle Swarm Optimization

    Science.gov (United States)

    Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

    2002-01-01

    The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

  16. Heterogeneous architecture to process swarm optimization algorithms

    Directory of Open Access Journals (Sweden)

    Maria A. Dávila-Guzmán

    2014-01-01

    Full Text Available Since few years ago, the parallel processing has been embedded in personal computers by including co-processing units as the graphics processing units resulting in a heterogeneous platform. This paper presents the implementation of swarm algorithms on this platform to solve several functions from optimization problems, where they highlight their inherent parallel processing and distributed control features. In the swarm algorithms, each individual and dimension problem are parallelized by the granularity of the processing system which also offer low communication latency between individuals through the embedded processing. To evaluate the potential of swarm algorithms on graphics processing units we have implemented two of them: the particle swarm optimization algorithm and the bacterial foraging optimization algorithm. The algorithms’ performance is measured using the acceleration where they are contrasted between a typical sequential processing platform and the NVIDIA GeForce GTX480 heterogeneous platform; the results show that the particle swarm algorithm obtained up to 36.82x and the bacterial foraging swarm algorithm obtained up to 9.26x. Finally, the effect to increase the size of the population is evaluated where we show both the dispersion and the quality of the solutions are decreased despite of high acceleration performance since the initial distribution of the individuals can converge to local optimal solution.

  17. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

  18. Swarming UAS II

    Science.gov (United States)

    2010-05-05

    employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map, allowing pheromone-like...matter of design, DSE-R-0808 employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map

  19. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    The introgression of modern humans (Homo sapiens) with Neanderthals 40,000 YBP after a half-million years of separation, may have led to the best example of a hybrid swarm on earth. Modern trade and transportation in support of the human hybrids has continued to introduce additional species, genotyp...

  20. MAGNAS - Magnetic Nanoprobe SWARM

    DEFF Research Database (Denmark)

    Lubberstedt, H.; Koebel, D.; Hansen, Flemming

    2005-01-01

    This paper presents the Magnetic Nano-Probe Swarm mission utilising a constellation of several swarms of nano-satellites in order to acquire simultaneous measurements of the geomagnetic field resolving the local field gradients. The space segment comprises of up to 4 S/C swarms each consisting...... of up to 6 nano-satellites (Nano-Probes) and 1 mother spacecraft (MSC) to be launched with a single launcher in polar low Earth orbits. The Nano-Probes. equipped with magnetometer payloads operate in the vicinity of the MSCs. The MSCs will eject the NPs after acquisition of the initial orbits. provide...

  1. Adaptive cockroach swarm algorithm

    Science.gov (United States)

    Obagbuwa, Ibidun C.; Abidoye, Ademola P.

    2017-07-01

    An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

  2. A Tale of Two Seismic Swarms: Implications for different forcing mechanisms (Invited)

    Science.gov (United States)

    Thelen, W. A.; Gomberg, J. S.; Bodin, P.; Hartog, R.; Wright, A.; Rohay, A.

    2009-12-01

    Within the compressional tectonic regime of the Columbia Basin, swarms are the dominant source of seismicity. Not all swarms, however, are created equal. Two recent swarms, the 2007-2008 swarm near Maupin, Oregon and the 2009 Wooded Island earthquake sequence near Richland, Washington, displayed very different behavior despite being within the same tectonic regime. The Maupin earthquake swarm lasted 20 months with strike-slip earthquakes with magnitudes as large as M3.8. The swarm was 18 km deep. Nearly all of the earthquakes within the Maupin swarm were highly similar with maximum p-wave lags of about 0.05 seconds. This seismic evidence therefore suggests a single, repeatable, and very energetic source with dimensions of less than 750 m at mid-crustal levels. Swarms, apparently collocated, also occurred in 1987 and 1976. However the waveforms from these swarms are not similar to the 2007-2008 sequence, suggesting that the source geometry or orientation of the source has changed from 1976 to 1987 and 2007. In contrast, the 2009 Wooded Island earthquake sequence is currently (as of September 3) only 8 months in duration, but has already had nearly five times the number earthquakes as the Maupin swarm, with a maximum magnitude of 3. The total energy released in the Wooded Island earthquake sequence was less than in the Maupin earthquake sequence. The earthquakes in the Wooded Island sequence were shallow, with focal depths of less than 2 km, which made focal mechanisms unreliable. However, the earthquakes were associated with a deformation anomaly detected from InSAR. Based on the correlations between waveforms, earthquakes that comprise this swarm can be classified into many different families, suggesting slip along a network of distributed shallow faults and/or a heterogeneous stress field. Precise relocations show a dipping structure, consistent with a fault geometry that matches well with source models of the InSAR deformation anomaly. Swarms have been attributed

  3. The Swarm Magnetometry Package

    DEFF Research Database (Denmark)

    Merayo, José M.G.; Jørgensen, John Leif; Friis-Christensen, Eigil

    2008-01-01

    The Swarm mission under the ESA's Living Planet Programme is planned for launch in 2010 and consists of a constellation of three satellites at LEO. The prime objective of Swarm is to measure the geomagnetic field with unprecedented accuracy in space and time. The magnetometry package consists of ...... of an extremely accurate and stable vector magnetometer, which is co-mounted in an optical bench together with a start tracker system to ensure mechanical stability of the measurements....

  4. Particle Swarm Optimization Toolbox

    Science.gov (United States)

    Grant, Michael J.

    2010-01-01

    The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry

  5. Xarxa social (Swarm)

    OpenAIRE

    Capdevila Piro, Antonio

    2012-01-01

    Aquesta memòria presenta les línies generals que s'han seguit per tal d'implementar una aplicació anomenada SWARM. En aquest document es recullen les bases del nostre projecte utilitzant el llenguatge de programació C# i fent servir altres eines i frameworks per les diferents capes de què consta el projecte, com poden ser Silverlight o WCF. Esta memoria presenta las líneas generales que se han seguido para implementar una aplicación llamada SWARM. En este documento se recogen las bases de ...

  6. Social interactions in myxobacterial swarming.

    Directory of Open Access Journals (Sweden)

    Yilin Wu

    2007-12-01

    Full Text Available Swarming, a collective motion of many thousands of cells, produces colonies that rapidly spread over surfaces. In this paper, we introduce a cell-based model to study how interactions between neighboring cells facilitate swarming. We chose to study Myxococcus xanthus, a species of myxobacteria, because it swarms rapidly and has well-defined cell-cell interactions mediated by type IV pili and by slime trails. The aim of this paper is to test whether the cell contact interactions, which are inherent in pili-based S motility and slime-based A motility, are sufficient to explain the observed expansion of wild-type swarms. The simulations yield a constant rate of swarm expansion, which has been observed experimentally. Also, the model is able to quantify the contributions of S motility and A motility to swarming. Some pathogenic bacteria spread over infected tissue by swarming. The model described here may shed some light on their colonization process.

  7. Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

    Science.gov (United States)

    Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui

    2016-10-01

    The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.

  8. Particle Swarms in Fractures: Open Versus Partially Closed Systems

    Science.gov (United States)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2014-12-01

    In the field, fractures may be isolated or connected to fluid reservoirs anywhere along the perimeter of a fracture. These boundaries affect fluid circulation, flow paths and communication with external reservoirs. The transport of drop like collections of colloidal-sized particles (particle swarms) in open and partially closed systems was studied. A uniform aperture synthetic fracture was constructed using two blocks (100 x 100 x 50 mm) of transparent acrylic placed parallel to each other. The fracture was fully submerged a tank filled with 100cSt silicone oil. Fracture apertures were varied from 5-80 mm. Partially closed systems were created by sealing the sides of the fracture with plastic film. The four boundary conditions study were: (Case 1) open, (Case 2) closed on the sides, (Case 3) closed on the bottom, and (Case 4) closed on both the sides and bottom of the fracture. A 15 μL dilute suspension of soda-lime glass particles in oil (2% by mass) were released into the fracture. Particle swarms were illuminated using a green (525 nm) LED array and imaged with a CCD camera. The presence of the additional boundaries modified the speed of the particle swarms (see figure). In Case 1, enhanced swarm transport was observed for a range of apertures, traveling faster than either very small or very large apertures. In Case 2, swarm velocities were enhanced over a larger range of fracture apertures than in any of the other cases. Case 3 shifted the enhanced transport regime to lower apertures and also reduced swarm speed when compared to Case 2. Finally, Case 4 eliminated the enhanced transport regime entirely. Communication between the fluid in the fracture and an external fluid reservoir resulted in enhanced swarm transport in Cases 1-3. The non-rigid nature of a swarm enables drag from the fracture walls to modify the swarm geometry. The particles composing a swarm reorganize in response to the fracture, elongating the swarm and maintaining its density. Unlike a

  9. Possible structures of the old Urcunina Caldera, revealed by high precision relocation of VT earthquakes at Galeras volcano

    Science.gov (United States)

    Lizarazo C, M. J.; Alvarado, H.; Sanchez, J. J.

    2013-12-01

    Volcano-Tectonic earthquakes at Galeras Volcano were relocated using the waveform catalog waveform and preliminary phase arrival data compiled by the monitoring network at Observatorio Volcanológico y Sismológico de Pasto. Several routines were developed in MATLAB, mainly to prepare waveforms, calculate differential travel times, and identifying seismic families; and the HypoDD program was implemented, which allowed performing the relocations. The procedure resulted in the detection of 10 swarm-type families and 4 spatial-type families of earthquakes, which reveal a fault of 1.6 km bounding the Urcunina Caldera, and a ring fault of 1.8 km in diameter, adjacent to the crater. Reductions in the range 56.84% - 87.48% were achieved in the hypocentral parameters uncertainties as compared to uncertainties in traditional locations, to finally obtain an alternative image of the Volcano-Tectonic earthquakes distribution Galeras Volcano VG with a significantly lower uncertainty.

  10. Measuring seismicity diversity and anomalies using point process models: case studies before and after the 2016 Kumamoto earthquakes in Kyushu, Japan

    Science.gov (United States)

    Kumazawa, Takao; Ogata, Yosihiko; Tsuruoka, Hiroshi

    2017-12-01

    This paper reviews seismic activity in and around the Kumamoto region before and after the April 16, 2016, Kumamoto earthquake of M7.3 using statistical models such as stationary, two-stage, and non-stationary epidemic-type aftershock sequence (ETAS) models to examine seismicity anomalies. Our findings are summarized as follows. First, most of the earthquake clusters before April 2016 are explained by the stationary ETAS model, except for a few clusters of swarm activity, one of which was remotely induced by the 2011 Tohoku-Oki earthquake (M9). The non-stationary ETAS model describes changes in the rate of background seismicity of swarm activity. Second, we revealed seismic quiescence relative to the stationary ETAS model in the foreshock sequence from the M6.5 earthquake on April 14, 2016, and further in the aftershock activity of the 2000 M5.0 earthquake that occurred in the shallower extension of the M6.5 foreshock zone. Thirdly, the main-fault and two off-fault aftershock clusters of the M7.3 mainshock show different features, caused by static triggering effects of the mainshock and/or effects induced by fault weakening. Finally, the b-value increased stepwise over time during the entire period of foreshocks and aftershocks, the reason of which is explained.

  11. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Directory of Open Access Journals (Sweden)

    Long Qin

    2013-01-01

    Full Text Available Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  12. Swarm robotics and minimalism

    Science.gov (United States)

    Sharkey, Amanda J. C.

    2007-09-01

    Swarm Robotics (SR) is closely related to Swarm Intelligence, and both were initially inspired by studies of social insects. Their guiding principles are based on their biological inspiration and take the form of an emphasis on decentralized local control and communication. Earlier studies went a step further in emphasizing the use of simple reactive robots that only communicate indirectly through the environment. More recently SR studies have moved beyond these constraints to explore the use of non-reactive robots that communicate directly, and that can learn and represent their environment. There is no clear agreement in the literature about how far such extensions of the original principles could go. Should there be any limitations on the individual abilities of the robots used in SR studies? Should knowledge of the capabilities of social insects lead to constraints on the capabilities of individual robots in SR studies? There is a lack of explicit discussion of such questions, and researchers have adopted a variety of constraints for a variety of reasons. A simple taxonomy of swarm robotics is presented here with the aim of addressing and clarifying these questions. The taxonomy distinguishes subareas of SR based on the emphases and justifications for minimalism and individual simplicity.

  13. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    Stohlgren, Thomas J.; Szalanski, Allen L; Gaskin, John F.; Young, Nicholas E.; West, Amanda; Jarnevich, Catherine S.; Tripodi, Amber

    2014-01-01

    Science has shown that the introgression or hybridization of modern humans (Homo sapiens) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis, was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica, showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

  14. Components of Swarm Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    David Bruemmer; Donald Dudenhoeffer; Matthew Anderson; Mark McKay

    2004-03-01

    This paper discusses the successes and failures over the past three years as efforts at the Idaho National Engineering and Environmental Laboratory (INEEL) have developed and evaluated robot behaviors that promote the emergence of swarm intelligence. Using a team of 12 small robots with the ability to respond to light and sound, the INEEL has investigated the fundamental advantages of swarm behavior as well as the limitations of this approach. The paper discusses the ways in which biology has inspired this work and the ways in which adherence to the biological model has proven to be both a benefit and hindrance to developing a fieldable system. The paper outlines how a hierarchical command and control structure can be imposed in order to permit human control at a level of group abstraction and discusses experimental results that show how group performance scales as different numbers of robots are utilized. Lastly, the paper outlines the applications for which the resulting capabilities have been applied and demonstrated.

  15. Foraging behavior analysis of swarm robotics system

    Directory of Open Access Journals (Sweden)

    Sakthivelmurugan E.

    2018-01-01

    Full Text Available Swarm robotics is a number of small robots that are synchronically works together to accomplish a given task. Swarm robotics faces many problems in performing a given task. The problems are pattern formation, aggregation, Chain formation, self-assembly, coordinated movement, hole avoidance, foraging and self-deployment. Foraging is most essential part in swarm robotics. Foraging is the task to discover the item and get back into the shell. The researchers conducted foraging experiments with random-movement of robots and they have end up with unique solutions. Most of the researchers have conducted experiments using the circular arena. The shell is placed at the centre of the arena and environment boundary is well known. In this study, an attempt is made to different strategic movements like straight line approach, parallel line approach, divider approach, expanding square approach, and parallel sweep approach. All these approaches are to be simulated by using player/stage open-source simulation software based on C and C++ programming language in Linux operating system. Finally statistical comparison will be done with task completion time of all these strategies using ANOVA to identify the significant searching strategy.

  16. Seismic features of the June 1999 tectonic swarm in the Stromboli volcano region, Italy

    Science.gov (United States)

    Falsaperla, S.; Alparone, S.; Spampinato, S.

    2003-07-01

    Crustal tectonic seismicity in the Southern Tyrrhenian Sea is characterized by the high occurrence rates of earthquakes to the west of the alignment of Salina, Lipari and Vulcano islands in the Aeolian archipelago. Only a few earthquakes affect the crustal region east of these islands, whereas intermediate and deep seismicity plays a relevant role. Based on this evidence, two aspects of the seismic swarm recorded at the Aeolian Island Seismic Network between June 6 and 17, 1999 looked anomalous. The first aspect concerned the number of earthquakes (78) that affected the Stromboli submarine edifice in a short time interval. Secondly, despite the low maximum magnitude Md 3.2 reached, the cumulative strain release was conspicuous in comparison with previous swarms in this region. We localized the swarm about 6 km northeast of Stromboli, at a depth between 8 and 12 km. The source region was identified using standard methods of hypocentral location, as well as azimuth analysis. It is worth noting that the volcanic activity at Stromboli did not change significantly during the swarm nor throughout the following months. Therefore, the seismic swarm had no link with volcanic activity observed at the surface. Most of the earthquakes shared similar waveform and frequency content, and can be divided into families. We identified some earthquakes - with magnitude up to Md 3 - having relatively low frequency content at different seismic stations. This anomalous feature leads us to hypothesize the presence of fluid circulation and/or propagation of seismic waves in a ductile medium. Our hypothesis is in agreement with studies on marine geology, which highlight various forms of submarine volcanism in the southern basin of the Tyrrhenian Sea.

  17. The 2012 Brawley swarm triggered by injection-induced aseismic slip

    Science.gov (United States)

    Wei, Shengji; Avouac, Jean-Philippe; Hudnut, Kenneth W.; Donnellan, Andrea; Parker, Jay W.; Graves, Robert W.; Helmberger, Don; Fielding, Eric; Liu, Zhen; Cappa, Frederic; Eneva, Mariana

    2015-07-01

    It has long been known that fluid injection or withdrawal can induce earthquakes, but the underlying mechanisms remain elusive. For example, the 2012 Brawley swarm, which produced two strike-slip shocks with magnitudes larger than 5.3 and surface ruptures in the close vicinity of a geothermal field, started with earthquakes about 5 km deeper than the injection depth (∼1.5 km). This makes the causality between the injection and seismicity unclear. Here, we jointly analyze broadband and strong motion waveforms, UAVSAR, leveling measurements and field observations to reveal the detailed seismic and aseismic faulting behaviors associated with the 2012 Brawley swarm. In particular, path calibration established from smaller events in the swarm allows waveform inversion to be conducted up to 3 Hz to resolve finite rupture process of the Mw 4.7 normal event. Our results show that the 2012 earthquake sequence was preceded by aseismic slip on a shallow normal fault beneath the geothermal field. Aseismic slip initiated in 2010 when injection rate rapidly increased and triggered the following earthquakes subsequently, including unusually shallow and relatively high frequency seismic excitations on the normal fault. In this example, seismicity is induced indirectly by fluid injection, a result of mediation by aseismic creep, rather than directly by a pore pressure increase at the location of the earthquakes.

  18. Earthquakes in British Columbia

    National Research Council Canada - National Science Library

    1991-01-01

    This pamphlet provides information about the causes of earthquakes, where earthquakes occur, British Columbia plate techtonics, earthquake patterns, earthquake intensity, geology and earthquake impact...

  19. USGS GNSS Applications to Earthquake Disaster Response and Hazard Mitigation

    Science.gov (United States)

    Hudnut, K. W.; Murray, J. R.; Minson, S. E.

    2015-12-01

    Rapid characterization of earthquake rupture is important during a disaster because it establishes which fault ruptured and the extent and amount of fault slip. These key parameters, in turn, can augment in situ seismic sensors for identifying disruption to lifelines as well as localized damage along the fault break. Differential GNSS station positioning, along with imagery differencing, are important methods for augmenting seismic sensors. During response to recent earthquakes (1989 Loma Prieta, 1992 Landers, 1994 Northridge, 1999 Hector Mine, 2010 El Mayor - Cucapah, 2012 Brawley Swarm and 2014 South Napa earthquakes), GNSS co-seismic and post-seismic observations proved to be essential for rapid earthquake source characterization. Often, we find that GNSS results indicate key aspects of the earthquake source that would not have been known in the absence of GNSS data. Seismic, geologic, and imagery data alone, without GNSS, would miss important details of the earthquake source. That is, GNSS results provide important additional insight into the earthquake source properties, which in turn help understand the relationship between shaking and damage patterns. GNSS also adds to understanding of the distribution of slip along strike and with depth on a fault, which can help determine possible lifeline damage due to fault offset, as well as the vertical deformation and tilt that are vitally important for gravitationally driven water systems. The GNSS processing work flow that took more than one week 25 years ago now takes less than one second. Formerly, portable receivers needed to be set up at a site, operated for many hours, then data retrieved, processed and modeled by a series of manual steps. The establishment of continuously telemetered, continuously operating high-rate GNSS stations and the robust automation of all aspects of data retrieval and processing, has led to sub-second overall system latency. Within the past few years, the final challenges of

  20. Swarming behavior in plant roots.

    Directory of Open Access Journals (Sweden)

    Marzena Ciszak

    Full Text Available Interactions between individuals that are guided by simple rules can generate swarming behavior. Swarming behavior has been observed in many groups of organisms, including humans, and recent research has revealed that plants also demonstrate social behavior based on mutual interaction with other individuals. However, this behavior has not previously been analyzed in the context of swarming. Here, we show that roots can be influenced by their neighbors to induce a tendency to align the directions of their growth. In the apparently noisy patterns formed by growing roots, episodic alignments are observed as the roots grow close to each other. These events are incompatible with the statistics of purely random growth. We present experimental results and a theoretical model that describes the growth of maize roots in terms of swarming.

  1. Toward more complete magnetic gradiometry with the Swarm mission

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros

    2016-01-01

    similar signal content as the theoretical radial gradient ΓΓ(0)={[∇∇B]rr}. These results demonstrate the ability of multi-satellite missions such as Swarm, which cannot directly measure the radial gradient, to retrieve similar signal content by means of the horizontal gradients. Finally, lithospheric...

  2. Seismic Swarms at Paricutin Volcano Area. Magmatic Intrusion or Tectonic Seismicity?

    Science.gov (United States)

    Pinzon, J. I.; Nunez-Cornu, F. J.; Escudero, C. R.; Rowe, C. A.

    2014-12-01

    We relocate a seismic swarm with more than 700 earthquakes that took place between May and June 2006 in the Paricutin volcano area, Mexico inside of the Michoacan monogenetic volcanic field. This seismic swarm was recorded by the project "Mapping the Riviera Subduction Zone" (MARS), a temporary seismic network that was installed in the states of Jalisco, Colima and Michoacán between January 2006 and June 2007. Previously seismic swarms in the area were reported in the years of 1997, 1999 and 2000. For one that took place in the year of 1997 the Servicio Sismologico Nacional deployed a local network in the area, they conclude that the source of the seismicity was tectonic with depths between 18 and 12 km. The episodes of 1999 and 2000 were reported as similar to the 1997 swarm. A previous analysis of the 2006 swarm concludes that the depth of seismicity migrates from 9 to 5 km and was originated by a magmatic intrusion. We did a relocation of this swarm reading all the events and using Hypo71 and the P-wave velocity model used by the Jalisco Seismic and Acelerometric Network; a waveform analysis using cross-correlation method was also carried out. We obtained 15 earthquakes families with a correlation factor equal or greater than 0.79 and composed focal mechanism for each family. These families present a migration in depth beginning at 16 km and ended at 9 km. Our results agrees with a magmatic intrusion, but not so shallow as the previous study of the 2006 swarm.

  3. Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

    Directory of Open Access Journals (Sweden)

    Paul Jean Etienne Jeszensky

    2005-02-01

    Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

  4. Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2017-07-01

    Full Text Available The robots science has been developed over the past few years, where robots have become used to accomplish difficult, repetitive or accurate tasks, which are very hard for humans to carry out. In this paper, we propose an algorithm to control the motion of a swarm of robots and make them able to avoid obstacles. The proposed solution is based on forming the robots in circular fashion. A group set of robots consists of multiple groups of robots, each group of robots consists of robots forming a circular shape and each group set is a circular form of robots. The proposed algorithm is concerned with first locating the randomly generated robots in groups and secondly with the swarm robot motion and finally with the swarm obstacle avoidance and swarm reorganization after crossing the obstacle. The proposed algorithm has been simulated with five different obstacles with various numbers of randomly generated robots. The results show that the swarm in the circular form can deal with the obstacles very effectively by passing the obstacles smoothly. The proposed algorithm has been compared with flocking algorithm and it is shown that the circular formation algorithm does not need extensive computation after obstacle avoidance whereas the flocking algorithm needs extensive computation. In addition, the circular formation algorithm maintains every robot in its group after avoiding the obstacles whereas with flocking algorithm does not.

  5. Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem

    Directory of Open Access Journals (Sweden)

    S Sarathambekai

    2017-03-01

    Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.

  6. Multi-objective swarm intelligence theoretical advances and applications

    CERN Document Server

    Jagadev, Alok; Panda, Mrutyunjaya

    2015-01-01

    The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.       

  7. Defeating Earthquakes

    Science.gov (United States)

    Stein, R. S.

    2012-12-01

    our actions. Using these global datasets will help to make the model as uniform as possible. The model must be built by scientists in the affected countries with GEM's support, augmented by their insights and data. The model will launch in 2014; to succeed it must be open, international, independent, and continuously tested. But the mission of GEM is not just the likelihood of ground shaking, but also gaging the economic and social consequences of earthquakes, which greatly amplify the losses. For example, should the municipality of Istanbul retrofit schools, or increase its insurance reserves and recovery capacity? Should a homeowner in a high-risk area move or strengthen her building? This is why GEM is a public-private partnership. GEM's fourteen public sponsors and eight non-governmental organization members are standing for the developing world. To extend GEM into the financial world, we draw upon the expertise of companies. GEM's ten private sponsors have endorsed the acquisition of public knowledge over private gain. In a competitive world, this is a courageous act. GEM is but one link in a chain of preparedness: from earth science and engineering research, through groups like GEM, to mitigation, retrofit or relocate decisions, building codes and insurance, and finally to prepared hospitals, schools, and homes. But it is a link that our community can make strong.

  8. The Maupin, Oregon, Earthquakes Observed With A Portable Broadband Seismic Array

    Science.gov (United States)

    Connolly, J.; Thelen, W.; Hartog, J. R.; Wright, A.; Crosson, B.; Bodin, P.; Vidale, J. E.

    2008-12-01

    We report preliminary analyses from a 5-station portable broadband seismic array deployed around a site of persistent swarm-like earthquakes near the town of Maupin in north central Oregon. Swarm behavior is common amongst crustal earthquakes in Cascadia, particularly east of the Cascades where seismic instrumentation is sparse and seismicity may be relatively poorly characterized. This challenges our understanding of the generative mechanisms of swarms and their roles in the seismotectonics of the Pacific Northwest. The Maupin earthquakes provide a high quality case study for Oregon swarms. From November 2006 to August 2008, 315 earthquakes from M0.8 to M4.2 have been catalogued by the Pacific Northwest Seismic Network, complete down to M1.5, and with a magnitude-occurrence b-value of 0.8. During the 67 days of the temporary deployment, 300 earthquakes were recorded with magnitudes as small as M-0.5, complete down to M0.3, also with a b-value of 0.8. PNSN network catalog locations were determined to be quite accurate for the recent swarm. The additional close-in temporary stations reduced the epicentral scatter to 1km and the depth range to between 16 and 18 km. A similar swarm took place in 1976, with 17 earthquakes catalogued between M2.6 and M4.6. Although the seismic network has changed significantly in 30 years, it is likely that the structures responsible for the 1976 earthquakes are also active in the recent sequence. Seismicity rates fluctuate greatly, with both larger and smaller earthquake productivity waxing and waning together. There is no obvious periodicity in this fluctuation. Waveform similarity amongst the earthquakes suggests only 2-3 highly productive source zones, which appear to be active at different times. High precision relative relocations using waveform cross correlation techniques will be presented to better characterize these source zones.

  9. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  10. Dynamic scaling in natural swarms

    Science.gov (United States)

    Cavagna, Andrea; Conti, Daniele; Creato, Chiara; Del Castello, Lorenzo; Giardina, Irene; Grigera, Tomas S.; Melillo, Stefania; Parisi, Leonardo; Viale, Massimiliano

    2017-09-01

    Collective behaviour in biological systems presents theoretical challenges beyond the borders of classical statistical physics. The lack of concepts such as scaling and renormalization is particularly problematic, as it forces us to negotiate details whose relevance is often hard to assess. In an attempt to improve this situation, we present here experimental evidence of the emergence of dynamic scaling laws in natural swarms of midges. We find that spatio-temporal correlation functions in different swarms can be rescaled by using a single characteristic time, which grows with the correlation length with a dynamical critical exponent z ~ 1, a value not found in any other standard statistical model. To check whether out-of-equilibrium effects may be responsible for this anomalous exponent, we run simulations of the simplest model of self-propelled particles and find z ~ 2, suggesting that natural swarms belong to a novel dynamic universality class. This conclusion is strengthened by experimental evidence of the presence of non-dissipative modes in the relaxation, indicating that previously overlooked inertial effects are needed to describe swarm dynamics. The absence of a purely dissipative regime suggests that natural swarms undergo a near-critical censorship of hydrodynamics.

  11. Particle Swarm Optimization with Double Learning Patterns.

    Science.gov (United States)

    Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

    2016-01-01

    Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants.

  12. Particle Swarm Optimization with Double Learning Patterns

    Directory of Open Access Journals (Sweden)

    Yuanxia Shen

    2016-01-01

    Full Text Available Particle Swarm Optimization (PSO is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants.

  13. UAV Swarm Operational Risk Assessment System

    Science.gov (United States)

    2015-09-01

    distribution is unlimited UAV SWARM OPERATIONAL RISK ASSESSMENT SYSTEM by Team CQ Alpha Cohort 311-141A September 2015 Project Advisors: Gregory......need for a UAV Swarm Risk Assessment Tool and how it can assist the Navy’s decision makers in assessing risk of UAV swarm threats in littoral

  14. Multispacecraft current estimates at swarm

    DEFF Research Database (Denmark)

    Dunlop, M. W.; Yang, Y.-Y.; Yang, J.-Y.

    2015-01-01

    During the first several months of the three-spacecraft Swarm mission all three spacecraft camerepeatedly into close alignment, providing an ideal opportunity for validating the proposed dual-spacecraftmethod for estimating current density from the Swarm magnetic field data. Two of the Swarm...... orbit the use oftime-shifted positions allow stable estimates of current density to be made and can verify temporal effects aswell as validating the interpretation of the current components as arising predominantly from field-alignedcurrents. In the case of four-spacecraft configurations we can resolve...... the full vector current and therefore cancheck the perpendicular as well as parallel current density components directly, together with the qualityfactor for the estimates directly (for the first time in situ at low Earth orbit)....

  15. Nowcasting Earthquakes

    Science.gov (United States)

    Rundle, J. B.; Donnellan, A.; Grant Ludwig, L.; Turcotte, D. L.; Luginbuhl, M.; Gail, G.

    2016-12-01

    Nowcasting is a term originating from economics and finance. It refers to the process of determining the uncertain state of the economy or markets at the current time by indirect means. We apply this idea to seismically active regions, where the goal is to determine the current state of the fault system, and its current level of progress through the earthquake cycle. In our implementation of this idea, we use the global catalog of earthquakes, using "small" earthquakes to determine the level of hazard from "large" earthquakes in the region. Our method does not involve any model other than the idea of an earthquake cycle. Rather, we define a specific region and a specific large earthquake magnitude of interest, ensuring that we have enough data to span at least 20 or more large earthquake cycles in the region. We then compute the earthquake potential score (EPS) which is defined as the cumulative probability distribution P(nearthquakes in the region. From the count of small earthquakes since the last large earthquake, we determine the value of EPS = P(nearthquake cycle in the defined region at the current time.

  16. Swarm Science objectives and challenges

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Lühr, Hermann; Hulot, Gauthier

    Swarm is the fifth Earth Explorer mission in ESA’s Living Planet Programme to be launched in 2009. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution. The innovative constellation concept and a unique set of dedicated instrume...... instruments will provide the necessary observations that are required to separate and model the various sources of the geomagnetic field. This will provide new insights into the Earth system by improving our understanding of the Earth’s interior and Sun-Earth connection processes....

  17. Swarm Utilisation Analysis: LEO satellite observations for the ESA's SSA Space Weather network

    Science.gov (United States)

    Kervalishvili, Guram; Stolle, Claudia; Rauberg, Jan; Olsen, Nils; Vennerstrøm, Susanne; Gullikstad Johnsen, Magnar; Hall, Chris

    2017-04-01

    ESA's (European Space Agency) constellation mission Swarm was successfully launched on 22 November 2013. The three satellites achieved their final constellation on 17 April 2014 and since then Swarm-A and Swarm-C orbiting the Earth at about 470 km (flying side-by-side) and Swarm-B at about 520 km altitude. Each of Swarm satellite carries instruments with high precision to measure magnetic and electric fields, neutral and plasma densities, and TEC (Total Electron Content) for which a dual frequency GPS receiver is used. SUA (Swarm Utilisation Analysis) is a project of the ESA's SSA (Space Situational Awareness) SWE (Space Weather) program. Within this framework GFZ (German Research Centre for Geosciences, Potsdam, Germany) and DTU (National Space Institute, Kongens Lyngby, Denmark) have developed two new Swarm products ROT (Rate Of change of TEC) and PEJ (Location and intensity level of Polar Electrojets), respectively. ROT is derived as the first time derivative from the Swarm measurements of TEC at 1 Hz sampling. ROT is highly relevant for users in navigation and communications: strong plasma gradients cause GPS signal degradation or even loss of GPS signal. Also, ROT is a relevant space weather asset irrespective of geomagnetic activity, e.g., high amplitude values of ROT occur during all geomagnetic conditions. PEJ is derived from the Swarm measurements of the magnetic field strength at 1 Hz sampling. PEJ has a high-level importance for power grid companies since the polar electrojet is a major cause for ground-induced currents. ROT and PEJ together with five existing Swarm products TEC, electron density, IBI (Ionospheric Bubble Index), FAC (Field-Aligned Current), and vector magnetic field build the SUA service prototype. This prototype will be integrated into ESA's SSA Space Weather network as a federated service and will be available soon from ESA's SSA SWE Ionospheric Weather and Geomagnetic Conditions Expert Service Centres (ESCs).

  18. Adaptive Gradient Multiobjective Particle Swarm Optimization.

    Science.gov (United States)

    Han, Honggui; Lu, Wei; Zhang, Lu; Qiao, Junfei

    2017-10-09

    An adaptive gradient multiobjective particle swarm optimization (AGMOPSO) algorithm, based on a multiobjective gradient (stocktickerMOG) method and a self-adaptive flight parameters mechanism, is developed to improve the computation performance in this paper. In this AGMOPSO algorithm, the stocktickerMOG method is devised to update the archive to improve the convergence speed and the local exploitation in the evolutionary process. Meanwhile, the self-adaptive flight parameters mechanism, according to the diversity information of the particles, is then established to balance the convergence and diversity of AGMOPSO. Attributed to the stocktickerMOG method and the self-adaptive flight parameters mechanism, this AGMOPSO algorithm not only has faster convergence speed and higher accuracy, but also its solutions have better diversity. Additionally, the convergence is discussed to confirm the prerequisite of any successful application of AGMOPSO. Finally, with regard to the computation performance, the proposed AGMOPSO algorithm is compared with some other multiobjective particle swarm optimization algorithms and two state-of-the-art multiobjective algorithms. The results demonstrate that the proposed AGMOPSO algorithm can find better spread of solutions and have faster convergence to the true Pareto-optimal front.

  19. Gold rush - A swarm dynamics in games

    Science.gov (United States)

    Zelinka, Ivan; Bukacek, Michal

    2017-07-01

    This paper is focused on swarm intelligence techniques and its practical use in computer games. The aim is to show how a swarm dynamics can be generated by multiplayer game, then recorded, analyzed and eventually controlled. In this paper we also discuss possibility to use swarm intelligence instead of game players. Based on our previous experiments two games, using swarm algorithms are mentioned briefly here. The first one is strategy game StarCraft: Brood War, and TicTacToe in which SOMA algorithm has also take a role of player against human player. Open research reported here has shown potential benefit of swarm computation in the field of strategy games and players strategy based on swarm behavior record and analysis. We propose new game called Gold Rush as an experimental environment for human or artificial swarm behavior and consequent analysis.

  20. Epidemic Synchronization in Robotic Swarms

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Ngo, Trung Dung

    2009-01-01

    Clock synchronization in swarms of networked mobile robots is studied in a probabilistic, epidemic framework. In this setting communication and synchonization is considered to be a randomized process, taking place at unplanned instants of geographical rendezvous between robots. In combination wit...

  1. behaved particle swarm optimization (QPSO)

    African Journals Online (AJOL)

    Administrator

    2011-06-13

    Jun 13, 2011 ... fermentation process, and consequently, it increased the yield of fermentation. Key words: Soft-sensing model, quantum-behaved particle swarm optimization algorithm, neural network. INTRODUCTION. In industrial production through fermentation, the main effect variables include physical variables (the ...

  2. Transport of Particle Swarms Through Fractures

    Science.gov (United States)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2011-12-01

    The transport of engineered micro- and nano-scale particles through fractured rock is often assumed to occur as dispersions or emulsions. Another potential transport mechanism is the release of particle swarms from natural or industrial processes where small liquid drops, containing thousands to millions of colloidal-size particles, are released over time from seepage or leaks. Swarms have higher velocities than any individual colloid because the interactions among the particles maintain the cohesiveness of the swarm as it falls under gravity. Thus particle swarms give rise to the possibility that engineered particles may be transported farther and faster in fractures than predicted by traditional dispersion models. In this study, the effect of fractures on colloidal swarm cohesiveness and evolution was studied as a swarm falls under gravity and interacts with fracture walls. Transparent acrylic was used to fabricate synthetic fracture samples with either (1) a uniform aperture or (2) a converging aperture followed by a uniform aperture (funnel-shaped). The samples consisted of two blocks that measured 100 x 100 x 50 mm. The separation between these blocks determined the aperture (0.5 mm to 50 mm). During experiments, a fracture was fully submerged in water and swarms were released into it. The swarms consisted of dilute suspensions of either 25 micron soda-lime glass beads (2% by mass) or 3 micron polystyrene fluorescent beads (1% by mass) with an initial volume of 5μL. The swarms were illuminated with a green (525 nm) LED array and imaged optically with a CCD camera. In the uniform aperture fracture, the speed of the swarm prior to bifurcation increased with aperture up to a maximum at a fracture width of approximately 10 mm. For apertures greater than ~15 mm, the velocity was essentially constant with fracture width (but less than at 10 mm). This peak suggests that two competing mechanisms affect swarm velocity in fractures. The wall provides both drag, which

  3. The k -Unanimity Rule for Self-Organized Decision-Making in Swarms of Robots.

    Science.gov (United States)

    Scheidler, Alexander; Brutschy, Arne; Ferrante, Eliseo; Dorigo, Marco

    2016-05-01

    In this paper, we propose a collective decision-making method for swarms of robots. The method enables a robot swarm to select, from a set of possible actions, the one that has the fastest mean execution time. By means of positive feedback the method achieves consensus on the fastest action. The novelty of our method is that it allows robots to collectively find consensus on the fastest action without measuring explicitly the execution times of all available actions. We study two analytical models of the decision-making method in order to understand the dynamics of the consensus formation process. Moreover, we verify the applicability of the method in a real swarm robotics scenario. To this end, we conduct three sets of experiments that show that a robotic swarm can collectively select the shortest of two paths. Finally, we use a Monte Carlo simulation model to study and predict the influence of different parameters on the method.

  4. A Distributed Particle Swarm Optimization Zlgorithmfor Flexible Job-hop Scheduling Problem

    Directory of Open Access Journals (Sweden)

    LIU Sheng--hui

    2017-06-01

    Full Text Available According to the characteristics of the Flexible job shop scheduling problem the minimum makespan as measures we proposed a distributed particle swarm optimization algorithm aiming to solve flexible job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi agent particle swarm optimization model in this algorithm it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the FJSP and it also verified the reasonableness of the multi}gent particle swarm optimization model.

  5. Phase Coexistence in Insect Swarms

    Science.gov (United States)

    Sinhuber, Michael; Ouellette, Nicholas T.

    2017-10-01

    Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core "condensed" phase surrounded by a dilute "vapor" phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.

  6. Organic Computing and Swarm Intelligence

    Science.gov (United States)

    Merkle, Daniel; Middendorf, Martin; Scheidler, Alexander

    The relations between swarm intelligence and organic computing are discussed in this chapter. The aim of organic computing is to design and study computing systems that consist of many autonomous components and show forms of collective behavior. Such organic computing systems (OC systems) should possess self-x properties (e.g., self-healing, self-managing, self-optimizing), have a decentralized control, and be adaptive to changing requirements of their user. Examples of OC systems are described in this chapter and two case studies are presented that show in detail that OC systems share important properties with social insect colonies and how methods of swarm intelligence can be used to solve problems in organic computing.

  7. Time Optimal Reachability Analysis Using Swarm Verification

    DEFF Research Database (Denmark)

    Zhang, Zhengkui; Nielsen, Brian; Larsen, Kim Guldstrand

    2016-01-01

    and planning problems, response time optimization etc. We propose swarm verification to accelerate time optimal reachability using the real-time model-checker Uppaal. In swarm verification, a large number of model checker instances execute in parallel on a computer cluster using different, typically randomized...... search strategies. We develop four swarm algorithms and evaluate them with four models in terms scalability, and time- and memory consumption. Three of these cooperate by exchanging costs of intermediate solutions to prune the search using a branch-and-bound approach. Our results show that swarm...

  8. Towards CHAOS-5 - How can Swarm contribute?

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Tøffner-Clausen, Lars

    2014-01-01

    The launch of ESA's satellite trio Swarm in November 2013 opens an exciting new chapter in the observation and monitoring of Earth's magnetic field from space. We report preliminary results from an extension of the CHAOS series of geomagnetic field models to include both scalar and vector field...... observations from the three Swarm satellites, along with the most recent quasi-definitive ground observatory data. The fit of this new update CHAOS field model to the Swarm observations will be presented in detail providing useful insight the initial Swarm data. Enhancements of the CHAOS modelling scheme...

  9. Analog earthquakes

    Energy Technology Data Exchange (ETDEWEB)

    Hofmann, R.B. [Center for Nuclear Waste Regulatory Analyses, San Antonio, TX (United States)

    1995-09-01

    Analogs are used to understand complex or poorly understood phenomena for which little data may be available at the actual repository site. Earthquakes are complex phenomena, and they can have a large number of effects on the natural system, as well as on engineered structures. Instrumental data close to the source of large earthquakes are rarely obtained. The rare events for which measurements are available may be used, with modfications, as analogs for potential large earthquakes at sites where no earthquake data are available. In the following, several examples of nuclear reactor and liquified natural gas facility siting are discussed. A potential use of analog earthquakes is proposed for a high-level nuclear waste (HLW) repository.

  10. Multiswarm Particle Swarm Optimization with Transfer of the Best Particle.

    Science.gov (United States)

    Wei, Xiao-peng; Zhang, Jian-xia; Zhou, Dong-sheng; Zhang, Qiang

    2015-01-01

    We propose an improved algorithm, for a multiswarm particle swarm optimization with transfer of the best particle called BMPSO. In the proposed algorithm, we introduce parasitism into the standard particle swarm algorithm (PSO) in order to balance exploration and exploitation, as well as enhancing the capacity for global search to solve nonlinear optimization problems. First, the best particle guides other particles to prevent them from being trapped by local optima. We provide a detailed description of BMPSO. We also present a diversity analysis of the proposed BMPSO, which is explained based on the Sphere function. Finally, we tested the performance of the proposed algorithm with six standard test functions and an engineering problem. Compared with some other algorithms, the results showed that the proposed BMPSO performed better when applied to the test functions and the engineering problem. Furthermore, the proposed BMPSO can be applied to other nonlinear optimization problems.

  11. Multiswarm Particle Swarm Optimization with Transfer of the Best Particle

    Directory of Open Access Journals (Sweden)

    Xiao-peng Wei

    2015-01-01

    Full Text Available We propose an improved algorithm, for a multiswarm particle swarm optimization with transfer of the best particle called BMPSO. In the proposed algorithm, we introduce parasitism into the standard particle swarm algorithm (PSO in order to balance exploration and exploitation, as well as enhancing the capacity for global search to solve nonlinear optimization problems. First, the best particle guides other particles to prevent them from being trapped by local optima. We provide a detailed description of BMPSO. We also present a diversity analysis of the proposed BMPSO, which is explained based on the Sphere function. Finally, we tested the performance of the proposed algorithm with six standard test functions and an engineering problem. Compared with some other algorithms, the results showed that the proposed BMPSO performed better when applied to the test functions and the engineering problem. Furthermore, the proposed BMPSO can be applied to other nonlinear optimization problems.

  12. Swarm Products and Space Weather Applications

    DEFF Research Database (Denmark)

    Stolle, Claudia; Olsen, Nils; Martini, Daniel

    The Swarm satellite constellation mission provides high precision magnetic field data and models and other observations that enable us to explore near Earth space for example in terms of in situ electron density and electric fields. On board GPS observables can be used for sounding ionospheric an...... in aeronomy and space weather. We will emphasize results from the Swarm mission....

  13. Swarm Data Processing and First Scientific Results

    DEFF Research Database (Denmark)

    Olsen, Nils

    2014-01-01

    , accelerometer, plasma and electric field measurements. These observations will be distributed by ESA as Level-1b data, which are the calibrated and formatted time series of e.g. the magnetic field measurements taken by each of the three Swarm satellites. The talks presents a first scientific validation of Swarm...... Level-1b data products....

  14. Particle Swarm Transport in Fracture Networks

    Science.gov (United States)

    Pyrak-Nolte, L. J.; Mackin, T.; Boomsma, E.

    2012-12-01

    Colloidal particles of many types occur in fractures in the subsurface as a result of both natural and industrial processes (e.g., environmental influences, synthetic nano- & micro-particles from consumer products, chemical and mechanical erosion of geologic material, proppants used in gas and oil extraction, etc.). The degree of localization and speed of transport of such particles depends on the transport mechanisms, the chemical and physical properties of the particles and the surrounding rock, and the flow path geometry through the fracture. In this study, we investigated the transport of particle swarms through artificial fracture networks. A synthetic fracture network was created using an Objet Eden 350V 3D printer to build a network of fractures. Each fracture in the network had a rectangular cross-sectional area with a constant depth of 7 mm but with widths that ranged from 2 mm to 11 mm. The overall dimensions of the network were 132 mm by 166 mm. The fracture network had 7 ports that were used either as the inlet or outlet for fluid flow through the sample or for introducing a particle swarm. Water flow rates through the fracture were controlled with a syringe pump, and ranged from zero flow to 6 ml/min. Swarms were composed of a dilute suspension (2% by mass) of 3 μm fluorescent polystyrene beads in water. Swarms with volumes of 5, 10, 20, 30 and 60 μl were used and delivered into the network using a second syringe pump. The swarm behavior was imaged using an optical fluorescent imaging system illuminated by green (525 nm) LED arrays and captured by a CCD camera. For fracture networks with quiescent fluids, particle swarms fell under gravity and remained localized within the network. Large swarms (30-60 μl) were observed to bifurcate at shallower depths resulting in a broader dispersal of the particles than for smaller swarm volumes. For all swarm volumes studied, particle swarms tended to bifurcate at the intersection between fractures. These

  15. Design and control of swarm dynamics

    CERN Document Server

    Bouffanais, Roland

    2016-01-01

    The book is about the key elements required for designing, building and controlling effective artificial swarms comprised of multiple moving physical agents. Therefore this book presents the fundamentals of each of those key elements in the particular frame of dynamic swarming, specifically exposing the profound connections between these elements and establish some general design principles for swarming behaviors. This scientific endeavor requires an inter-disciplinary approach: biomimetic inspiration from ethology and ecology, study of social information flow, analysis of temporal and adaptive signaling network of interaction, considerations of control of networked real-time systems, and lastly, elements of complex adaptive dynamical systems. This book offers a completely new perspective on the scientific understanding of dynamic collective behaviors thanks to its multi-disciplinary approach and its focus on artificial swarm of physical agents. Two of the key problems in understanding the emergence of swarm ...

  16. Insular species swarm goes underground

    DEFF Research Database (Denmark)

    P. S. Reboleira, Ana Sofia; Enghoff, Henrik

    2014-01-01

    -group, an insular species swarm distributed in the archipelagos of Madeira and the Canary Islands. We discuss the differences between the new species and their relatives and present information on the subterranean environment of Madeira. An updated overview of the subterranean biodiversity of millipedes......Two new species of the genus Cylindroiulus Verhoeff, 1894, C. julesvernei and C. oromii, are described from the subterranean ecosystem of Madeira Island, Portugal. Species are illustrated with photographs and diagrammatic drawings. The new species belong to the Cylindroiulus madeirae...

  17. Earthquake Facts

    Science.gov (United States)

    ... to the Atlantic Ocean, around Africa, Asia, and Australia, and under the Pacific Ocean to the west ... are similar to earthquakes, but occur within the ice sheet itself instead of the land underneath the ...

  18. Cooperative Control of Swarms of Unmanned Aerial Vehicles

    NARCIS (Netherlands)

    De Vries, E.; Subbarao, K.

    2011-01-01

    Potential function based swarm control is a technique using artificial potential functions to generate steering commands resulting in swarming behavior. This means that the vehicles in the swarm autonomously take care of flying in formation, resulting in steering the swarm, instead of all the

  19. Swarming dynamics in bacterial colonies

    Science.gov (United States)

    Zhang, Hepeng; Be'Er, Avraham; Smith, Rachel; Florin, E.-L.; Swinney, Harry L.

    2009-11-01

    Swarming is a widespread phenomenon observed in both biological and non-biological systems. Large mammal herds, fish schools, and bird flocks are among the most spectacular examples. Many theoretical and numerical efforts have been made to unveil the general principles of the phenomenon, but systematic experimental studies have been very limited. We determine the characteristic velocity, length, and time scales for bacterial motion in swarming colonies of Paenibacillus dendritiformis growing on semi-solid agar substrates. The bacteria swim within a thin fluid layer, and they form long-lived jets and vortices. These coherent structures lead to anisotropy in velocity spatial correlations and to a two-step relaxation in velocity temporal correlations. The mean squared displacement of passive tracers exhibits a short-time regime with nearly ballistic transport and a diffusive long-time regime. We find that various definitions of the correlation length all lead to length scales that are, surprisingly, essentially independent of the mean bacterial speed, while the correlation time is linearly proportional to the ratio of the correlation length to the mean speed.

  20. Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.

    Science.gov (United States)

    Garro, Beatriz A; Vázquez, Roberto A

    2015-01-01

    Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.

  1. Earthquakes for Kids

    Science.gov (United States)

    ... dug across a fault to learn about past earthquakes. Science Fair Projects A GPS instrument measures slow movements of the ground. Become an Earthquake Scientist Cool Earthquake Facts Today in Earthquake History ...

  2. Earthquake Hazards Program: Earthquake Scenarios

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A scenario represents one realization of a potential future earthquake by assuming a particular magnitude, location, and fault-rupture geometry and estimating...

  3. Connecting slow earthquakes to huge earthquakes

    OpenAIRE

    Obara, Kazushige; Kato, Aitaro

    2016-01-01

    Slow earthquakes are characterized by a wide spectrum of fault slip behaviors and seismic radiation patterns that differ from those of traditional earthquakes. However, slow earthquakes and huge megathrust earthquakes can have common slip mechanisms and are located in neighboring regions of the seismogenic zone. The frequent occurrence of slow earthquakes may help to reveal the physics underlying megathrust events as useful analogs. Slow earthquakes may function as stress meters because of th...

  4. A detailed analysis of some local earthquakes at Somma-Vesuvius

    OpenAIRE

    C. Troise; C. Godano; F. Di Sena; G. De Natale; U. Coppa; P. Capuano

    1999-01-01

    In this paper, we analyze local earthquakes which occurred at Somma-Vesuvius during two episodes of intense seismic swarms, in 1989 and 1995 respectively. For the selected earthquakes we have computed accurate hypocentral locations, focal mechanisms and spectral parameters. We have also studied the ground acceleration produced by the largest events of the sequences (ML 3.0), at various digital stations installed in the area during the periods of higher seismic activity. The main result is tha...

  5. Physiological processes related to the bee swarming

    Directory of Open Access Journals (Sweden)

    Jiří Svoboda

    2010-01-01

    Full Text Available One of the essential genetically subjected behaviours of a bee-colony is swarming. However, in the time of queen breeding and technical approach to colony division, swarming constitutes a problem in the effectiveness of controlled beekeeping and subsequently in decreasing of the attainable economic profits. The intensity of swarming is a polyfactorial phenomenon whose characteristic feature is seasonality (the availability of breed, course of weather so the swarming intensity is different in particular years. This study is connected with the research carried out at the Department of Zoo­lo­gy, Fisheries, Hydrobiology and Apiculture at Mendel University in Brno. The experiment focused on the relationship between the swarming and biological state of bee-colony was realized in three seasons of the period 2003–2005. Experimental bee-colonies were stimulated to the swarming fever by zoo-technical practices, at the same time the biological status of given bee-colony was observed. Within the process of marking of newly emerged workers there was observed their number continuously during the particular season. The samples of 3- and 4-week-old workers were instrumental to the analysis of the development of their hypopharyngeal glands. The study has proved that a bee-colonies building higher number of queen cells are likely expected to be in swarming fever, b 3-week-old workers have hypopharyngeal glands in higher stage of development than 4-week-old workers, c higher stage of swarming fever is closely correlated with higher stage of de­ve­lop­ment of hypopharyngeal glands. These facts can contribute to the comprehension of the reason and relationships of the swarming.

  6. Swarm Intelligence Optimization and Its Applications

    Science.gov (United States)

    Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

    Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

  7. Binary particle swarm optimization for operon prediction.

    Science.gov (United States)

    Chuang, Li-Yeh; Tsai, Jui-Hung; Yang, Cheng-Hong

    2010-07-01

    An operon is a fundamental unit of transcription and contains specific functional genes for the construction and regulation of networks at the entire genome level. The correct prediction of operons is vital for understanding gene regulations and functions in newly sequenced genomes. As experimental methods for operon detection tend to be nontrivial and time consuming, various methods for operon prediction have been proposed in the literature. In this study, a binary particle swarm optimization is used for operon prediction in bacterial genomes. The intergenic distance, participation in the same metabolic pathway, the cluster of orthologous groups, the gene length ratio and the operon length are used to design a fitness function. We trained the proper values on the Escherichia coli genome, and used the above five properties to implement feature selection. Finally, our study used the intergenic distance, metabolic pathway and the gene length ratio property to predict operons. Experimental results show that the prediction accuracy of this method reached 92.1%, 93.3% and 95.9% on the Bacillus subtilis genome, the Pseudomonas aeruginosa PA01 genome and the Staphylococcus aureus genome, respectively. This method has enabled us to predict operons with high accuracy for these three genomes, for which only limited data on the properties of the operon structure exists.

  8. Mining Customer Change Model Based on Swarm Intelligence

    Science.gov (United States)

    Jin, Peng; Zhu, Yunlong

    Understanding and adapting to changes of customer behavior is an important aspect of surviving in a continuously changing market environment for a modern company. The concept of customer change model mining is introduced and its process is analyzed in this paper. A customer change model mining method based on swarm intelligence is presented, and the strategies of pheromone updating and items searching are given. Finally, an examination on two customer datasets of a telecom company illuminates that this method can achieve customer change model efficiently.

  9. Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

    Directory of Open Access Journals (Sweden)

    Haifa Mehdi

    2011-11-01

    Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

  10. Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

    Directory of Open Access Journals (Sweden)

    Haifa Mehdi

    2011-11-01

    Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov‐based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSOmethod,differentindexperformancesare considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

  11. A REVIEW OF SWARMING UNMANNED AERIAL VEHICLES

    Directory of Open Access Journals (Sweden)

    CORNEA Mihai

    2016-11-01

    Full Text Available This paper in if fact an overview of state of the art in mobile multi-robot systems as an initial part of our research in implementing a system based on swarm robotics concepts to be used in natural disaster search and rescue missions. The system is to be composed of a group of drones that can detect survivor mobile cell signals and exhibit some other features as well. This paper surveys the swarm robotics research landscape to provide a theoretical background to the implementation and help determine the techniques available to create the system. The Particle swarm optimization (PSO and Glowworm swarm optimization (GSO algorithms are briefly described and there is also insight into Bird flocking behavior and the model behind it

  12. Locating multiple optima using particle swarm optimization

    CSIR Research Space (South Africa)

    Brits, R

    2007-01-01

    Full Text Available Many scientific and engineering applications require optimization methods to find more than one solution to multimodal optimization problems. This paper presents a new particle swarm optimization (PSO) technique to locate and refine multiple...

  13. Synchronized rotation in swarms of magnetotactic bacteria

    Science.gov (United States)

    Belovs, M.; Livanovičs, R.; CÄ`bers, A.

    2017-10-01

    Self-organizing behavior has been widely reported in both natural and artificial systems, typically distinguishing between temporal organization (synchronization) and spatial organization (swarming). Swarming has been experimentally observed in systems of magnetotactic bacteria under the action of external magnetic fields. Here we present a model of ensembles of magnetotactic bacteria in which hydrodynamic interactions lead to temporal synchronization in addition to the swarming. After a period of stabilization during which the bacteria form a quasiregular hexagonal lattice structure, the entire swarm begins to rotate in a direction opposite to the direction of the rotation of the magnetic field. We thus illustrate an emergent mechanism of macroscopic motion arising from the synchronized microscopic rotations of hydrodynamically interacting bacteria, reminiscent of the recently proposed concept of swarmalators.

  14. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  15. SWARM - An earth Observation Mission investigating Geospace

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Lühr, H.; Knudsen, D.

    2008-01-01

    The Swarm mission was selected as the 5th mission in ESA's Earth Explorer Programme in 2004. This mission aims at measuring the Earth's magnetic field with unprecedented accuracy. This will be done by a constellation of three satellites, where two will fly at lower altitude, measuring the gradient...... of the Swarm science objectives, the mission concept, the scientific instrumentation, and the expected contribution to the ILWS programme will be summarized. (C) 2007 Published by Elsevier Ltd on behalf of COSPAR....

  16. The Swarm Computing Approach to Business Intelligence

    Directory of Open Access Journals (Sweden)

    Schumann Andrew

    2015-07-01

    Full Text Available We have proposed to use some features of swarm behaviours in modelling business processes. Due to these features we deal with a propagation of business processes in all accessible directions. This propagation is involved into our formalization instead of communicating sequential processes. As a result, we have constructed a business process diagram language based on the swarm behavior and an extension of that language in the form of reflexive management language.

  17. Neuro-Fuzzy DC Motor Speed Control Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Boumediene ALLAOUA

    2009-12-01

    Full Text Available This paper presents an application of Adaptive Neuro-Fuzzy Inference System (ANFIS control for DC motor speed optimized with swarm collective intelligence. First, the controller is designed according to Fuzzy rules such that the systems are fundamentally robust. Secondly, an adaptive Neuro-Fuzzy controller of the DC motor speed is then designed and simulated; the ANFIS has the advantage of expert knowledge of the Fuzzy inference system and the learning capability of neural networks. Finally, the ANFIS is optimized by Swarm Intelligence. Digital simulation results demonstrate that the deigned ANFIS-Swarm speed controller realize a good dynamic behavior of the DC motor, a perfect speed tracking with no overshoot, give better performance and high robustness than those obtained by the ANFIS alone.

  18. On Formal Specification of Emergent Behaviours in Swarm Robotic Systems

    Directory of Open Access Journals (Sweden)

    Alan FT Winfield

    2005-12-01

    Full Text Available It is a characteristic of swarm robotics that specifying overall emergent swarm behaviours in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation we need such specifications. This paper explores the use of temporal logic to formally specify, and possibly also prove, the emergent behaviours of a robotic swarm. The paper makes use of a simplified wireless connected swarm as a case study with which to illustrate the approach. Such a formal approach could be an important step toward a disciplined design methodology for swarm robotics.

  19. The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products

    DEFF Research Database (Denmark)

    Olsen, Nils; Friis-Christensen, Eigil; Floberghagen, R.

    2013-01-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, is expected to be launched in late 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution......, in order to gain new insights into the Earth system by improving our understanding of the Earth's interior and environment. In order to derive advanced models of the geomagnetic field (and other higher-level data products) it is necessary to take explicit advantage of the constellation aspect of Swarm....... The Swarm SCARF (Satellite Constellation Application and Research Facility) has been established with the goal of deriving Level-2 products by combination of data from the three satellites, and of the various instruments. The present paper describes the Swarm input data products (Level-1b and auxiliary data...

  20. Merging the fields of swarm robotics and new media: Perceiving swarm robotics as new media

    Directory of Open Access Journals (Sweden)

    Monika O. Ivanova

    2014-06-01

    Full Text Available The aim of this paper is to provide evidence that swarm robotic systems can be perceived as new media objects. A thorough description of the five principles of new media proposed by Lev Manovich in “The Language of New Media” is presented. This is complemented by a state of the art on swarm robotics with an in-depth comparison of the characteristics of both fields. Also presented are examples of swarm robotics used in new media installations in order to illustrate the cutting-edge applications of robotics and artificial intelligence achieved through the unity of bothfields. The hypothesis of this research is that a novel point of view would be introduced by examining the field of swarm robotics through the scope of new media, which would benefit thework of both new media and swarm robotic researchers.

  1. The Fate of Colloidal Swarms in Fractures

    Science.gov (United States)

    Pyrak-Nolte, L. J.; Olander, M. K.

    2009-12-01

    In the next 10-20 years, nano- and micro-sensor engineering will advance to the stage where sensor swarms could be deployed in the subsurface to probe rock formations and the fluids contained in them. Sensor swarms are groups of nano- or micro- sensors that are maintained as a coherent group to enable either sensor-to-sensor communication and/or coherent transmission of information as a group. The ability to maintain a swarm of sensors depends on the complexity of the flow paths in the rock, on the size and shape of the sensors and on the chemical interaction among the sensors, fluids, and rock surfaces. In this study, we investigate the effect of fracture aperture and fluid currents on the formation, evolution and break-up of colloidal swarms under gravity. Transparent cubic samples (100 mm x 100 mm x 100 mm) containing synthetic fractures with uniform and non-uniform aperture distributions were used to quantify the effect of aperture on swarm formation, swarm velocity, and swarm geometry using optical imaging. A fracture with a uniform aperture distribution was fabricated from two polished rectangular prisms of acrylic. A fracture with a non-uniform aperture distribution was created with a polished rectangular acrylic prism and an acrylic replica of an induced fracture surface from a carbonate rock. A series of experiments were performed to determine how swarm movement and geometry are affected as the walls of the fracture are brought closer together from 50 mm to 1 mm. During the experiments, the fracture was fully saturated with water. We created the swarms using two different particle sizes in dilute suspension (~ 1.0% by mass) . The particles were 3 micron diameter fluorescent polymer beads and 25 micron diameter soda-lime glass beads. The swarm behavior was imaged using an optical fluorescent imaging system composed of a CCD camera illuminated by a 100 mW diode-pumped doubled YAG laser. A swam was created when approximately 0.01 g drop of the suspension was

  2. Hybridization hotspots at bat swarming sites.

    Directory of Open Access Journals (Sweden)

    Wiesław Bogdanowicz

    Full Text Available During late summer and early autumn in temperate zones of the Northern Hemisphere, thousands of bats gather at caves, mainly for the purpose of mating. We demonstrated that this swarming behavior most probably leads not only to breeding among bats of the same species but also interbreeding between different species. Using 14 nuclear microsatellites and three different methods (the Bayesian assignment approaches of STRUCTURE and NEWHYBRIDS and a principal coordinate analysis of pairwise genetic distances, we analyzed 375 individuals belonging to three species of whiskered bats (genus Myotis at swarming sites across their sympatric range in southern Poland. The overall hybridization rate varied from 3.2 to 7.2%. At the species level, depending on the method used, these values ranged from 2.1-4.6% in M. mystacinus and 3.0-3.7% in M. brandtii to 6.5-30.4% in M. alcathoe. Hybrids occurred in about half of the caves we studied. In all three species, the sex ratio of hybrids was biased towards males but the observed differences did not differ statistically from those noted at the population level. In our opinion, factors leading to the formation of these admixed individuals and their relatively high frequency are: i swarming behaviour at swarming sites, where high numbers of bats belonging to several species meet; ii male-biased sex ratio during the swarming period; iii the fact that all these bats are generally polygynous. The highly different population sizes of different species at swarming sites may also play some role. Swarming sites may represent unique hybrid hotspots, which, as there are at least 2,000 caves in the Polish Carpathians alone, may occur on a massive scale not previously observed for any group of mammal species in the wild. Evidently, these sites should be treated as focal points for the conservation of biodiversity and evolutionary processes.

  3. Collective motion of predictive swarms.

    Directory of Open Access Journals (Sweden)

    Nathaniel Rupprecht

    Full Text Available Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

  4. Genetic Learning Particle Swarm Optimization.

    Science.gov (United States)

    Gong, Yue-Jiao; Li, Jing-Jing; Zhou, Yicong; Li, Yun; Chung, Henry Shu-Hung; Shi, Yu-Hui; Zhang, Jun

    2016-10-01

    Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for "learning." This leads to a generalized "learning PSO" paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.

  5. Connecting slow earthquakes to huge earthquakes.

    Science.gov (United States)

    Obara, Kazushige; Kato, Aitaro

    2016-07-15

    Slow earthquakes are characterized by a wide spectrum of fault slip behaviors and seismic radiation patterns that differ from those of traditional earthquakes. However, slow earthquakes and huge megathrust earthquakes can have common slip mechanisms and are located in neighboring regions of the seismogenic zone. The frequent occurrence of slow earthquakes may help to reveal the physics underlying megathrust events as useful analogs. Slow earthquakes may function as stress meters because of their high sensitivity to stress changes in the seismogenic zone. Episodic stress transfer to megathrust source faults leads to an increased probability of triggering huge earthquakes if the adjacent locked region is critically loaded. Careful and precise monitoring of slow earthquakes may provide new information on the likelihood of impending huge earthquakes. Copyright © 2016, American Association for the Advancement of Science.

  6. Update earthquake risk assessment in Cairo, Egypt

    Science.gov (United States)

    Badawy, Ahmed; Korrat, Ibrahim; El-Hadidy, Mahmoud; Gaber, Hanan

    2017-07-01

    The Cairo earthquake (12 October 1992; m b = 5.8) is still and after 25 years one of the most painful events and is dug into the Egyptians memory. This is not due to the strength of the earthquake but due to the accompanied losses and damages (561 dead; 10,000 injured and 3000 families lost their homes). Nowadays, the most frequent and important question that should rise is "what if this earthquake is repeated today." In this study, we simulate the same size earthquake (12 October 1992) ground motion shaking and the consequent social-economic impacts in terms of losses and damages. Seismic hazard, earthquake catalogs, soil types, demographics, and building inventories were integrated into HAZUS-MH to produce a sound earthquake risk assessment for Cairo including economic and social losses. Generally, the earthquake risk assessment clearly indicates that "the losses and damages may be increased twice or three times" in Cairo compared to the 1992 earthquake. The earthquake risk profile reveals that five districts (Al-Sahel, El Basateen, Dar El-Salam, Gharb, and Madinat Nasr sharq) lie in high seismic risks, and three districts (Manshiyat Naser, El-Waily, and Wassat (center)) are in low seismic risk level. Moreover, the building damage estimations reflect that Gharb is the highest vulnerable district. The analysis shows that the Cairo urban area faces high risk. Deteriorating buildings and infrastructure make the city particularly vulnerable to earthquake risks. For instance, more than 90 % of the estimated buildings damages are concentrated within the most densely populated (El Basateen, Dar El-Salam, Gharb, and Madinat Nasr Gharb) districts. Moreover, about 75 % of casualties are in the same districts. Actually, an earthquake risk assessment for Cairo represents a crucial application of the HAZUS earthquake loss estimation model for risk management. Finally, for mitigation, risk reduction, and to improve the seismic performance of structures and assure life safety

  7. P-adic valued models of swarm behaviour

    Science.gov (United States)

    Schumann, Andrew

    2017-07-01

    The swarm behaviour can be fully determined by attractants (food pieces) which change the directions of swarm propagation. If we assume that at each time step the swarm can find out not more than p - 1 attractants, then the swarm behaviour can be coded by p-adic integers. The main task of any swarm is to logistically optimize the road system connecting the reachable attractants. In the meanwhile, the transporting network of the swarm has loops (circles) and permanently changes, e.g. the swarm occupies some attractants and leaves the others. However, this complex dynamics can be effectively coded by p-adic integers. This allows us to represent the swarm behaviour as a calculation on p-adic valued strings.

  8. Comparison of two large earthquakes: the 2008 Sichuan Earthquake and the 2011 East Japan Earthquake.

    Science.gov (United States)

    Otani, Yuki; Ando, Takayuki; Atobe, Kaori; Haiden, Akina; Kao, Sheng-Yuan; Saito, Kohei; Shimanuki, Marie; Yoshimoto, Norifumi; Fukunaga, Koichi

    2012-01-01

    Between August 15th and 19th, 2011, eight 5th-year medical students from the Keio University School of Medicine had the opportunity to visit the Peking University School of Medicine and hold a discussion session titled "What is the most effective way to educate people for survival in an acute disaster situation (before the mental health care stage)?" During the session, we discussed the following six points: basic information regarding the Sichuan Earthquake and the East Japan Earthquake, differences in preparedness for earthquakes, government actions, acceptance of medical rescue teams, earthquake-induced secondary effects, and media restrictions. Although comparison of the two earthquakes was not simple, we concluded that three major points should be emphasized to facilitate the most effective course of disaster planning and action. First, all relevant agencies should formulate emergency plans and should supply information regarding the emergency to the general public and health professionals on a normal basis. Second, each citizen should be educated and trained in how to minimize the risks from earthquake-induced secondary effects. Finally, the central government should establish a single headquarters responsible for command, control, and coordination during a natural disaster emergency and should centralize all powers in this single authority. We hope this discussion may be of some use in future natural disasters in China, Japan, and worldwide.

  9. Visual Analysis of Swarm and Geomagnetic Model Data

    Science.gov (United States)

    Santillan Pedrosa, Daniel; Triebnig, Gerhard

    2016-08-01

    ESA Swarm data is available for anyone to use via the virtual research platform "VirES for Swarm" (http://vires.services). A highly interactive data manipulation and retrieval interface is provided for the magnetic products of the European Space Agency (ESA) Swarm constellation mission. It includes tools for studying various Earth magnetic models and for comparing them to the Swarm satellite measurements and given solar activity levels.

  10. Characterization of Novel Factors Involved in Swimming and Swarming Motility in Salmonella enterica Serovar Typhimurium.

    Directory of Open Access Journals (Sweden)

    Julia Andrea Deditius

    Full Text Available Salmonella enterica utilizes flagellar motility to swim through liquid environments and on surfaces. The biosynthesis of the flagellum is regulated on various levels, including transcriptional and posttranscriptional mechanisms. Here, we investigated the motility phenotype of 24 selected single gene deletions that were previously described to display swimming and swarming motility effects. Mutations in flgE, fliH, ydiV, rfaG, yjcC, STM1267 and STM3363 showed an altered motility phenotype. Deletions of flgE and fliH displayed a non-motile phenotype in both swimming and swarming motility assays as expected. The deletions of STM1267, STM3363, ydiV, rfaG and yjcC were further analyzed in detail for flagellar and fimbrial gene expression and filament formation. A ΔydiV mutant showed increased swimming motility, but a decrease in swarming motility, which coincided with derepression of curli fimbriae. A deletion of yjcC, encoding for an EAL domain-containing protein, increased swimming motility independent on flagellar gene expression. A ΔSTM1267 mutant displayed a hypermotile phenotype on swarm agar plates and was found to have increased numbers of flagella. In contrast, a knockout of STM3363 did also display an increase in swarming motility, but did not alter flagella numbers. Finally, a deletion of the LPS biosynthesis-related protein RfaG reduced swimming and swarming motility, associated with a decrease in transcription from flagellar class II and class III promoters and a lack of flagellar filaments.

  11. Double Flight-Modes Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2013-01-01

    Full Text Available Getting inspiration from the real birds in flight, we propose a new particle swarm optimization algorithm that we call the double flight modes particle swarm optimization (DMPSO in this paper. In the DMPSO, each bird (particle can use both rotational flight mode and nonrotational flight mode to fly, while it is searching for food in its search space. There is a King in the swarm of birds, and the King controls each bird’s flight behavior in accordance with certain rules all the time. Experiments were conducted on benchmark functions such as Schwefel, Rastrigin, Ackley, Step, Griewank, and Sphere. The experimental results show that the DMPSO not only has marked advantage of global convergence property but also can effectively avoid the premature convergence problem and has good performance in solving the complex and high-dimensional optimization problems.

  12. Statistical tests of simple earthquake cycle models

    Science.gov (United States)

    DeVries, Phoebe M. R.; Evans, Eileen L.

    2016-12-01

    A central goal of observing and modeling the earthquake cycle is to forecast when a particular fault may generate an earthquake: a fault late in its earthquake cycle may be more likely to generate an earthquake than a fault early in its earthquake cycle. Models that can explain geodetic observations throughout the entire earthquake cycle may be required to gain a more complete understanding of relevant physics and phenomenology. Previous efforts to develop unified earthquake models for strike-slip faults have largely focused on explaining both preseismic and postseismic geodetic observations available across a few faults in California, Turkey, and Tibet. An alternative approach leverages the global distribution of geodetic and geologic slip rate estimates on strike-slip faults worldwide. Here we use the Kolmogorov-Smirnov test for similarity of distributions to infer, in a statistically rigorous manner, viscoelastic earthquake cycle models that are inconsistent with 15 sets of observations across major strike-slip faults. We reject a large subset of two-layer models incorporating Burgers rheologies at a significance level of α = 0.05 (those with long-term Maxwell viscosities ηM 4.6 × 1020 Pa s) but cannot reject models on the basis of transient Kelvin viscosity ηK. Finally, we examine the implications of these results for the predicted earthquake cycle timing of the 15 faults considered and compare these predictions to the geologic and historical record.

  13. Swarms of UAVs and fighter aircraft

    Energy Technology Data Exchange (ETDEWEB)

    Trahan, M.W.; Wagner, J.S.; Stantz, K.M.; Gray, P.C.; Robinett, R.

    1998-11-01

    This paper describes a method of modeling swarms of UAVs and/or fighter aircraft using particle simulation concepts. Recent investigations into the use of genetic algorithms to design neural networks for the control of autonomous vehicles (i.e., robots) led to the examination of methods of simulating large collections of robots. This paper describes the successful implementation of a model of swarm dynamics using particle simulation concepts. Several examples of the complex behaviors achieved in a target/interceptor scenario are presented.

  14. Swarm Optimization Methods in Microwave Imaging

    Directory of Open Access Journals (Sweden)

    Andrea Randazzo

    2012-01-01

    Full Text Available Swarm intelligence denotes a class of new stochastic algorithms inspired by the collective social behavior of natural entities (e.g., birds, ants, etc.. Such approaches have been proven to be quite effective in several applicative fields, ranging from intelligent routing to image processing. In the last years, they have also been successfully applied in electromagnetics, especially for antenna synthesis, component design, and microwave imaging. In this paper, the application of swarm optimization methods to microwave imaging is discussed, and some recent imaging approaches based on such methods are critically reviewed.

  15. Software Engineering and Swarm-Based Systems

    Science.gov (United States)

    Hinchey, Michael G.; Sterritt, Roy; Pena, Joaquin; Rouff, Christopher A.

    2006-01-01

    We discuss two software engineering aspects in the development of complex swarm-based systems. NASA researchers have been investigating various possible concept missions that would greatly advance future space exploration capabilities. The concept mission that we have focused on exploits the principles of autonomic computing as well as being based on the use of intelligent swarms, whereby a (potentially large) number of similar spacecraft collaborate to achieve mission goals. The intent is that such systems not only can be sent to explore remote and harsh environments but also are endowed with greater degrees of protection and longevity to achieve mission goals.

  16. Extracting distinct behaviors from laboratory insect swarms

    Science.gov (United States)

    Puckett, James; Ouellette, Nicholas

    2014-03-01

    Throughout nature, self-organized collective motion in animal groups produces rich and complex behaviors. Many modeling approaches have been proposed from continuum to discrete agent based models which are capable of emulating the behavior observed in flocks and swarms. Most models assume uniformity in the way individuals interact and discard differences between individuals and changes of behavior with time. While in many cases individual differences may average out in large groups of animals, this is not likely the case for small groups. By measuring trajectories and kinematics of individual Chironomids in laboratory mating swarms, we assess the dynamics of individual behavior and discuss the impact of our results on current models.

  17. Thermospheric neutral densities derived from Swarm accelerometer and GPS data

    DEFF Research Database (Denmark)

    Doornbos, Eelco; Encarnacao, Joao; van den IJss, Jose

    approach, affects the possibility of determining densities from the accelerometer measurements of the Swarm A and B satellites. We also investigate the possibility of determining crosswind speeds from Swarm data.In the meantime, we have investigated the possibility of deriving thermosphere neutral density...... data from the Swarm GPS observations only, with a much lower temporal resolution. We analyse the differences in the data between the three Swarm satellites as well as between the accelerometer-derived and GPS-only-derived densities for Swarm C....

  18. Identified EM Earthquake Precursors

    Science.gov (United States)

    Jones, Kenneth, II; Saxton, Patrick

    2014-05-01

    recurrence, duration, and frequency response. At the Southern California field sites, one loop antenna was positioned for omni-directional reception and also detected a strong First Schumann Resonance; however, additional Schumann Resonances were absent. At the Timpson, TX field sites, loop antennae were positioned for directional reception, due to earthquake-induced, hydraulic fracturing activity currently conducted by the oil and gas industry. Two strong signals, one moderately strong signal, and approximately 6-8 weaker signals were detected in the immediate vicinity. The three stronger signals were mapped by a biangulation technique, followed by a triangulation technique for confirmation. This was the first antenna mapping technique ever performed for determining possible earthquake epicenters. Six and a half months later, Timpson experienced two M4 (M4.1 and M4.3) earthquakes on September 2, 2013 followed by a M2.4 earthquake three days later, all occurring at a depth of five kilometers. The Timpson earthquake activity now has a cyclical rate and a forecast was given to the proper authorities. As a result, the Southern California and Timpson, TX field results led to an improved design and construction of a third prototype antenna. With a loop antenna array, a viable communication system, and continuous monitoring, a full fracture cycle can be established and observed in real-time. In addition, field data could be reviewed quickly for assessment and lead to a much more improved earthquake forecasting capability. The EM precursors determined by this method appear to surpass all prior precursor claims, and the general public will finally receive long overdue forecasting.

  19. Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

    Science.gov (United States)

    Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

    2013-01-01

    The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

  20. Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

    Science.gov (United States)

    Niu, Ben; Huang, Huali; Tan, Lijing; Duan, Qiqi

    2017-01-01

    Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position including the experience of internal and external multiple swarms, is used to keep the diversity of the population. Two different levels of social interaction within and between multiple swarms are proposed. In the search process, particles not only exchange social experience with others that are from their own sub-swarms, but also are influenced by the experience of particles from other fellow sub-swarms. According to the different exemplars and learning strategy, this model is instantiated as four variants of SALMPSO and a set of 15 test functions are conducted to compare with some variants of PSO including 10, 30 and 50 dimensions, respectively. Experimental results demonstrate that the alternative learning strategy in each SALMPSO version can exhibit better performance in terms of the convergence speed and optimal values on most multimodal functions in our simulation.

  1. Role of tumbling in bacterial swarming

    Science.gov (United States)

    Sidortsov, Marina; Morgenstern, Yakov; Be'er, Avraham

    2017-08-01

    Typical wild-type bacteria swimming in sparse suspensions exhibit a movement pattern called "run and tumble," characterized by straight trajectories (runs) interspersed by shorter, random reorientation (tumbles). This is achieved by rotating their flagella counterclockwise, or clockwise, respectively. The chemotaxis signaling network operates in controlling the frequency of tumbles, enabling navigation toward or away from desired regions in the medium. In contrast, while in dense populations, flagellated bacteria exhibit collective motion and form large dynamic clusters, whirls, and jets, with intricate dynamics that is fundamentally different than trajectories of sparsely swimming cells. Although collectively swarming cells do change direction at the level of the individual cell, often exhibiting reversals, it has been suggested that chemotaxis does not play a role in multicellular colony expansion, but the change in direction stems from clockwise flagellar rotation. In this paper, the effects of cell rotor switching (i.e., the ability to tumble) and chemotaxis on the collective statistics of swarming bacteria are studied experimentally in wild-type Bacillus subtilis and two mutants—one that does not tumble and one that tumbles independently of the chemotaxis system. We show that while several of the parameters examined are similar between the strains, other collective and individual characteristics are significantly different. The results demonstrate that tumbling and/or flagellar directional rotor switching has an important role on the dynamics of swarming, and imply that swarming models of self-propelled rods that do not take tumbling and/or rotor switching into account may be oversimplified.

  2. Swarm Level 2 Comprehensive Inversion, 2016 Production

    DEFF Research Database (Denmark)

    Tøffner-Clausen, Lars; Sabaka, Terence; Olsen, Nils

    In the framework of the ESA Earth Observation Magnetic Mapping Mission Swarm, the Expert Support Laboratories (ESL) provides high quality Level 2 Products describing a.o. the magnetic fields of the Earth. This poster provides details of the Level 2 Products from the Comprehensive Inversion chain...

  3. Novelty-driven Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Galvao, Diana; Lehman, Joel Anthony; Urbano, Paulo

    2015-01-01

    Particle Swarm Optimization (PSO) is a well-known population-based optimization algorithm. Most often it is applied to optimize objective-based fitness functions that reward progress towards a desired objective or behavior. As a result, search increasingly focuses on higher-fitness areas. However...

  4. Selectively-informed particle swarm optimization.

    Science.gov (United States)

    Gao, Yang; Du, Wenbo; Yan, Gang

    2015-03-19

    Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems. In the original PSO and most of its variants all particles are treated equally, overlooking the impact of structural heterogeneity on individual behavior. Here we employ complex networks to represent the population structure of swarms and propose a selectively-informed PSO (SIPSO), in which the particles choose different learning strategies based on their connections: a densely-connected hub particle gets full information from all of its neighbors while a non-hub particle with few connections can only follow a single yet best-performed neighbor. Extensive numerical experiments on widely-used benchmark functions show that our SIPSO algorithm remarkably outperforms the PSO and its existing variants in success rate, solution quality, and convergence speed. We also explore the evolution process from a microscopic point of view, leading to the discovery of different roles that the particles play in optimization. The hub particles guide the optimization process towards correct directions while the non-hub particles maintain the necessary population diversity, resulting in the optimum overall performance of SIPSO. These findings deepen our understanding of swarm intelligence and may shed light on the underlying mechanism of information exchange in natural swarm and flocking behaviors.

  5. Swarm controlled emergence for ant clustering

    DEFF Research Database (Denmark)

    Scheidler, Alexander; Merkle, Daniel; Middendorf, Martin

    2013-01-01

    implications: The particular finding, that certain behaviours of control agents can lead to stronger clustering, can help to design improved clustering algorithms by using heterogeneous swarms of agents. Originality/value: In general, the control of (unwanted) emergent effects in artificial systems...

  6. A Comparison of Selected Modifications of the Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Michala Jakubcová

    2014-01-01

    Full Text Available We compare 27 modifications of the original particle swarm optimization (PSO algorithm. The analysis evaluated nine basic PSO types, which differ according to the swarm evolution as controlled by various inertia weights and constriction factor. Each of the basic PSO modifications was analyzed using three different distributed strategies. In the first strategy, the entire swarm population is considered as one unit (OC-PSO, the second strategy periodically partitions the population into equally large complexes according to the particle’s functional value (SCE-PSO, and the final strategy periodically splits the swarm population into complexes using random permutation (SCERand-PSO. All variants are tested using 11 benchmark functions that were prepared for the special session on real-parameter optimization of CEC 2005. It was found that the best modification of the PSO algorithm is a variant with adaptive inertia weight. The best distribution strategy is SCE-PSO, which gives better results than do OC-PSO and SCERand-PSO for seven functions. The sphere function showed no significant difference between SCE-PSO and SCERand-PSO. It follows that a shuffling mechanism improves the optimization process.

  7. Determination of Spatial Configuration of an Underwater Swarm with Minimum Data

    Directory of Open Access Journals (Sweden)

    Ramiro dell'Erba

    2015-07-01

    Full Text Available This paper is the extension of work presented at the IARP Conference “Bio inspired robotics” held in Frascati (Italy, 14 May 2014. The subject is the localization problem of an underwater swarm of autonomous underwater robots (AUV, in the frame of the HARNESS project; by localization, we mean the relative swarm configuration, i.e., the geometrical shape of the group. The result is achieved by using the signals that the robots exchange. The swarm is organized by rules and conceived to perform tasks, ranging from environmental monitoring to terrorism-attack surveillance. Two methods of determining the shape of the swarm, both based on trilateration calculation, are proposed. The first method focuses on the robot's speed. In this case, we use our knowledge of the speeds and distances between the machines, while the second method considers only distances and the orientation angles of the robots. Unlike a trilateration problem, we do not know the position of the beacons and this renders the problem a difficult one. Moreover, we have very few data. More than one step of motion is needed to resolve the multiple solutions found, owing to the symmetries of the system and optimization process of one or more objective functions leading to the final configuration. We subsequently checked our algorithm using a simulator taking into account random errors affecting the measurements.

  8. Recurrent slow slip event likely hastened by the 2011 Tohoku earthquake

    Science.gov (United States)

    Hirose, Hitoshi; Kimura, Hisanori; Enescu, Bogdan; Aoi, Shin

    2012-01-01

    Slow slip events (SSEs) are another mode of fault deformation than the fast faulting of regular earthquakes. Such transient episodes have been observed at plate boundaries in a number of subduction zones around the globe. The SSEs near the Boso Peninsula, central Japan, are among the most documented SSEs, with the longest repeating history, of almost 30 y, and have a recurrence interval of 5 to 7 y. A remarkable characteristic of the slow slip episodes is the accompanying earthquake swarm activity. Our stable, long-term seismic observations enable us to detect SSEs using the recorded earthquake catalog, by considering an earthquake swarm as a proxy for a slow slip episode. Six recurrent episodes are identified in this way since 1982. The average duration of the SSE interoccurrence interval is 68 mo; however, there are significant fluctuations from this mean. While a regular cycle can be explained using a simple physical model, the mechanisms that are responsible for the observed fluctuations are poorly known. Here we show that the latest SSE in the Boso Peninsula was likely hastened by the stress transfer from the March 11, 2011 great Tohoku earthquake. Moreover, a similar mechanism accounts for the delay of an SSE in 1990 by a nearby earthquake. The low stress buildups and drops during the SSE cycle can explain the strong sensitivity of these SSEs to stress transfer from external sources. PMID:22949688

  9. A Triangle Mesh Standardization Method Based on Particle Swarm Optimization.

    Science.gov (United States)

    Wang, Wuli; Duan, Liming; Bai, Yang; Wang, Haoyu; Shao, Hui; Zhong, Siyang

    2016-01-01

    To enhance the triangle quality of a reconstructed triangle mesh, a novel triangle mesh standardization method based on particle swarm optimization (PSO) is proposed. First, each vertex of the mesh and its first order vertices are fitted to a cubic curve surface by using least square method. Additionally, based on the condition that the local fitted surface is the searching region of PSO and the best average quality of the local triangles is the goal, the vertex position of the mesh is regulated. Finally, the threshold of the normal angle between the original vertex and regulated vertex is used to determine whether the vertex needs to be adjusted to preserve the detailed features of the mesh. Compared with existing methods, experimental results show that the proposed method can effectively improve the triangle quality of the mesh while preserving the geometric features and details of the original mesh.

  10. Order-2 Stability Analysis of Particle Swarm Optimization.

    Science.gov (United States)

    Liu, Qunfeng

    2015-01-01

    Several stability analyses and stable regions of particle swarm optimization (PSO) have been proposed before. The assumption of stagnation and different definitions of stability are adopted in these analyses. In this paper, the order-2 stability of PSO is analyzed based on a weak stagnation assumption. A new definition of stability is proposed and an order-2 stable region is obtained. Several existing stable analyses for canonical PSO are compared, especially their definitions of stability and the corresponding stable regions. It is shown that the classical stagnation assumption is too strict and not necessary. Moreover, among all these definitions of stability, it is shown that our definition requires the weakest conditions, and additional conditions bring no benefit. Finally, numerical experiments are reported to show that the obtained stable region is meaningful. A new parameter combination of PSO is also shown to be good, even better than some known best parameter combinations.

  11. Tohoku earthquake: a surprise?

    CERN Document Server

    Kagan, Yan Y

    2011-01-01

    We consider three issues related to the 2011 Tohoku mega-earthquake: (1) how to evaluate the earthquake maximum size in subduction zones, (2) what is the repeat time for the largest earthquakes in Tohoku area, and (3) what are the possibilities of short-term forecasts during the 2011 sequence. There are two quantitative methods which can be applied to estimate the maximum earthquake size: a statistical analysis of the available earthquake record and the moment conservation principle. The latter technique studies how much of the tectonic deformation rate is released by earthquakes. For the subduction zones, the seismic or historical record is not sufficient to provide a reliable statistical measure of the maximum earthquake. The moment conservation principle yields consistent estimates of maximum earthquake size: for all the subduction zones the magnitude is of the order 9.0--9.7, and for major subduction zones the maximum earthquake size is statistically indistinguishable. Starting in 1999 we have carried out...

  12. Power Enhancement of Weightlifters during Snatch through Reducing Torque on Joints by Particle Swarm Optimization

    OpenAIRE

    Firooz Salaami; Nima Jamshidi; Mostafa Rostami; Siamak Najarian

    2008-01-01

    In this research, an athlete's body on sagittal plane in tension phase of snatch weightlifting has been modeled in two dimensions for calculating the generated torques in joints. The error back propagation multi-layer perceptrons has been used for modeling the torque through changing the angular velocity, angular acceleration and absolute angle of each segment. Finally, the torque in joints has been minimized by particle swarm optimization technique and the power of athlete has been maximized...

  13. Insight into the Earthquake Risk Information Seeking Behavior of the Victims: Evidence from Songyuan, China

    Directory of Open Access Journals (Sweden)

    Shasha Li

    2017-03-01

    Full Text Available Efficient risk communication is a vital way to reduce the vulnerability of individuals when facing emergency risks, especially regarding earthquakes. Efficient risk communication aims at improving the supply of risk information and fulfilling the need for risk information by individuals. Therefore, an investigation into individual-level information seeking behavior within earthquake risk contexts is very important for improved earthquake risk communication. However, at present there are very few studies that have explored the behavior of individuals seeking earthquake risk information. Under the guidance of the Risk Information Seeking and Processing model as well as relevant practical findings using the structural equation model, this study attempts to explore the main determinants of an individual’s earthquake risk information seeking behavior, and to validate the mediator effect of information need during the seeking process. A questionnaire-based survey of 918 valid respondents in Songyuan, China, who had been hit by a small earthquake swarm, was used to provide practical evidence for this study. Results indicated that information need played a noteworthy role in the earthquake risk information seeking process, and was detected both as an immediate predictor and as a mediator. Informational subjective norms drive the seeking behavior on earthquake risk information through both direct and indirect approaches. Perceived information gathering capacity, negative affective responses and risk perception have an indirect effect on earthquake risk information seeking behavior via information need. The implications for theory and practice regarding risk communication are discussed and concluded.

  14. Insight into the Earthquake Risk Information Seeking Behavior of the Victims: Evidence from Songyuan, China.

    Science.gov (United States)

    Li, Shasha; Zhai, Guofang; Zhou, Shutian; Fan, Chenjing; Wu, Yunqing; Ren, Chongqiang

    2017-03-07

    Efficient risk communication is a vital way to reduce the vulnerability of individuals when facing emergency risks, especially regarding earthquakes. Efficient risk communication aims at improving the supply of risk information and fulfilling the need for risk information by individuals. Therefore, an investigation into individual-level information seeking behavior within earthquake risk contexts is very important for improved earthquake risk communication. However, at present there are very few studies that have explored the behavior of individuals seeking earthquake risk information. Under the guidance of the Risk Information Seeking and Processing model as well as relevant practical findings using the structural equation model, this study attempts to explore the main determinants of an individual's earthquake risk information seeking behavior, and to validate the mediator effect of information need during the seeking process. A questionnaire-based survey of 918 valid respondents in Songyuan, China, who had been hit by a small earthquake swarm, was used to provide practical evidence for this study. Results indicated that information need played a noteworthy role in the earthquake risk information seeking process, and was detected both as an immediate predictor and as a mediator. Informational subjective norms drive the seeking behavior on earthquake risk information through both direct and indirect approaches. Perceived information gathering capacity, negative affective responses and risk perception have an indirect effect on earthquake risk information seeking behavior via information need. The implications for theory and practice regarding risk communication are discussed and concluded.

  15. Insight into the Earthquake Risk Information Seeking Behavior of the Victims: Evidence from Songyuan, China

    Science.gov (United States)

    Li, Shasha; Zhai, Guofang; Zhou, Shutian; Fan, Chenjing; Wu, Yunqing; Ren, Chongqiang

    2017-01-01

    Efficient risk communication is a vital way to reduce the vulnerability of individuals when facing emergency risks, especially regarding earthquakes. Efficient risk communication aims at improving the supply of risk information and fulfilling the need for risk information by individuals. Therefore, an investigation into individual-level information seeking behavior within earthquake risk contexts is very important for improved earthquake risk communication. However, at present there are very few studies that have explored the behavior of individuals seeking earthquake risk information. Under the guidance of the Risk Information Seeking and Processing model as well as relevant practical findings using the structural equation model, this study attempts to explore the main determinants of an individual’s earthquake risk information seeking behavior, and to validate the mediator effect of information need during the seeking process. A questionnaire-based survey of 918 valid respondents in Songyuan, China, who had been hit by a small earthquake swarm, was used to provide practical evidence for this study. Results indicated that information need played a noteworthy role in the earthquake risk information seeking process, and was detected both as an immediate predictor and as a mediator. Informational subjective norms drive the seeking behavior on earthquake risk information through both direct and indirect approaches. Perceived information gathering capacity, negative affective responses and risk perception have an indirect effect on earthquake risk information seeking behavior via information need. The implications for theory and practice regarding risk communication are discussed and concluded. PMID:28272359

  16. Seismotectonic significance of the 2008–2010 Walloon Brabant seismic swarm in the Brabant Massif, Belgium

    Science.gov (United States)

    Van Noten, Koen; Lecocq, Thomas; Shah, Anjana K.; Camelbeeck, Thierry

    2015-01-01

    Between 12 July 2008 and 18 January 2010 a seismic swarm occurred close to the town of Court-Saint-Etienne, 20 km SE of Brussels (Belgium). The Belgian network and a temporary seismic network covering the epicentral area established a seismic catalogue in which magnitude varies between ML -0.7 and ML 3.2. Based on waveform cross-correlation of co-located earthquakes, the spatial distribution of the hypocentre locations was improved considerably and shows a dense cluster displaying a 200 m-wide, 1.5-km long, NW-SE oriented fault structure at a depth range between 5 and 7 km, located in the Cambrian basement rocks of the Lower Palaeozoic Anglo-Brabant Massif. Waveform comparison of the largest events of the 2008–2010 swarm with an ML 4.0 event that occurred during swarm activity between 1953 and 1957 in the same region shows similar P- and S-wave arrivals at the Belgian Uccle seismic station. The geometry depicted by the hypocentral distribution is consistent with a nearly vertical, left-lateral strike-slip fault taking place in a current local WNW–ESE oriented local maximum horizontal stress field. To determine a relevant tectonic structure, a systematic matched filtering approach of aeromagnetic data, which can approximately locate isolated anomalies associated with hypocentral depths, has been applied. Matched filtering shows that the 2008–2010 seismic swarm occurred along a limited-sized fault which is situated in slaty, low-magnetic rocks of the Mousty Formation. The fault is bordered at both ends with obliquely oriented magnetic gradients. Whereas the NW end of the fault is structurally controlled, its SE end is controlled by a magnetic gradient representing an early-orogenic detachment fault separating the low-magnetic slaty Mousty Formation from the high-magnetic Tubize Formation. The seismic swarm is therefore interpreted as a sinistral reactivation of an inherited NW–SE oriented isolated fault in a weakened crust within the Cambrian core of

  17. Glowworm swarm optimization theory, algorithms, and applications

    CERN Document Server

    Kaipa, Krishnanand N

    2017-01-01

    This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intellige...

  18. A comprehensive review of swarm optimization algorithms.

    Directory of Open Access Journals (Sweden)

    Mohd Nadhir Ab Wahab

    Full Text Available Many swarm optimization algorithms have been introduced since the early 60's, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE and is closely followed by Particle Swarm Optimization (PSO, compared with other considered approaches.

  19. A comprehensive review of swarm optimization algorithms.

    Science.gov (United States)

    Ab Wahab, Mohd Nadhir; Nefti-Meziani, Samia; Atyabi, Adham

    2015-01-01

    Many swarm optimization algorithms have been introduced since the early 60's, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches.

  20. Macroscopic definition of distributed swarm morphogenesis

    Science.gov (United States)

    Aznar, Fidel; Pujol, Mar; Rizo, Ramón

    2012-12-01

    In this paper, we present a system that will be able to obtain microscopic assembly behaviours for a robotic swarm to achieve an assembly target (macroscopic model). It will be designed taking into consideration the essential features of a self-assembling system needed to be implemented in a real robotic swarm. This system is composed of a typology of generative languages PD0L, and an algorithm for generating individual rules to be processed by the robots. The assembly process will be performed in a distributed manner, and will be also designed to require minimal communication capabilities between robots. Both the expressive capacities of language and the rule generation algorithm will be demonstrated by evaluating their performance with a core set of test morphologies widely used in self-assembly tasks. Furthermore, we compare the assembly time and the number of messages required between a classic controller (centralised) and our distributed approach.

  1. Thermoregulation and adaptation in honeybee swarms

    Science.gov (United States)

    Ocko, Samuel; Mahadevan, L.

    2012-11-01

    Swarming is an essential part of honeybee behavior, wherein thousands of bees cling onto each other to form a dense cluster that is exposed to the environment for up to several days. This cluster has the ability to maintain its core temperature actively without a central controller raising the question of mechanism. Inspired by experimental observations, we treat the swarm cluster as an active porous structure with a variable metabolism that needs to adjust to outside conditions to control heat loss and regulate its core temperature. Using a continuum model that takes the form of a set of advection-diffusion equations for heat transfer in a mobile porous medium, we show that effective thermoregulation can result from the collective behavior of individual bees in the cluster.

  2. Preliminary Results of the 2013 - 2014 Sabancaya, Peru Earthquakes from COSMO-Skymed Satellite Constellation InSAR Time-Series

    Science.gov (United States)

    Milillo, P.; Lundgren, P.; Jolivet, R.; Simons, M.

    2014-12-01

    We examine an earthquake series in southern Peru that features a complex interaction of main- and after-shocks located in an active volcanic zone. The earthquakes started with the 17 July 2013 Mw 5.9 and 24 July 2013 Mw 4.0 earthquakes north-west 20 km NW of active Sabancaya volcano in the Andean Central volcanic Zone of Peru. During this time interval Sabancaya volcano experienced a strong seismic swarm, fumarole activity and earthquakes possibly related to fracturing of rock and fluid movements.We analyze satellite InSAR data from the Italian Space Agency (ASI) COSMO-SkyMed (CSK) constellation and airborne InSAR data from the NASA UAVSAR. CSK provides a dense InSAR time series that track deformation from 2013 through 2014. Thanks to the short repeat interval of the CSK constellation we are able to discriminate between different earthquakes, aftershocks and post seismic processes leading to a better constraint of the sources. The initial coseismic interferograms from CSK provide a stunningly detailed image of the fault deformation, due in part to the high resolution, short wavelength (3.1 cm) of CSK, and the high coherence, and high elevation of the location. For such a relatively small earthquake there is significant shallow fault complexity and surface breaks evident. We found that post-seismic deformation starts immediately following the 17 July main event and is still ongoing. The post seismic deformation measured by the CSK InSAR time series shows a logarithmic time dependency for the southern part of the fault involved in the July 17 earthquake. Using a non-linear least squares approach we found a characteristic time constant of ~0.5 years. We found complex co-seismic and persistent post seismic deformation northeast of Sabancaya volcano possibly related to the complex fault system. To model the coseismic fault geometry and fault slip distribution we use a Bayesian method to solve for the basic fault geometry. This model forms the basis for a detailed

  3. Particle Swarm Optimization as an Efficient Computational Method in order to Minimize Vibrations of Multimesh Gears Transmission

    Directory of Open Access Journals (Sweden)

    Alexandre Carbonelli

    2011-01-01

    Full Text Available The aim of this work is to present the great performance of the numerical algorithm of Particle Swarm Optimization applied to find the best teeth modifications for multimesh helical gears, which are crucial for the static transmission error (STE. Indeed, STE fluctuation is the main source of vibrations and noise radiated by the geared transmission system. The microgeometrical parameters studied for each toothed wheel are the crowning, tip reliefs and start diameters for these reliefs. Minimization of added up STE amplitudes on the idler gear of a three-gear cascade is then performed using the Particle Swarm Optimization. Finally, robustness of the solutions towards manufacturing errors and applied torque is analyzed by the Particle Swarm algorithm to access to the deterioration capacity of the tested solution.

  4. A Game Theoretic Approach to Swarm Robotics

    Directory of Open Access Journals (Sweden)

    S. N. Givigi

    2006-01-01

    Full Text Available In this article, we discuss some techniques for achieving swarm intelligent robots through the use of traits of personality. Traits of personality are characteristics of each robot that, altogether, define the robot's behaviours. We discuss the use of evolutionary psychology to select a set of traits of personality that will evolve due to a learning process based on reinforcement learning. The use of Game Theory is introduced, and some simulations showing its potential are reported.

  5. Countering A2/AD with Swarming

    Science.gov (United States)

    2016-04-01

    inferior force can deny or delay a decisive engagement through time or attrition ultimately changing the political calculus.6 Using chess as an...deterrence in a non-nuclear scenario. Conventional deterrence is largely based on perceptions . Creating the wrong perception can cause conventional...necessarily defeat an enemy’s A2/AD strategy. Rather, the swarm needs to only create a perception that the U.S. is willing to fight within the A2/AD

  6. Two Invariants of Human-Swarm Interaction

    Science.gov (United States)

    2018-01-16

    often have formal attractors such as nest selection (Nevai & Passino, 2010) and many of the collective animal behaviors described by Sumpter (Sumpter...can be used to design swarm systems with desired fan-outs and workloads in mind . The key reason this is possible is that we are managing attractors...E., Giardina, I., et al. (2008). Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a

  7. Survey of Methods and Algorithms of Robot Swarm Aggregation

    Science.gov (United States)

    E Shlyakhov, N.; Vatamaniuk, I. V.; Ronzhin, A. L.

    2017-01-01

    The paper considers the problem of swarm aggregation of autonomous robots with the use of three methods based on the analogy of the behavior of biological objects. The algorithms substantiating the requirements for hardware realization of sensor, computer and network resources and propulsion devices are presented. Techniques for efficiency estimation of swarm aggregation via space-time characteristics are described. The developed model of the robot swarm reconfiguration into a predetermined three-dimensional shape is presented.

  8. POLICE OFFICE MODEL IMPROVEMENT FOR SECURITY OF SWARM ROBOTIC SYSTEMS

    OpenAIRE

    I. A. Zikratov; A. V. Gurtov; T. V. Zikratova; Kozlova, E. V.

    2014-01-01

    This paper focuses on aspects of information security for group of mobile robotic systems with swarm intellect. The ways for hidden attacks realization by the opposing party on swarm algorithm are discussed. We have fulfilled numerical modeling of potentially destructive information influence on the ant shortest path algorithm. We have demonstrated the consequences of attacks on the ant algorithm with different concentration in a swarm of subversive robots. Approaches are suggested for inform...

  9. INHIBITION OF SWARMING BY UREA AND ITS DIAGNOSTIC ...

    African Journals Online (AJOL)

    The anti-swarming property of urea and effects on antibiotic susceptibility among 52 uropathogenic Proteus strains from Lagos, Nigeria were investigated. Urea caused a reduction in swarming and number of swarmed cells at 0.5% (n = 42, DOCZ = 15.5mm), 0.75% (n= 24, DOCZ = 10.7mm), 1% (n = 17, DOCZ = 3.4mm) and ...

  10. A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

    Science.gov (United States)

    Sun, Tao; Xu, Ming-Hai

    2017-01-01

    Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

  11. Earthquakes: hydrogeochemical precursors

    Science.gov (United States)

    Ingebritsen, Steven E.; Manga, Michael

    2014-01-01

    Earthquake prediction is a long-sought goal. Changes in groundwater chemistry before earthquakes in Iceland highlight a potential hydrogeochemical precursor, but such signals must be evaluated in the context of long-term, multiparametric data sets.

  12. Earthquake Damage - General

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An earthquake is the motion or trembling of the ground produced by sudden displacement of rock in the Earth's crust. Earthquakes result from crustal strain,...

  13. Earthquakes in Southern California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — There have been many earthquake occurrences in Southern California. This set of slides shows earthquake damage from the following events: Imperial Valley, 1979,...

  14. Earthquake Notification Service

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Earthquake Notification Service (ENS) is a free service that sends you automated notifications to your email or cell phone when earthquakes happen.

  15. Collective motion of a class of social foraging swarms

    Energy Technology Data Exchange (ETDEWEB)

    Liu Bo [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: boliu@mech.pku.edu.cn; Chu Tianguang [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: chutg@pku.edu.cn; Wang Long; Wang Zhanfeng [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)

    2008-10-15

    This paper considers a class of social foraging swarms with a nutrient profile (or an attractant/repellent) and an attraction-repulsion coupling function, which is chosen to guarantee collision avoidance between individuals. The paper also studies non-identical interaction ability or efficiency among different swarm individuals for different profiles. The swarm behavior is a result of a balance between inter-individual interplays as well as the interplays of the swarm individuals (agents) with their environment. It is proved that the individuals of a quasi-reciprocal swarm will aggregate and eventually form a cohesive cluster of finite size for different profiles. It is also shown that the swarm system is completely stable, that is, every solution converges to the set of equilibrium points of the system. Moreover, all the swarm individuals will converge to more favorable areas of the profile under certain conditions. For general non-reciprocal swarms, numerical simulations show that more complex self-organized rotation may occur in the swarms.

  16. Swarming behaviour and mass occurrences in the world's largest ...

    African Journals Online (AJOL)

    millipede species, Zoosphaerium neptunus, on Madagascar and its implication for conservation efforts (Diplopoda: Sphaerotheriida) ... Madagascar Conservation & Development ... KEY WORDS: Swarming behaviour, millipede, island gigantism.

  17. A detailed analysis of some local earthquakes at Somma-Vesuvius

    Directory of Open Access Journals (Sweden)

    C. Troise

    1999-06-01

    Full Text Available In this paper, we analyze local earthquakes which occurred at Somma-Vesuvius during two episodes of intense seismic swarms, in 1989 and 1995 respectively. For the selected earthquakes we have computed accurate hypocentral locations, focal mechanisms and spectral parameters. We have also studied the ground acceleration produced by the largest events of the sequences (ML 3.0, at various digital stations installed in the area during the periods of higher seismic activity. The main result is that seismicity during the two swarm episodes presents similar features in both locations and focal mechanisms. Strong site dependent effects are evidenced in the seismic radiation and strong amplifications in the frequency band 10-15 Hz are evident at stations located on the younger Vesuvius structure, with respect to one located on the ancient Somma structure. Furthermore, seismic stations show peak accelerations for the same events of more than one order of magnitude apart.

  18. Testing hypotheses of earthquake occurrence

    Science.gov (United States)

    Kagan, Y. Y.; Jackson, D. D.; Schorlemmer, D.; Gerstenberger, M.

    2003-12-01

    We present a relatively straightforward likelihood method for testing those earthquake hypotheses that can be stated as vectors of earthquake rate density in defined bins of area, magnitude, and time. We illustrate the method as it will be applied to the Regional Earthquake Likelihood Models (RELM) project of the Southern California Earthquake Center (SCEC). Several earthquake forecast models are being developed as part of this project, and additional contributed forecasts are welcome. Various models are based on fault geometry and slip rates, seismicity, geodetic strain, and stress interactions. We would test models in pairs, requiring that both forecasts in a pair be defined over the same set of bins. Thus we offer a standard "menu" of bins and ground rules to encourage standardization. One menu category includes five-year forecasts of magnitude 5.0 and larger. Forecasts would be in the form of a vector of yearly earthquake rates on a 0.05 degree grid at the beginning of the test. Focal mechanism forecasts, when available, would be also be archived and used in the tests. The five-year forecast category may be appropriate for testing hypotheses of stress shadows from large earthquakes. Interim progress will be evaluated yearly, but final conclusions would be made on the basis of cumulative five-year performance. The second category includes forecasts of earthquakes above magnitude 4.0 on a 0.05 degree grid, evaluated and renewed daily. Final evaluation would be based on cumulative performance over five years. Other types of forecasts with different magnitude, space, and time sampling are welcome and will be tested against other models with shared characteristics. All earthquakes would be counted, and no attempt made to separate foreshocks, main shocks, and aftershocks. Earthquakes would be considered as point sources located at the hypocenter. For each pair of forecasts, we plan to compute alpha, the probability that the first would be wrongly rejected in favor of

  19. Characterization and Modeling of Insect Swarms Using tools from Fluid Dynamics

    Science.gov (United States)

    2016-09-01

    quantitatively measuring the flight trajectories of swarming insects and to use the resulting data to evaluate currently used models of collective...for quantitatively measuring the flight trajectories of swarming insects and to use the resulting data to evaluate currently used models of...exception was the introduction of a ground-based “swarm marker” to encourage swarm nucleation and to place the swarm in a convenient location. Once swarms

  20. Redefining Earthquakes and the Earthquake Machine

    Science.gov (United States)

    Hubenthal, Michael; Braile, Larry; Taber, John

    2008-01-01

    The Earthquake Machine (EML), a mechanical model of stick-slip fault systems, can increase student engagement and facilitate opportunities to participate in the scientific process. This article introduces the EML model and an activity that challenges ninth-grade students' misconceptions about earthquakes. The activity emphasizes the role of models…

  1. Children's Ideas about Earthquakes

    Science.gov (United States)

    Simsek, Canan Lacin

    2007-01-01

    Earthquake, a natural disaster, is among the fundamental problems of many countries. If people know how to protect themselves from earthquake and arrange their life styles in compliance with this, damage they will suffer will reduce to that extent. In particular, a good training regarding earthquake to be received in primary schools is considered…

  2. Induced earthquakes. Sharp increase in central Oklahoma seismicity since 2008 induced by massive wastewater injection.

    Science.gov (United States)

    Keranen, K M; Weingarten, M; Abers, G A; Bekins, B A; Ge, S

    2014-07-25

    Unconventional oil and gas production provides a rapidly growing energy source; however, high-production states in the United States, such as Oklahoma, face sharply rising numbers of earthquakes. Subsurface pressure data required to unequivocally link earthquakes to wastewater injection are rarely accessible. Here we use seismicity and hydrogeological models to show that fluid migration from high-rate disposal wells in Oklahoma is potentially responsible for the largest swarm. Earthquake hypocenters occur within disposal formations and upper basement, between 2- and 5-kilometer depth. The modeled fluid pressure perturbation propagates throughout the same depth range and tracks earthquakes to distances of 35 kilometers, with a triggering threshold of ~0.07 megapascals. Although thousands of disposal wells operate aseismically, four of the highest-rate wells are capable of inducing 20% of 2008 to 2013 central U.S. seismicity. Copyright © 2014, American Association for the Advancement of Science.

  3. Mapping of earthquakes vulnerability area in Papua

    Science.gov (United States)

    Muhammad Fawzy Ismullah, M.; Massinai, Muh. Altin

    2016-05-01

    Geohazard is a geological occurrence which may lead to a huge loss for human. A mitigation of these natural disasters is one important thing to be done properly in order to reduce the risks. One of the natural disasters that frequently occurs in the Papua Province is the earthquake. This study applies the principle of Geospatial and its application for mapping the earthquake-prone area in the Papua region. It uses earthquake data, which is recorded for 36 years (1973-2009), fault location map, and ground acceleration map of the area. The earthquakes and fault map are rearranged into an earthquake density map, as well as an earthquake depth density map and fault density map. The overlaid data of these three maps onto ground acceleration map are then (compiled) to obtain an earthquake unit map. Some districts area, such as Sarmi, Nabire, and Dogiyai, are identified by a high vulnerability index. In the other hand, Waropen, Puncak, Merauke, Asmat, Mappi, and Bouven Digoel area shows lower index. Finally, the vulnerability index in other places is detected as moderate.

  4. Joint global optimization of tomographic data based on particle swarm optimization and decision theory

    Science.gov (United States)

    Paasche, H.; Tronicke, J.

    2012-04-01

    In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto

  5. Magma Supply System at Batur Volcano Inferred from Volcano-Tectonic Earthquakes and Their Focal Mechanism

    Directory of Open Access Journals (Sweden)

    Sri Hidayati

    2014-07-01

    Full Text Available DOI: 10.17014/ijog.v8i2.159The Volcano-Tectonic (VT earthquakes occurring during September - November 2009 were analyzed. The result shows that the epicentres aligning in NE- SW direction coincided with the weak zone of Batur Volcano Complex. The focal zone is located at the depth around 1.5 - 5.5 km beneath the summit. Migration of magma was detected by ground deformation measured by GPS and focal mechanism. Mechanism of VT earthquake shows mostly normal fault types during the swarm in November 2009.

  6. Multi-objective particle swarm optimization using Pareto-based set and aggregation approach

    Science.gov (United States)

    Huang, Song; Wang, Yan; Ji, Zhicheng

    2017-07-01

    Multi-objective optimization problems (MOPs) need to be solved in real world recently. In this paper, a multi-objective particle swarm optimization based on Pareto set and aggregation approach was proposed to deal with MOPs. Firstly, velocities and positions were updated similar to PSO. Then, global-best set was defined in particle swarm optimizer to preserve Pareto-based set obtained by the population. Specifically, a hybrid updating strategy based on Pareto set and aggregation approach was introduced to update the global-best set and local search was carried on global-best set. Thirdly, personal-best positions were updated in decomposition way, and global-best position was selected from global-best set. Finally, ZDT instances and DTLZ instances were selected to evaluate the performance of MULPSO and the results show validity of the proposed algorithm for MOPs.

  7. A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

    Science.gov (United States)

    Ni, Qingjian; Pan, Qianqian; Du, Huimin; Cao, Cen; Zhai, Yuqing

    2017-01-01

    An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.

  8. The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

    Science.gov (United States)

    Han, Gaining; Fu, Weiping; Wang, Wen

    2016-01-01

    In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

  9. Application of Earthquake Subspace Detectors at Kilauea and Mauna Loa Volcanoes, Hawai`i

    Science.gov (United States)

    Okubo, P.; Benz, H.; Yeck, W.

    2016-12-01

    Recent studies have demonstrated the capabilities of earthquake subspace detectors for detailed cataloging and tracking of seismicity in a number of regions and settings. We are exploring the application of subspace detectors at the United States Geological Survey's Hawaiian Volcano Observatory (HVO) to analyze seismicity at Kilauea and Mauna Loa volcanoes. Elevated levels of microseismicity and occasional swarms of earthquakes associated with active volcanism here present cataloging challenges due the sheer numbers of earthquakes and an intrinsically low signal-to-noise environment featuring oceanic microseism and volcanic tremor in the ambient seismic background. With high-quality continuous recording of seismic data at HVO, we apply subspace detectors (Harris and Dodge, 2011, Bull. Seismol. Soc. Am., doi: 10.1785/0120100103) during intervals of noteworthy seismicity. Waveform templates are drawn from Magnitude 2 and larger earthquakes within clusters of earthquakes cataloged in the HVO seismic database. At Kilauea, we focus on seismic swarms in the summit caldera region where, despite continuing eruptions from vents in the summit region and in the east rift zone, geodetic measurements reflect a relatively inflated volcanic state. We also focus on seismicity beneath and adjacent to Mauna Loa's summit caldera that appears to be associated with geodetic expressions of gradual volcanic inflation, and where precursory seismicity clustered prior to both Mauna Loa's most recent eruptions in 1975 and 1984. We recover several times more earthquakes with the subspace detectors - down to roughly 2 magnitude units below the templates, based on relative amplitudes - compared to the numbers of cataloged earthquakes. The increased numbers of detected earthquakes in these clusters, and the ability to associate and locate them, allow us to infer details of the spatial and temporal distributions and possible variations in stresses within these key regions of the volcanoes.

  10. Crowdsourced earthquake early warning

    Science.gov (United States)

    Minson, Sarah E.; Brooks, Benjamin A.; Glennie, Craig L.; Murray, Jessica R.; Langbein, John O.; Owen, Susan E.; Heaton, Thomas H.; Iannucci, Robert A.; Hauser, Darren L.

    2015-01-01

    Earthquake early warning (EEW) can reduce harm to people and infrastructure from earthquakes and tsunamis, but it has not been implemented in most high earthquake-risk regions because of prohibitive cost. Common consumer devices such as smartphones contain low-cost versions of the sensors used in EEW. Although less accurate than scientific-grade instruments, these sensors are globally ubiquitous. Through controlled tests of consumer devices, simulation of an Mw (moment magnitude) 7 earthquake on California’s Hayward fault, and real data from the Mw 9 Tohoku-oki earthquake, we demonstrate that EEW could be achieved via crowdsourcing.

  11. Earthquake Protection Measures for People with Disabilities

    Science.gov (United States)

    Gountromichou, C.; Kourou, A.; Kerpelis, P.

    2009-04-01

    The problem of seismic safety for people with disabilities not only exists but is also urgent and of primary importance. Working towards disability equality, Earthquake Planning and Protection Organization of Greece (E.P.P.O.) has developed an educational scheme for people with disabilities in order to guide them to develop skills to protect themselves as well as to take the appropriate safety measures before, during and after an earthquake. The framework of this initiative includes a number of actions have been already undertaken, including the following: a. Recently, the main guidelines have been published to help people who have physical, cognitive, visual, or auditory disabilities to cope with a destructive earthquake. Of great importance, in case of people with disabilities, is to be prepared for the disaster, with several measures that must be taken starting today. In the pre-earthquake period, it is important that these people, in addition to other measures, do the following: - Create a Personal Support Network The Personal Support Network should be a group of at least three trustful people that can assist the disabled person to prepare for a disastrous event and to recover after it. - Complete a Personal Assessment The environment may change after a destructive earthquake. People with disabilities are encouraged to make a list of their personal needs and their resources for meeting them in a disaster environment. b. Lectures and training seminars on earthquake protection are given for students, teachers and educators in Special Schools for disabled people, mainly for informing and familiarizing them with earthquakes and with safety measures. c. Many earthquake drills have already taken place, for each disability, in order to share good practices and lessons learned to further disaster reduction and to identify gaps and challenges. The final aim of this action is all people with disabilities to be well informed and motivated towards a culture of earthquake

  12. Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

    Science.gov (United States)

    Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

    2015-01-01

    The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

  13. Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

    Directory of Open Access Journals (Sweden)

    Sanjay Saini

    Full Text Available The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO. However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO. The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF and Hierarchical Particle Swarm Optimization (HPSO. Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

  14. Agent-Based Simulation and Analysis of a Defensive UAV Swarm Against an Enemy UAV Swarm

    Science.gov (United States)

    2011-06-01

    energy options” [10]. The research of swarm robotics derives much of its inspiration from natural systems. Social insects are known to coordinate their...Monterey, California 9. CPT. Francisco J. Hederra Direccion de Investigacion , Programas y Desarrollo de la Armada Armada de Chile CHILE 10. CAPT Jeffrey Kline, USN(ret.) Naval Postgraduate School Monterey, California 91

  15. Earthquakes - a danger to deep-lying repositories?; erdbeben: eine gefahr fuer tiefenlager?

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-03-15

    This booklet issued by the Swiss National Cooperative for the Disposal of Radioactive Waste NAGRA takes a look at geological factors concerning earthquakes and the safety of deep-lying repositories for nuclear waste. The geological processes involved in the occurrence of earthquakes are briefly looked at and the definitions for magnitude and intensity of earthquakes are discussed. Examples of damage caused by earthquakes are given. The earthquake situation in Switzerland is looked at and the effects of earthquakes on sub-surface structures and deep-lying repositories are discussed. Finally, the ideas proposed for deep-lying geological repositories for nuclear wastes are discussed.

  16. Improved cuckoo search with particle swarm optimization for ...

    Indian Academy of Sciences (India)

    Content based image retrieval (CBIR); image compression; partial recurrent neural network (PRNN); particle swarm optimization (PSO); HAARwavelet; Cuckoo Search ... are NP hard, a hybrid Particle Swarm Optimization (PSO) – Cuckoo Search algorithm (CS) is proposed to optimize the learning rate of the neural network.

  17. A new hybrid teaching–learning particle swarm optimization ...

    Indian Academy of Sciences (India)

    This paper proposes a novel hybrid teaching–learning particle swarm optimization (HTLPSO) algorithm, which merges two established nature-inspired algorithms, namely, optimization based on teaching–learning (TLBO) and particle swarm optimization (PSO). The HTLPSO merges the best half of population obtained after ...

  18. Swarming modulatory effects of some amino acids on Proteus ...

    African Journals Online (AJOL)

    Swarming motility, a multicellular behaviour characterized by periodic concentric growth on solid media has severally been reported as a constraint in the clinical investigation of mixed-culture infections involving Proteus and as a requirement for virulence. While media are being formulated to restrain swarming in this ...

  19. Level-2 product generation for the Swarm satellite constellation mission

    DEFF Research Database (Denmark)

    Olsen, Poul Erik Holmdahl; Tøffner-Clausen, Lars; Olsen, Nils

    In order to take advantage of the unique constellation aspect of ESA's Swarm constellation mission, considerably advanced data analysis tools have been developed. The Swarm ESL/SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, derives...

  20. A novel particle swarm optimization based on population category

    Science.gov (United States)

    Wang, Jingying; Qu, Jianhua

    2017-10-01

    This paper raised a novel particle swarm optimization algorithm based on population category. Traditional particle swarm optimization algorithm is easily to trap in local optimum. In order to avoid standard algorithm appearing premature convergence, this novel algorithm use population category strategy to find new directions for particles. At last, computational results show that the new method is effective and has a high-performance.

  1. A persistent homology approach to collective behavior in insect swarms

    Science.gov (United States)

    Sinhuber, Michael; Ouellette, Nicholas T.

    Various animals from birds and fish to insects tend to form aggregates, displaying self-organized collective swarming behavior. Due to their frequent occurrence in nature and their implications for engineered, collective systems, these systems have been investigated and modeled thoroughly for decades. Common approaches range from modeling them with coupled differential equations on the individual level up to continuum approaches. We present an alternative, topology-based approach for describing swarming behavior at the macroscale rather than the microscale. We study laboratory swarms of Chironomus riparius, a flying, non-biting midge. To obtain the time-resolved three-dimensional trajectories of individual insects, we use a multi-camera stereoimaging and particle-tracking setup. To investigate the swarming behavior in a topological sense, we employ a persistent homology approach to identify persisting structures and features in the insect swarm that elude a direct, ensemble-averaging approach. We are able to identify features of sub-clusters in the swarm that show behavior distinct from that of the remaining swarm members. The coexistence of sub-swarms with different features resembles some non-biological systems such as active colloids or even thermodynamic systems.

  2. Proteus mirabilis interkingdom swarming signals attract blow flies

    Science.gov (United States)

    Ma, Qun; Fonseca, Alicia; Liu, Wenqi; Fields, Andrew T; Pimsler, Meaghan L; Spindola, Aline F; Tarone, Aaron M; Crippen, Tawni L; Tomberlin, Jeffery K; Wood, Thomas K

    2012-01-01

    Flies transport specific bacteria with their larvae that provide a wider range of nutrients for those bacteria. Our hypothesis was that this symbiotic interaction may depend on interkingdom signaling. We obtained Proteus mirabilis from the salivary glands of the blow fly Lucilia sericata; this strain swarmed significantly and produced a strong odor that attracts blow flies. To identify the putative interkingdom signals for the bacterium and flies, we reasoned that as swarming is used by this bacterium to cover the food resource and requires bacterial signaling, the same bacterial signals used for swarming may be used to communicate with blow flies. Using transposon mutagenesis, we identified six novel genes for swarming (ureR, fis, hybG, zapB, fadE and PROSTU_03490), then, confirming our hypothesis, we discovered that fly attractants, lactic acid, phenol, NaOH, KOH and ammonia, restore swarming for cells with the swarming mutations. Hence, compounds produced by the bacterium that attract flies also are utilized for swarming. In addition, bacteria with the swarming mutation rfaL attracted fewer blow flies and reduced the number of eggs laid by the flies. Therefore, we have identified several interkingdom signals between P. mirabilis and blow flies. PMID:22237540

  3. Swarming modulatory effects of some amino acids on Proteus ...

    African Journals Online (AJOL)

    Swarming motility, a multicellular behaviour characterized by periodic concentric growth on solid media has severally been reported as a constraint in the clinical ... The effects of 20 amino acids on swarming, extracellular protease activity, cellular RNA level and total protein concentration in 20 clinical Proteus strains from ...

  4. New paleomagnetic results on 2367 Ma Dharwar giant dyke swarm ...

    Indian Academy of Sciences (India)

    N Ramesh Babu

    2018-02-14

    Feb 14, 2018 ... 2012). This direction is considered as primary magnetization of 2082 Ma radiating dyke swarm of. EDC (Kumar et al. 2015). Hence, we infer here that the source for component (B) is possibly the recently reported 2080 Ma spectacular radiating dyke swarm, which radiates beneath the Cudda- pah basin with ...

  5. Transport of Particle Swarms Through Variable Aperture Fractures

    Science.gov (United States)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2012-12-01

    Particle transport through fractured rock is a key concern with the increased use of micro- and nano-size particles in consumer products as well as from other activities in the sub- and near surface (e.g. mining, industrial waste, hydraulic fracturing, etc.). While particle transport is often studied as the transport of emulsions or dispersions, particles may also enter the subsurface from leaks or seepage that lead to particle swarms. Swarms are drop-like collections of millions of colloidal-sized particles that exhibit a number of unique characteristics when compared to dispersions and emulsions. Any contaminant or engineered particle that forms a swarm can be transported farther, faster, and more cohesively in fractures than would be expected from a traditional dispersion model. In this study, the effects of several variable aperture fractures on colloidal swarm cohesiveness and evolution were studied as a swarm fell under gravity and interacted with the fracture walls. Transparent acrylic was used to fabricate synthetic fracture samples with (1) a uniform aperture, (2) a converging region followed by a uniform region (funnel shaped), (3) a uniform region followed by a diverging region (inverted funnel), and (4) a cast of a an induced fracture from a carbonate rock. All of the samples consisted of two blocks that measured 100 x 100 x 50 mm. The minimum separation between these blocks determined the nominal aperture (0.5 mm to 20 mm). During experiments a fracture was fully submerged in water and swarms were released into it. The swarms consisted of a dilute suspension of 3 micron polystyrene fluorescent beads (1% by mass) with an initial volume of 5μL. The swarms were illuminated with a green (525 nm) LED array and imaged optically with a CCD camera. The variation in fracture aperture controlled swarm behavior. Diverging apertures caused a sudden loss of confinement that resulted in a rapid change in the swarm's shape as well as a sharp increase in its velocity

  6. Swarming Robot Design, Construction and Software Implementation

    Science.gov (United States)

    Stolleis, Karl A.

    2014-01-01

    In this paper is presented an overview of the hardware design, construction overview, software design and software implementation for a small, low-cost robot to be used for swarming robot development. In addition to the work done on the robot, a full simulation of the robotic system was developed using Robot Operating System (ROS) and its associated simulation. The eventual use of the robots will be exploration of evolving behaviors via genetic algorithms and builds on the work done at the University of New Mexico Biological Computation Lab.

  7. Collective motion in Proteus mirabilis swarms

    Science.gov (United States)

    Haoran, Xu

    Proteus mirabilisis a Gram-negative, rod-shaped bacterium. It is widely distributed in soil and water, and it is well known for exhibiting swarming motility on nutrient agar surfaces. In our study, we focused on the collective motility of P. mirabilis and uncovered a range of interesting phenomena. Here we will present our efforts to understand these phenomena through experiments and simulation. Mailing address: Room 306 Science Centre North Block, The Chinese University of Hong Kong, Shatin, N.T. Hong Kong SAR. Phone: +852-3943-6354. Fax: +852-2603-5204. E-mail:xhrphx@gmail.com.

  8. Human management of a robotic swarm

    OpenAIRE

    Salomons, N.; Kapellmann-Zafra, G.; Gross, R.

    2016-01-01

    This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On aver...

  9. Particle Swarm Optimization and Regression Analysis II

    Science.gov (United States)

    Mohanty, Soumya D.

    2012-10-01

    In the first part of this article, Particle Swarm Optimization (PSO) was applied to the problem of optimizing knot placement in the regression spline method. Although promising for broadband signals having smooth, but otherwise unknown, waveforms, this simple approach fails in the case of narrowband signals when the carrier frequency as well as the amplitude and phase modulations are unknown. A method is presented that addresses this challenge by using PSO based regression splines for the in-phase and quadrature amplitudes separately. It is thereby seen that PSO is an effective tool for regression analysis of a broad class of signals.

  10. Test Frequency Selection Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Zdenek Kincl

    2013-01-01

    Full Text Available The paper deals with the problem of test frequency selection for multi-frequency parametric fault diagnosis of analog linear circuits. An appropriate set of test frequencies is determined by minimizing the conditionality of the sensitivity matrix based on the system of fault equations using a global stochastic optimization. A novel method based on the Particle Swarm Optimization, which provides more accurate results and improves the convergence rate, is described. The paper provides several practical examples of its application to test frequency selection for active RC filters. A comparison of the results obtained by the proposed method and by the Genetic Algorithm is also presented.

  11. Research on response spectrum of dam based on scenario earthquake

    Science.gov (United States)

    Zhang, Xiaoliang; Zhang, Yushan

    2017-10-01

    Taking a large hydropower station as an example, the response spectrum based on scenario earthquake is determined. Firstly, the potential source of greatest contribution to the site is determined on the basis of the results of probabilistic seismic hazard analysis (PSHA). Secondly, the magnitude and epicentral distance of the scenario earthquake are calculated according to the main faults and historical earthquake of the potential seismic source zone. Finally, the response spectrum of scenario earthquake is calculated using the Next Generation Attenuation (NGA) relations. The response spectrum based on scenario earthquake method is less than the probability-consistent response spectrum obtained by PSHA method. The empirical analysis shows that the response spectrum of scenario earthquake considers the probability level and the structural factors, and combines the advantages of the deterministic and probabilistic seismic hazard analysis methods. It is easy for people to accept and provide basis for seismic engineering of hydraulic engineering.

  12. Is the seismicity swarm at long-dormant Jailolo volcano (Indonesia) a signature of a magmatic unrest?

    Science.gov (United States)

    Passarelli, Luigi; Cesca, Simone; Heryandoko, Nova; Lopez Comino, Jose Angel; Strollo, Angelo; Rivalta, Eleonora; Rohadi, Supryianto; Dahm, Torsten; Milkereit, Claus

    2017-04-01

    Magmatic unrest is challenging to detect when monitoring is sparse and there is little knowledge about the volcano. This is especially true for long-dormant volcanoes. Geophysical observables like seismicity, deformation, temperature and gas emission are reliable indicators of ongoing volcanic unrest caused by magma movements. Jailolo volcano is a Holocene volcano belonging to the Halmahera volcanic arc in the Northern Moluccas Islands, Indonesia. Global databases of volcanic eruptions have no records of its eruptive activity and no geological investigation has been carried out to better assess the past eruptive activity at Jailolo. It probably sits on the northern rim of an older caldera which now forms the Jailolo bay. Hydrothermal activity is intense with several hot-springs and steaming ground spots around the Jailolo volcano. In November 2015 an energetic seismic swarm started and lasted until late February 2016 with four earthquakes with M>5 recorded by global seismic networks. At the time of the swarm no close geophysical monitoring network was available around Jailolo volcano except for a broadband station at 30km distant. We installed last summer a local dense multi-parametric monitoring network with 36 seismic stations, 6 GPS and 2 gas monitoring stations around Jailolo volcano. We revised the focal mechanisms of the larger events and used single station location methods in order to exploit the little information available at the time of the swarm activity. We also combined the old sparse data with our local dense network. Migration of hypocenters and inversion of the local stress field derived by focal mechanisms analysis indicate that the Nov-Feb seismicity swarm may be related to a magmatic intrusion at shallow depth. Data from our dense network confirms ongoing micro-seismic activity underneath Jailolo volcano but there are no indications of new magma intrusion. Our findings indicate that magmatic unrest occurred at Jailolo volcano and call for a

  13. Antarctic krill swarm characteristics in the Southeast Atlantic sector of the Southern Ocean

    KAUST Repository

    Krafft, BA

    2012-09-28

    Knowledge about swarm dynamics and underlying causes is essential to understand the ecology and distribution of Antarctic krill Euphausia superba. We collected acoustic data and key environmental data continuously across extensive gradients in the little-studied Southeast Atlantic sector of the Southern Ocean. A total of 4791 krill swarms with swarm descriptors including swarm height and length, packing density, swimming depth and inter-swarm distance were extracted. Through multivariate statistics, swarms were categorized into 4 groups. Group 2 swarms were largest (median length 108 m and thickness 18 m), whereas swarms in both Groups 1 and 4 were on average small, but differed markedly in depth distribution (median: 52 m for Group 1 vs. 133 m for Group 4). There was a strong spatial autocorrelation in the occurrence of swarms, and an autologistic regression model found no prediction of swarm occurrence from environmental variables for any of the Groups 1, 2 or 4. Probability of occurrence of Group 3 swarms, however, increased with increasing depth and temperature. Group 3 was the most distinctive swarm group with an order of magnitude higher packing density (median: 226 ind. m−3) than swarms from any of the other groups and about twice the distance to nearest neighbor swarm (median: 493 m). The majority of the krill were present in Group 3 swarms, and the absence of association with hydrographic or topographic concentrating mechanisms strongly suggests that these swarms aggregate through their own locomotion, possibly associated with migration.

  14. New tools for characterizing swarming systems: A comparison of minimal models

    Science.gov (United States)

    Huepe, Cristián; Aldana, Maximino

    2008-05-01

    We compare three simple models that reproduce qualitatively the emergent swarming behavior of bird flocks, fish schools, and other groups of self-propelled agents by using a new set of diagnosis tools related to the agents’ spatial distribution. Two of these correspond in fact to different implementations of the same model, which had been previously confused in the literature. All models appear to undergo a very similar order-to-disorder phase transition as the noise level is increased if we only compare the standard order parameter, which measures the degree of agent alignment. When considering our novel quantities, however, their properties are clearly distinguished, unveiling previously unreported qualitative characteristics that help determine which model best captures the main features of realistic swarms. Additionally, we analyze the agent clustering in space, finding that the distribution of cluster sizes is typically exponential at high noise, and approaches a power-law as the noise level is reduced. This trend is sometimes reversed at noise levels close to the phase transition, suggesting a non-trivial critical behavior that could be verified experimentally. Finally, we study a bi-stable regime that develops under certain conditions in large systems. By computing the probability distributions of our new quantities, we distinguish the properties of each of the coexisting metastable states. Our study suggests new experimental analyses that could be carried out to characterize real biological swarms.

  15. Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Yanbin Gao

    2015-01-01

    Full Text Available Artificial fish swarm algorithm (AFSA is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS. In this study, a novel artificial fish swarm algorithm (NAFSA that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification.

  16. Swarm intelligence based on modified PSO algorithm for the optimization of axial-flow pump impeller

    Energy Technology Data Exchange (ETDEWEB)

    Miao, Fuqing; Kim, Chol Min; Ahn, Seok Young [Pusan National University, Busan (Korea, Republic of); Park, Hong Seok [Ulsan University, Ulsan (Korea, Republic of)

    2015-11-15

    This paper presents a multi-objective optimization of the impeller shape of an axial-flow pump based on the Modified particle swarm optimization (MPSO) algorithm. At first, an impeller shape was designed and used as a reference in the optimization process then NPSHr and η of the axial flow pump were numerically investigated by using the commercial software ANSYS with the design variables concerning hub angle β{sub h}, chord angle β{sub c}, cascade solidity of chord σ{sub c} and maximum thickness of blade H. By using the Group method of data handling (GMDH) type neural networks in commercial software DTREG, the corresponding polynomial representation for NPSHr and η with respect to the design variables were obtained. A benchmark test was employed to evaluate the performance of the MPSO algorithm in comparison with other particle swarm algorithms. Later the MPSO approach was used for Pareto based optimization. Finally, the MPSO optimization result and CFD simulation result were compared in a re-evaluation process. By using swarm intelligence based on the modified PSO algorithm, better performance pump with higher efficiency and lower NPSHr could be obtained. This novel algorithm was successfully applied for the optimization of axial-flow pump impeller shape design.

  17. Encyclopedia of earthquake engineering

    CERN Document Server

    Kougioumtzoglou, Ioannis; Patelli, Edoardo; Au, Siu-Kui

    2015-01-01

    The Encyclopedia of Earthquake Engineering is designed to be the authoritative and comprehensive reference covering all major aspects of the science of earthquake engineering, specifically focusing on the interaction between earthquakes and infrastructure. The encyclopedia comprises approximately 265 contributions. Since earthquake engineering deals with the interaction between earthquake disturbances and the built infrastructure, the emphasis is on basic design processes important to both non-specialists and engineers so that readers become suitably well-informed without needing to deal with the details of specialist understanding. The content of this encyclopedia provides technically inclined and informed readers about the ways in which earthquakes can affect our infrastructure and how engineers would go about designing against, mitigating and remediating these effects. The coverage ranges from buildings, foundations, underground construction, lifelines and bridges, roads, embankments and slopes. The encycl...

  18. Earthquake detection through computationally efficient similarity search.

    Science.gov (United States)

    Yoon, Clara E; O'Reilly, Ossian; Bergen, Karianne J; Beroza, Gregory C

    2015-12-01

    Seismology is experiencing rapid growth in the quantity of data, which has outpaced the development of processing algorithms. Earthquake detection-identification of seismic events in continuous data-is a fundamental operation for observational seismology. We developed an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint And Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than 2 hours, or 140 times faster than autocorrelation. FAST adapts a data mining algorithm, originally designed to identify similar audio clips within large databases; it first creates compact "fingerprints" of waveforms by extracting key discriminative features, then groups similar fingerprints together within a database to facilitate fast, scalable search for similar fingerprint pairs, and finally generates a list of earthquake detections. FAST detected most (21 of 24) cataloged earthquakes and 68 uncataloged earthquakes in 1 week of continuous data from a station located near the Calaveras Fault in central California, achieving detection performance comparable to that of autocorrelation, with some additional false detections. FAST is expected to realize its full potential when applied to extremely long duration data sets over a distributed network of seismic stations. The widespread application of FAST has the potential to aid in the discovery of unexpected seismic signals, improve seismic monitoring, and promote a greater understanding of a variety of earthquake processes.

  19. Catalog of earthquake hypocenters at Alaskan volcanoes: January 1, 1994 through December 31, 1999

    Science.gov (United States)

    Jolly, Arthur D.; Stihler, Scott D.; Power, John A.; Lahr, John C.; Paskievitch, John; Tytgat, Guy; Estes, Steve; Lockhart, Andrew B.; Moran, Seth C.; McNutt, Stephen R.; Hammond, William R.

    2001-01-01

    swarm at Akutan volcano in March and April 1996 (Lu and others, 2000); 2) an eruption at Pavlof Volcano in fall 1996 (Garces and others, 2000; McNutt and others, 2000); 3) an earthquake swarm at Iliamna volcano between September and December 1996; 4) an earthquake swarm at Mount Mageik in October 1996 (Jolly and McNutt, 1999); 5) an earthquake swarm located at shallow depth near Strandline Lake; 6) a strong swarm of earthquakes near Becharof Lake; 7) precursory seismicity and an eruption at Shishaldin Volcano in April 1999 that included a 5.2 ML earthquake and aftershock sequence (Moran and others, in press; Thompson and others, in press). The 1996 calendar year is also notable as the seismicity rate was very high, especially in the fall when 3 separate areas (Strandline Lake, Iliamna Volcano, and several of the Katmai volcanoes) experienced high rates of located earthquakes.This catalog covers the period from January 1, 1994, through December 31,1999, and includes: 1) earthquake origin times, hypocenters, and magnitudes with summary statistics describing the earthquake location quality; 2) a description of instruments deployed in the field and their locations and magnifications; 3) a description of earthquake detection, recording, analysis, and data archival; 4) velocity models used for earthquake locations; 5) phase arrival times recorded at individual stations; and 6) a summary of daily station usage from throughout the report period. We have made calculated hypocenters, station locations, system magnifications, velocity models, and phase arrival information available for download via computer network as a compressed Unix tar file.

  20. Application of particle swarm optimization to interpret Rayleigh wave dispersion curves

    Science.gov (United States)

    Song, Xianhai; Tang, Li; Lv, Xiaochun; Fang, Hongping; Gu, Hanming

    2012-09-01

    Rayleigh waves have been used increasingly as an appealing tool to obtain near-surface shear (S)-wave velocity profiles. However, inversion of Rayleigh wave dispersion curves is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this study, we proposed and tested a new Rayleigh wave dispersion curve inversion scheme based on particle swarm optimization (PSO). PSO is a global optimization strategy that simulates the social behavior observed in a flock (swarm) of birds searching for food. A simple search strategy in PSO guides the algorithm toward the best solution through constant updating of the cognitive knowledge and social behavior of the particles in the swarm. To evaluate calculation efficiency and stability of PSO to inversion of surface wave data, we first inverted three noise-free and three noise-corrupted synthetic data sets. Then, we made a comparative analysis with genetic algorithms (GA) and a Monte Carlo (MC) sampler and reconstructed a histogram of model parameters sampled on a low-misfit region less than 15% relative error to further investigate the performance of the proposed inverse procedure. Finally, we inverted a real-world example from a waste disposal site in NE Italy to examine the applicability of PSO on Rayleigh wave dispersion curves. Results from both synthetic and field data demonstrate that particle swarm optimization can be used for quantitative interpretation of Rayleigh wave dispersion curves. PSO seems superior to GA and MC in terms of both reliability and computational efforts. The great advantages of PSO are fast in locating the low misfit region and easy to implement. Also there are only three parameters to tune (inertia weight or constriction factor, local and global acceleration constants). Theoretical results exist to explain how to tune these parameters.

  1. Fourier transform and particle swarm optimization based modified LQR algorithm for mitigation of vibrations using magnetorheological dampers

    Science.gov (United States)

    Kumar, Gaurav; Kumar, Ashok

    2017-11-01

    Structural control has gained significant attention in recent times. The standalone issue of power requirement during an earthquake has already been solved up to a large extent by designing semi-active control systems using conventional linear quadratic control theory, and many other intelligent control algorithms such as fuzzy controllers, artificial neural networks, etc. In conventional linear-quadratic regulator (LQR) theory, it is customary to note that the values of the design parameters are decided at the time of designing the controller and cannot be subsequently altered. During an earthquake event, the response of the structure may increase or decrease, depending the quasi-resonance occurring between the structure and the earthquake. In this case, it is essential to modify the value of the design parameters of the conventional LQR controller to obtain optimum control force to mitigate the vibrations due to the earthquake. A few studies have been done to sort out this issue but in all these studies it was necessary to maintain a database of the earthquake. To solve this problem and to find the optimized design parameters of the LQR controller in real time, a fast Fourier transform and particle swarm optimization based modified linear quadratic regulator method is presented here. This method comprises four different algorithms: particle swarm optimization (PSO), the fast Fourier transform (FFT), clipped control algorithm and the LQR. The FFT helps to obtain the dominant frequency for every time window. PSO finds the optimum gain matrix through the real-time update of the weighting matrix R, thereby, dispensing with the experimentation. The clipped control law is employed to match the magnetorheological (MR) damper force with the desired force given by the controller. The modified Bouc-Wen phenomenological model is taken to recognize the nonlinearities in the MR damper. The assessment of the advised method is done by simulation of a three-story structure

  2. Operating Small Sat Swarms as a Single Entity: Introducing SODA

    Science.gov (United States)

    Conn, Tracie; Dono Perez, Andres

    2017-01-01

    Swarm concepts are a growing topic of interest in the small satellite community. Compared to a small satellite constellation, a swarm has the distinction of being multiple spacecraft in close proximity, in approximately the same orbit. Furthermore, we envision swarms to have capabilities for cross-link communication and station-keeping. Of particular interest is a means to maintain operator-specified geometry, alignment, and/or separation.From NASA's decadal survey, it is clear that simultaneous measurements from a 3D volume of space are desired for a variety of Earth scientific studies. As this mission concept is ultimately extended to deep space, some degree of local control for the swarm to self-correct its configuration is required. We claim that the practicality of ground commanding each individual satellite in the swarm is simply not a feasible concept of operations. In other words, the current state-of-practice does not scale to very large swarms (e.g. 100 spacecraft or more) without becoming cost prohibitive. To contain the operations costs and complexity, a new approach is required: the swarm must be operated as a unit, responding to high-level specifications for relative position and velocity.The Mission Design Division at NASA Ames Research Center is looking to the near future for opportunities to develop satellite swarm technology. As part of this effort, we are developing SODA (Swarm Orbital Dynamics Advisor), a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion. The purpose of SODA is two-fold. First, it encompasses the algorithms and orbital dynamics model to enable the desired relative motion of the swarm satellites. The process starts with the user specifying the properties of a swarm configuration. This could be as simple as varying in-track spacing of the swarm in one orbit, or as complex as maintaining a specified 3D geometrical orientation. We presume that science objectives will drive this

  3. Particle Swarm Transport through Immiscible Fluid Layers in a Fracture

    Science.gov (United States)

    Teasdale, N. D.; Boomsma, E.; Pyrak-Nolte, L. J.

    2011-12-01

    Immiscible fluids occur either naturally (e.g. oil & water) or from anthropogenic processes (e.g. liquid CO2 & water) in the subsurface and complicate the transport of natural or engineered micro- or nano-scale particles. In this study, we examined the effect of immiscible fluids on the formation and evolution of particle swarms in a fracture. A particle swarm is a collection of colloidal-size particles in a dilute suspension that exhibits cohesive behavior. Swarms fall under gravity with a velocity that is greater than the settling velocity of a single particle. Thus a particle swarm of colloidal contaminants can potentially travel farther and faster in a fracture than expected for a dispersion or emulsion of colloidal particles. We investigated the formation, evolution, and break-up of colloidal swarms under gravity in a uniform aperture fracture as hydrophobic/hydrophyllic particle swarms move across an oil-water interface. A uniform aperture fracture was fabricated from two transparent acrylic rectangular prisms (100 mm x 50 mm x 100 mm) that are separated by 1, 2.5, 5, 10 or 50 mm. The fracture was placed, vertically, inside a glass tank containing a layer of pure silicone oil (polydimethylsiloxane) on distilled water. Along the length of the fracture, 30 mm was filled with oil and 70 mm with water. Experiments were conducted using silicone oils with viscosities of 5, 10, 100, or 1000 cSt. Particle swarms (5 μl) were comprised of a 1% concentration (by mass) of 25 micron glass beads (hydrophilic) suspended in a water drop, or a 1% concentration (by mass) of 3 micron polystyrene fluorescent beads (hydrophobic) suspended in a water drop. The swarm behavior was imaged using an optical fluorescent imaging system composed of a CCD camera and by green (525 nm) LED arrays for illumination. Swarms were spherical and remained coherent as they fell through the oil because of the immiscibility of oil and water. However, as a swarm approached the oil-water interface, it

  4. Water surface tension modulates the swarming mechanics of Bacillus subtilis.

    Science.gov (United States)

    Ke, Wan-Ju; Hsueh, Yi-Huang; Cheng, Yu-Chieh; Wu, Chih-Ching; Liu, Shih-Tung

    2015-01-01

    Many Bacillus subtilis strains swarm, often forming colonies with tendrils on agar medium. It is known that B. subtilis swarming requires flagella and a biosurfactant, surfactin. In this study, we find that water surface tension plays a role in swarming dynamics. B. subtilis colonies were found to contain water, and when a low amount of surfactin is produced, the water surface tension of the colony restricts expansion, causing bacterial density to rise. The increased density induces a quorum sensing response that leads to heightened production of surfactin, which then weakens water surface tension to allow colony expansion. When the barrier formed by water surface tension is breached at a specific location, a stream of bacteria swarms out of the colony to form a tendril. If a B. subtilis strain produces surfactin at levels that can substantially weaken the overall water surface tension of the colony, water floods the agar surface in a thin layer, within which bacteria swarm and migrate rapidly. This study sheds light on the role of water surface tension in regulating B. subtilis swarming, and provides insight into the mechanisms underlying swarming initiation and tendril formation.

  5. Middleware Design for Swarm-Driving Robots Accompanying Humans.

    Science.gov (United States)

    Kim, Min Su; Kim, Sang Hyuck; Kang, Soon Ju

    2017-02-17

    Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF) communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR) communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves.

  6. Chaotic particle swarm optimization with mutation for classification.

    Science.gov (United States)

    Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

    2015-01-01

    In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

  7. Colias: An Autonomous Micro Robot for Swarm Robotic Applications

    Directory of Open Access Journals (Sweden)

    Farshad Arvin

    2014-07-01

    Full Text Available Robotic swarms that take inspiration from nature are becoming a fascinating topic for multi-robot researchers. The aim is to control a large number of simple robots in order to solve common complex tasks. Due to the hardware complexities and cost of robot platforms, current research in swarm robotics is mostly performed by simulation software. The simulation of large numbers of these robots in robotic swarm applications is extremely complex and often inaccurate due to the poor modelling of external conditions. In this paper, we present the design of a low-cost, open-platform, autonomous micro-robot (Colias for robotic swarm applications. Colias employs a circular platform with a diameter of 4 cm. It has a maximum speed of 35 cm/s which enables it to be used in swarm scenarios very quickly over large arenas. Long-range infrared modules with an adjustable output power allow the robot to communicate with its direct neighbours at a range of 0.5 cm to 2 m. Colias has been designed as a complete platform with supporting software development tools for robotics education and research. It has been tested in both individual and swarm scenarios, and the observed results demonstrate its feasibility for use as a micro-sized mobile robot and as a low-cost platform for robot swarm applications.

  8. HAZGRIDX: earthquake forecasting model for ML≥ 5.0 earthquakes in Italy based on spatially smoothed seismicity

    Directory of Open Access Journals (Sweden)

    Aybige Akinci

    2010-11-01

    Full Text Available We present a five-year, time-independent, earthquake-forecast model for earthquake magnitudes of 5.0 and greater in Italy using spatially smoothed seismicity data. The model is called HAZGRIDX, and it was developed based on the assumption that future earthquakes will occur near locations of historical earthquakes; it does not take into account any information from tectonic, geological, or geodetic data. Thus HAZGRIDX is based on observed earthquake occurrence from seismicity data, without considering any physical model. In the present study, we calculate earthquake rates on a spatial grid platform using two declustered catalogs: 1 the Parametric catalog of Italian earthquakes (Catalogo Parametrico dei Terremoti Italiani, CPTI04 that contains the larger earthquakes from MW 7.0 since 1100; and 2 the Italian seismicity catalogue (Catalogo della Sismicità Italiana, CSI 1.1 that contains the small earthquakes down to ML 1.0, with a maximum of ML 5.9, over the past 22 years (1981-2003. The model assumes that earthquake magnitudes follow the Gutenberg-Richter law, with a uniform b-value. The forecast rates are presented in terms of the expected numbers of ML>5.0 events per year for each grid cell of about 10 km × 10 km. The final map is derived by averaging the earthquake potentials that come from these two different catalogs: CPTI04 and CSI 1.1. We also describe the earthquake occurrences in terms of probabilities of occurrence of one event within a specified magnitude bin, DM0.1, in a five year time period. HAZGRIDX is one of several forecasting models, scaled to five and ten years, that have been submitted to the Collaboratory for the Study of Earthquake Probability (CSEP forecasting center in ETH, Zurich, to be tested for Italy.

  9. POLICE OFFICE MODEL IMPROVEMENT FOR SECURITY OF SWARM ROBOTIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    I. A. Zikratov

    2014-09-01

    Full Text Available This paper focuses on aspects of information security for group of mobile robotic systems with swarm intellect. The ways for hidden attacks realization by the opposing party on swarm algorithm are discussed. We have fulfilled numerical modeling of potentially destructive information influence on the ant shortest path algorithm. We have demonstrated the consequences of attacks on the ant algorithm with different concentration in a swarm of subversive robots. Approaches are suggested for information security mechanisms in swarm robotic systems, based on the principles of centralized security management for mobile agents. We have developed the method of forming a self-organizing information security management system for robotic agents in swarm groups implementing POM (Police Office Model – a security model based on police offices, to provide information security in multi-agent systems. The method is based on the usage of police station network in the graph nodes, which have functions of identification and authentication of agents, identifying subversive robots by both their formal characteristics and their behavior in the swarm. We have suggested a list of software and hardware components for police stations, consisting of: communication channels between the robots in police office, nodes register, a database of robotic agents, a database of encryption and decryption module. We have suggested the variants of logic for the mechanism of information security in swarm systems with different temporary diagrams of data communication between police stations. We present comparative analysis of implementation of protected swarm systems depending on the functioning logic of police offices, integrated in swarm system. It is shown that the security model saves the ability to operate in noisy environments, when the duration of the interference is comparable to the time necessary for the agent to overcome the path between police stations.

  10. Fractional order Darwinian particle swarm optimization applications and evaluation of an evolutionary algorithm

    CERN Document Server

    Couceiro, Micael

    2015-01-01

    This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, suc

  11. Napa earthquake: An earthquake in a highly connected world

    Science.gov (United States)

    Bossu, R.; Steed, R.; Mazet-Roux, G.; Roussel, F.

    2014-12-01

    The Napa earthquake recently occurred close to Silicon Valley. This makes it a good candidate to study what social networks, wearable objects and website traffic analysis (flashsourcing) can tell us about the way eyewitnesses react to ground shaking. In the first part, we compare the ratio of people publishing tweets and with the ratio of people visiting EMSC (European Mediterranean Seismological Centre) real time information website in the first minutes following the earthquake occurrence to the results published by Jawbone, which show that the proportion of people waking up depends (naturally) on the epicentral distance. The key question to evaluate is whether the proportions of inhabitants tweeting or visiting the EMSC website are similar to the proportion of people waking up as shown by the Jawbone data. If so, this supports the premise that all methods provide a reliable image of the relative ratio of people waking up. The second part of the study focuses on the reaction time for both Twitter and EMSC website access. We show, similarly to what was demonstrated for the Mineral, Virginia, earthquake (Bossu et al., 2014), that hit times on the EMSC website follow the propagation of the P waves and that 2 minutes of website traffic is sufficient to determine the epicentral location of an earthquake on the other side of the Atlantic. We also compare with the publication time of messages on Twitter. Finally, we check whether the number of tweets and the number of visitors relative to the number of inhabitants is correlated to the local level of shaking. Together these results will tell us whether the reaction of eyewitnesses to ground shaking as observed through Twitter and the EMSC website analysis is tool specific (i.e. specific to Twitter or EMSC website) or whether they do reflect people's actual reactions.

  12. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer

    Directory of Open Access Journals (Sweden)

    Yu-Jun Zheng

    2012-01-01

    Full Text Available Particle swarm optimization (PSO is a stochastic optimization method sensitive to parameter settings. The paper presents a modification on the comprehensive learning particle swarm optimizer (CLPSO, which is one of the best performing PSO algorithms. The proposed method introduces a self-adaptive mechanism that dynamically changes the values of key parameters including inertia weight and acceleration coefficient based on evolutionary information of individual particles and the swarm during the search. Numerical experiments demonstrate that our approach with adaptive parameters can provide comparable improvement in performance of solving global optimization problems.

  13. The Swarm Initial Field Model for the 2014 geomagnetic field

    DEFF Research Database (Denmark)

    Olsen, Nils; Hulot, Gauthier; Lesur, Vincent

    2015-01-01

    Data from the first year of ESA's Swarm constellation mission are used to derive the Swarm Initial Field Model (SIFM), a new model of the Earth's magnetic field and its time variation. In addition to the conventional magnetic field observations provided by each of the three Swarm satellites......, explicit advantage is taken of the constellation aspect by including East-West magnetic intensity gradient information from the lower satellite pair. Along-track differences in magnetic intensity provide further information concerning the North-South gradient. The SIFM static field shows excellent...

  14. Semisupervised Particle Swarm Optimization for Classification

    Directory of Open Access Journals (Sweden)

    Xiangrong Zhang

    2014-01-01

    Full Text Available A semisupervised classification method based on particle swarm optimization (PSO is proposed. The semisupervised PSO simultaneously uses limited labeled samples and large amounts of unlabeled samples to find a collection of prototypes (or centroids that are considered to precisely represent the patterns of the whole data, and then, in principle of the “nearest neighborhood,” the unlabeled data can be classified with the obtained prototypes. In order to validate the performance of the proposed method, we compare the classification accuracy of PSO classifier, k-nearest neighbor algorithm, and support vector machine on six UCI datasets, four typical artificial datasets, and the USPS handwritten dataset. Experimental results demonstrate that the proposed method has good performance even with very limited labeled samples due to the usage of both discriminant information provided by labeled samples and the structure information provided by unlabeled samples.

  15. Particle Swarm Optimization and regression analysis I

    Science.gov (United States)

    Mohanty, Souyma D.

    2012-04-01

    Particle Swarm Optimization (PSO) is now widely used in many problems that require global optimization of high-dimensional and highly multi-modal functions. However, PSO has not yet seen widespread use in astronomical data analysis even though optimization problems in this field have become increasingly complex. In this two-part article, we first provide an overview of the PSO method in the concrete context of a ubiquitous problem in astronomy, namely, regression analysis. In particular, we consider the problem of optimizing the placement of knots in regression based on cubic splines (spline smoothing). The second part will describe an in-depth investigation of PSO in some realistic data analysis challenges.

  16. Cosmological parameter estimation using Particle Swarm Optimization

    Science.gov (United States)

    Prasad, J.; Souradeep, T.

    2014-03-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

  17. Investigating the auroral electrojets using Swarm

    Science.gov (United States)

    Smith, Ashley; Macmillan, Susan; Beggan, Ciaran; Whaler, Kathy

    2016-04-01

    The auroral electrojets are large horizontal currents that flow within the ionosphere in ovals around the polar regions. They are an important aspect of space weather and their position and intensity vary with solar wind conditions and geomagnetic activity. The electrojet positions are also governed by the Earth's main magnetic field. During more active periods, the auroral electrojets typically move equatorward and become more intense. This causes a range of effects on Earth and in space, including geomagnetically induced currents in power transmission networks, disturbance to radio communications and increased drag on satellites due to expansion of the atmosphere. They are also indicative of where the aurora are visible. Monitoring of the auroral electrojets in the pre-satellite era was limited to the network of ground-based magnetic observatories, from which the traditional AE activity indices are produced. These suffer in particular from the stations' poor distribution in position and so this motivates the use of satellite-based measurements. With polar low-Earth orbit satellites carrying magnetometers, all latitudes can be sampled with excellent resolution. This poster presents an investigation using Swarm's magnetometer data to detect the electrojets as the spacecraft move above them. We compare and contrast two approaches, one which uses vector data and the other which uses scalar data (Hamilton and Macmillan 2013, Vennerstrom and Moretto, 2013). Using ideas from both approaches we determine the oval positions and intensities from Swarm and earlier satellites. The variation in latitude and intensity with solar wind conditions, geomagnetic activity and secular variation of the main field is investigated. We aim to elucidate the relative importance of these factors. Hamilton, B. and Macmillan, S., 2013. Investigation of decadal scale changes in the auroral oval positions using Magsat and CHAMP data. Poster at IAGA 12th Scientific Assembly, 2013. http

  18. Quantum particle swarm approaches applied to combinatorial problems

    Energy Technology Data Exchange (ETDEWEB)

    Nicolau, Andressa dos S.; Schirru, Roberto; Lima, Alan M.M. de, E-mail: andressa@lmp.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

    2017-07-01

    Quantum Particle Swarm Optimization (QPSO) is a global convergence algorithm that combines the classical PSO philosophy and quantum mechanics to improve performance of PSO. Different from PSO it only has the 'measurement' of the position equation for all particles. The process of 'measurement' in quantum mechanics, obey classic laws while the particle itself follows the quantum rules. QPSO works like PSO in search ability but has fewer parameters control. In order to improve the QPSO performance, some strategies have been proposed in the literature. Weighted QPSO (WQPSO) is a version of QPSO, where weight parameter is insert in the calculation of the balance between the global and local searching of the algorithm. It has been shown to perform well in finding the optimal solutions for many optimization problems. In this article random confinement was introduced in WQPSO. The WQPSO with random confinement was tested in two combinatorial problems. First, we execute the model on Travelling Salesman Problem (TSP) to find the parameters' values resulting in good solutions in general. Finally, the model was tested on Nuclear Reactor Reload Problem, and the performance was compared with QPSO standard. (author)

  19. Earthquakes and Schools

    Science.gov (United States)

    National Clearinghouse for Educational Facilities, 2008

    2008-01-01

    Earthquakes are low-probability, high-consequence events. Though they may occur only once in the life of a school, they can have devastating, irreversible consequences. Moderate earthquakes can cause serious damage to building contents and non-structural building systems, serious injury to students and staff, and disruption of building operations.…

  20. Bam Earthquake in Iran

    CERN Multimedia

    2004-01-01

    Following their request for help from members of international organisations, the permanent Mission of the Islamic Republic of Iran has given the following bank account number, where you can donate money to help the victims of the Bam earthquake. Re: Bam earthquake 235 - UBS 311264.35L Bubenberg Platz 3001 BERN

  1. An Ising model for earthquake dynamics

    Directory of Open Access Journals (Sweden)

    A. Jiménez

    2007-01-01

    Full Text Available This paper focuses on extracting the information contained in seismic space-time patterns and their dynamics. The Greek catalog recorded from 1901 to 1999 is analyzed. An Ising Cellular Automata representation technique is developed to reconstruct the history of these patterns. We find that there is strong correlation in the region, and that small earthquakes are very important to the stress transfers. Finally, it is demonstrated that this approach is useful for seismic hazard assessment and intermediate-range earthquake forecasting.

  2. Demand surge following earthquakes

    Science.gov (United States)

    Olsen, Anna H.

    2012-01-01

    Demand surge is understood to be a socio-economic phenomenon where repair costs for the same damage are higher after large- versus small-scale natural disasters. It has reportedly increased monetary losses by 20 to 50%. In previous work, a model for the increased costs of reconstruction labor and materials was developed for hurricanes in the Southeast United States. The model showed that labor cost increases, rather than the material component, drove the total repair cost increases, and this finding could be extended to earthquakes. A study of past large-scale disasters suggested that there may be additional explanations for demand surge. Two such explanations specific to earthquakes are the exclusion of insurance coverage for earthquake damage and possible concurrent causation of damage from an earthquake followed by fire or tsunami. Additional research into these aspects might provide a better explanation for increased monetary losses after large- vs. small-scale earthquakes.

  3. Evaluating Geometric Characteristics of Planar Surfaces using Improved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Pathak Vimal Kumar

    2017-08-01

    Full Text Available This paper presents a modified particle swarm optimization (MPSO algorithm for the evaluation of geometric characteristics defining form and function of planar surfaces. The geometric features of planar surfaces are decomposed into four components; namely straightness, flatness, perpendicularity, and parallelism. A non-linear minimum zone objective function is formulated mathematically for each planar surface geometric characteristic. Finally, the result of the proposed method is compared with previous work on the same problem and with other nature inspired algorithms. The results demonstrate that the proposed MPSO algorithm is more efficient and accurate in comparison to other algorithms and is well suited for effective and accurate evaluation of planar surface characteristics.

  4. Evaluating Geometric Characteristics of Planar Surfaces using Improved Particle Swarm Optimization

    Science.gov (United States)

    Pathak, Vimal Kumar; Kumar, Sagar; Nayak, Chitresh; Gowripathi Rao, NRNV

    2017-08-01

    This paper presents a modified particle swarm optimization (MPSO) algorithm for the evaluation of geometric characteristics defining form and function of planar surfaces. The geometric features of planar surfaces are decomposed into four components; namely straightness, flatness, perpendicularity, and parallelism. A non-linear minimum zone objective function is formulated mathematically for each planar surface geometric characteristic. Finally, the result of the proposed method is compared with previous work on the same problem and with other nature inspired algorithms. The results demonstrate that the proposed MPSO algorithm is more efficient and accurate in comparison to other algorithms and is well suited for effective and accurate evaluation of planar surface characteristics.

  5. Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization

    Directory of Open Access Journals (Sweden)

    Na Tian

    2015-01-01

    Full Text Available A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.

  6. Self-Assembling Wireless Autonomous Reconfigurable Modules (SWARM) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. and the MIT Space Systems Laboratory propose Self-assembling, Wireless, Autonomous, Reconfigurable Modules (SWARM) as an innovative approach to...

  7. Algorithmic requirements for swarm intelligence in differently coupled collective systems.

    Science.gov (United States)

    Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas

    2013-05-01

    Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments.

  8. SCARF - The Swarm Satellite Constellation Application and Research Facility

    DEFF Research Database (Denmark)

    Olsen, Nils

    2014-01-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, has been launched in November 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, which...... will bring new insights into the Earth system by improving our understanding of the Earth's interior and environment. In order to take advantage of the unique constellation aspect of Swarm, considerably advanced data analysis tools have been developed. Scientific users will also benefit significantly from...... derived products, the so-called Level-2 products, that take into account the features of the constellation. The Swarm SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, has been established with the goal of deriving Level-2 products...

  9. An apparatus to measure electrical charge of bubble swarms.

    Science.gov (United States)

    Uddin, S; Jin, L; Mirnezami, M; Finch, J A

    2013-01-01

    An apparatus has been developed to characterize bubble charge by measuring the swarm potential of gas bubbles. The technique allows in-process measurement of all system variables associated with bubble surface electrical charge: swarm potential, solution conductivity, gas holdup, pH and bubble size distribution. The method was validated by comparing with literature iso-electric point (iep) values. Bubble swarm potential was measured as a function of concentration and pH for a series of non-ionic surfactant frothers, ionic surfactant collectors and multivalent metal ions. Results showed good agreement with established theory and prior experimental findings. The setup is a step towards measurement of charge on flotation size range of bubble swarms. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Trung Dung Ngo

    2011-08-01

    Full Text Available A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  11. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm......A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One...... of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link...

  12. A Markov Chain Approach to Probabilistic Swarm Guidance

    Science.gov (United States)

    Acikmese, Behcet; Bayard, David S.

    2012-01-01

    This paper introduces a probabilistic guidance approach for the coordination of swarms of autonomous agents. The main idea is to drive the swarm to a prescribed density distribution in a prescribed region of the configuration space. In its simplest form, the probabilistic approach is completely decentralized and does not require communication or collabo- ration between agents. Agents make statistically independent probabilistic decisions based solely on their own state, that ultimately guides the swarm to the desired density distribution in the configuration space. In addition to being completely decentralized, the probabilistic guidance approach has a novel autonomous self-repair property: Once the desired swarm density distribution is attained, the agents automatically repair any damage to the distribution without collaborating and without any knowledge about the damage.

  13. Particle swarm inspired optimization algorithm without velocity equation

    Directory of Open Access Journals (Sweden)

    Mahmoud Mostafa El-Sherbiny

    2011-03-01

    Full Text Available This paper introduces Particle Swarm Without Velocity equation optimization algorithm (PSWV that significantly reduces the number of iterations required to reach good solutions for optimization problems. PSWV algorithm uses a set of particles as in particle swarm optimization algorithm but a different mechanism for finding the next position for each particle is used in order to reach a good solution in a minimum number of iterations. In PSWV algorithm, the new position of each particle is determined directly from the result of linear combination between its own best position and the swarm best position without using velocity equation. The results of PSWV algorithm and the results of different variations of particle swarm optimizer are experimentally compared. The performance of PSWV algorithm and the solution quality prove that PSWV is highly competitive and can be considered as a viable alternative to solve optimization problems.

  14. Femto-satellite Swarm State and Density Estimation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is planning future missions involving fleets of small satellites in LEO and GEO that can exhibit autonomous collective behavior. Such a "swarm of...

  15. Stable swarming using adaptive long-range interactions

    Science.gov (United States)

    Gorbonos, Dan; Gov, Nir S.

    2017-04-01

    Sensory mechanisms in biology, from cells to humans, have the property of adaptivity, whereby the response produced by the sensor is adapted to the overall amplitude of the signal, reducing the sensitivity in the presence of strong stimulus, while increasing it when it is weak. This property is inherently energy consuming and a manifestation of the nonequilibrium nature of living organisms. We explore here how adaptivity affects the effective forces that organisms feel due to others in the context of a uniform swarm, in both two and three dimensions. The interactions between the individuals are taken to be attractive and long-range and of power-law form. We find that the effects of adaptivity inside the swarm are dramatic, where the effective forces decrease (or remain constant) with increasing swarm density. Linear stability analysis demonstrates how this property prevents collapse (Jeans instability), when the forces are adaptive. Adaptivity therefore endows swarms with a natural mechanism for self-stabilization.

  16. Extending Particle Swarm Optimisers with Self-Organized Criticality

    DEFF Research Database (Denmark)

    Løvbjerg, Morten; Krink, Thiemo

    2002-01-01

    Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions.......Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions....

  17. Investigating Ground Swarm Robotics Using Agent Based Simulation

    Science.gov (United States)

    2006-12-01

    interesting to see how alternatives like MANA (and even Pythagoras 3 ) measure up to the calling. If indeed MANA has rarely been dedicated to model swarm... Pythagoras is an agent based simulation package developed by Northrop Grumman 5 Figure 2. Simulation packages used to models robot swarms... Pythagoras , an agent based software platform developed by Northrop Grumman. 93 As mentioned before, the model is not complete without modeling the

  18. Information flow principles for plasticity in foraging robot swarms

    OpenAIRE

    Pitonakova, Lenka; Crowder, Richard; Bullock, Seth

    2016-01-01

    An important characteristic of a robot swarm that must operate in the real world is the ability to cope with changeable environments by exhibiting behavioural plasticity at the collective level. For example, a swarm of foraging robots should be able to repeatedly reorganise in order to exploit resource deposits that appear intermittently in different locations throughout their environment. In this paper, we report on simulation experiments with homogeneous foraging robot teams and show that a...

  19. Instantaneous movement of krill swarms in the Antarctic Circumpolar Current

    OpenAIRE

    Tarling, Geraint A.; Thorpe, Sally E.

    2014-01-01

    Antarctic krill are known to have strong swimming capabilities, but direct observations of the speed and direction of krill-swarm movement within their natural environment are rare. We identified and examined 4060 swarms within the main flow of the Antarctic Circumpolar Current (Scotia Sea) using a combination of an EK60 echosounder, a 153.6 kHz acoustic Doppler current profiler, and ground-truthing nets. Net displacement magnitude (m) and net angle of deviation (d) were determined by vector ...

  20. Swarm Robot Systems Based on the Evolution of Personality Traits

    OpenAIRE

    Jr., Sidney Nascimento GIVIGI; SCHWARTZ, Howard M.

    2007-01-01

    Game theory may be very useful in modeling and analyzing swarms of robots. Using game theory in conjunction with traits of personalities, we achieve intelligent swarm robots. Traits of personality are characteristics of each robot that define the robots' behaviours. The environment is represented as a game and due to the evolution of the traits through a learning process, we show how the robots may react intelligently to changes in the environment. A proof of convergence f...

  1. Multi-Robot Motion Planning Using Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Gerasimos G. Rigatos

    2008-11-01

    Full Text Available Swarm intelligence theory is proposed for motion planning of multi-robot systems. Multiple particles start from different points in the solutions space and interact to each other while moving towards the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robotcooperation which works by searching iteratively in regions defined by each robot's best previous move and the best previous move of its neighbors. The method's performance is evaluated through simulation tests.

  2. Multi-Robot Motion Planning Using Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Gerasimos G. Rigatos

    2008-06-01

    Full Text Available Swarm intelligence theory is proposed for motion planning of multi-robot systems. Multiple particles start from different points in the solutions space and interact to each other while moving towards the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robotcooperation which works by searching iteratively in regions defined by each robot's best previous move and the best previous move of its neighbors. The method's performance is evaluated through simulation tests.

  3. The earthquake disaster risk characteristic and the problem in the earthquake emergency rescue of mountainous southwestern Sichuan

    Science.gov (United States)

    Yuan, S.; Xin, C.; Ying, Z.

    2016-12-01

    , outfitting the light and portable rescue equipment, improving the public's self and mutual aid ability. All these measures will help local government reach the final goal of reducing the earthquake disaster.

  4. Monitoring reservoir response to earthquakes and fluid extraction, Salton Sea geothermal field, California.

    Science.gov (United States)

    Taira, Taka'aki; Nayak, Avinash; Brenguier, Florent; Manga, Michael

    2018-01-01

    Continuous monitoring of in situ reservoir responses to stress transients provides insights into the evolution of geothermal reservoirs. By exploiting the stress dependence of seismic velocity changes, we investigate the temporal evolution of the reservoir stress state of the Salton Sea geothermal field (SSGF), California. We find that the SSGF experienced a number of sudden velocity reductions (~0.035 to 0.25%) that are most likely caused by openings of fractures due to dynamic stress transients (as small as 0.08 MPa and up to 0.45 MPa) from local and regional earthquakes. Depths of velocity changes are estimated to be about 0.5 to 1.5 km, similar to the depths of the injection and production wells. We derive an empirical in situ stress sensitivity of seismic velocity changes by relating velocity changes to dynamic stresses. We also observe systematic velocity reductions (0.04 to 0.05%) during earthquake swarms in mid-November 2009 and late-December 2010. On the basis of volumetric static and dynamic stress changes, the expected velocity reductions from the largest earthquakes with magnitude ranging from 3 to 4 in these swarms are less than 0.02%, which suggests that these earthquakes are likely not responsible for the velocity changes observed during the swarms. Instead, we argue that velocity reductions may have been induced by poroelastic opening of fractures due to aseismic deformation. We also observe a long-term velocity increase (~0.04%/year) that is most likely due to poroelastic contraction caused by the geothermal production. Our observations demonstrate that seismic interferometry provides insights into in situ reservoir response to stress changes.

  5. Monitoring reservoir response to earthquakes and fluid extraction, Salton Sea geothermal field, California

    Science.gov (United States)

    Taira, Taka’aki; Nayak, Avinash; Brenguier, Florent; Manga, Michael

    2018-01-01

    Continuous monitoring of in situ reservoir responses to stress transients provides insights into the evolution of geothermal reservoirs. By exploiting the stress dependence of seismic velocity changes, we investigate the temporal evolution of the reservoir stress state of the Salton Sea geothermal field (SSGF), California. We find that the SSGF experienced a number of sudden velocity reductions (~0.035 to 0.25%) that are most likely caused by openings of fractures due to dynamic stress transients (as small as 0.08 MPa and up to 0.45 MPa) from local and regional earthquakes. Depths of velocity changes are estimated to be about 0.5 to 1.5 km, similar to the depths of the injection and production wells. We derive an empirical in situ stress sensitivity of seismic velocity changes by relating velocity changes to dynamic stresses. We also observe systematic velocity reductions (0.04 to 0.05%) during earthquake swarms in mid-November 2009 and late-December 2010. On the basis of volumetric static and dynamic stress changes, the expected velocity reductions from the largest earthquakes with magnitude ranging from 3 to 4 in these swarms are less than 0.02%, which suggests that these earthquakes are likely not responsible for the velocity changes observed during the swarms. Instead, we argue that velocity reductions may have been induced by poroelastic opening of fractures due to aseismic deformation. We also observe a long-term velocity increase (~0.04%/year) that is most likely due to poroelastic contraction caused by the geothermal production. Our observations demonstrate that seismic interferometry provides insights into in situ reservoir response to stress changes. PMID:29326977

  6. Chicken Swarm Optimization Based on Elite Opposition-Based Learning

    Directory of Open Access Journals (Sweden)

    Chiwen Qu

    2017-01-01

    Full Text Available Chicken swarm optimization is a new intelligent bionic algorithm, simulating the chicken swarm searching for food in nature. Basic algorithm is likely to fall into a local optimum and has a slow convergence rate. Aiming at these deficiencies, an improved chicken swarm optimization algorithm based on elite opposition-based learning is proposed. In cock swarm, random search based on adaptive t distribution is adopted to replace that based on Gaussian distribution so as to balance the global exploitation ability and local development ability of the algorithm. In hen swarm, elite opposition-based learning is introduced to promote the population diversity. Dimension-by-dimension greedy search mode is used to do local search for individual of optimal chicken swarm in order to improve optimization precision. According to the test results of 18 standard test functions and 2 engineering structure optimization problems, this algorithm has better effect on optimization precision and speed compared with basic chicken algorithm and other intelligent optimization algorithms.

  7. The safety evaluation of earthquake emergency shelter based on the finite element analysis

    Science.gov (United States)

    Sun, Baitao; Yu, Jingjing; Yan, Peilei

    2017-08-01

    The earthquake emergency shelter is the powerful safeguard to resist the natural hazard, human accident and other accidents, so evaluate the buildings whether can be the earthquake emergency shelter appear to be particularly important. So far the adoptive evaluation system inland has not the united criterion and subjectivity, hence it is necessary to realize the quantitative evaluation. The paper set the example of Nenjiang county to make the safety evaluation, the method is combining the measured project profile and the calculative anti-earthquake performance index, comprehensive assessment the buildings' anti-earthquake redundancy, finally providing the identification results. Initially summary, the safety identification method to earthquake emergency shelter has definite guiding significance.

  8. Multi-Objective Sustainable Operation of the Three Gorges Cascaded Hydropower System Using Multi-Swarm Comprehensive Learning Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Xiang Yu

    2016-06-01

    Full Text Available Optimal operation of hydropower reservoir systems often needs to optimize multiple conflicting objectives simultaneously. The conflicting objectives result in a Pareto front, which is a set of non-dominated solutions. Non-dominated solutions cannot outperform each other on all the objectives. An optimization framework based on the multi-swarm comprehensive learning particle swarm optimization algorithm is proposed to solve the multi-objective operation of hydropower reservoir systems. Through adopting search techniques such as decomposition, mutation and differential evolution, the algorithm tries to derive multiple non-dominated solutions reasonably distributed over the true Pareto front in one single run, thereby facilitating determining the final tradeoff. The long-term sustainable planning of the Three Gorges cascaded hydropower system consisting of the Three Gorges Dam and Gezhouba Dam located on the Yangtze River in China is studied. Two conflicting objectives, i.e., maximizing hydropower generation and minimizing deviation from the outflow lower target to realize the system’s economic, environmental and social benefits during the drought season, are optimized simultaneously. Experimental results demonstrate that the optimization framework helps to robustly derive multiple feasible non-dominated solutions with satisfactory convergence, diversity and extremity in one single run for the case studied.

  9. Earthquakes and emergence

    Science.gov (United States)

    Earthquakes and emerging infections may not have a direct cause and effect relationship like tax evasion and jail, but new evidence suggests that there may be a link between the two human health hazards. Various media accounts have cited a massive 1993 earthquake in Maharashtra as a potential catalyst of the recent outbreak of plague in India that has claimed more than 50 lives and alarmed the world. The hypothesis is that the earthquake may have uprooted underground rat populations that carry the fleas infected with the bacterium that causes bubonic plague and can lead to the pneumonic form of the disease that is spread through the air.

  10. Earthquake engineering in Peru

    Science.gov (United States)

    Vargas, N.J

    1983-01-01

    During the last decade, earthquake engineering research in Peru has been carried out at the Catholic University of Peru and at the Universidad Nacional de Ingeniera (UNI). The Geophysical Institute (IGP) under the auspices of the Organization of American States (OAS) has initiated in Peru other efforts in regional seismic hazard assessment programs with direct impact to the earthquake engineering program. Further details on these programs have been reported by L. Ocola in the Earthquake Information Bulletin, January-February 1982, vol. 14, no. 1, pp. 33-38. 

  11. SWARMS Early Trials Management for The SWARMs ECSEL-H2020 Project

    Science.gov (United States)

    Alcaraz, Daniel; Morales, Tania; Castro, Ayoze; Barrera, Carlos; Hernández, Joaquín; Llinás, Octavio

    2017-04-01

    The work presented on this paper is aimed to explain how the Early Trials of the Project SWARMS were managed in order to complete the first field demonstrations on real environment. SWARMs aims to reduce the operational cost in the use of maritime robots and vehicles, in order to increase the safety of tasks and reduce profesional divers risks. This will be achieved enabling the AUVs/ROVs to work in a cooperative mesh. The challenge is to design and develop an integrated platform (a set of Software/Hardware components), incorporated into the current generation of underwater vehicles in order to improve autonomy, cooperation, robustness, cost-effectiveness, and reliability of the offshore operations. The first demonstration of the project has been performed at PLOCAN (The Oceanic Platform of the Canary Islands) where these technologies were validated on its first stage. The Early Trials have represented the first in situ deployment and test of the novel technologies developed during the initial 14 months of the Project. Going into the sea supposed a huge challenge also in terms of management. The 32 partners of SWARMS had very different requirements (logistics, technical needs, software/computation needs, etc.), and a limited time frame to test and prove their individual developments. In order to fullfill the project objectives, all these tests were divided in 7 missions that were aimed to cover this early demonstration requiements. From PLOCAN, a management protocol was designed in order to cover all the partners needs and make an efficient resource asignment from the begining. These results will be extended to other two demonstrations of the project that forseen to be held in Romania (2017) and Norway (2018).

  12. An atlas of ShakeMaps for selected global earthquakes

    Science.gov (United States)

    Allen, Trevor I.; Wald, David J.; Hotovec, Alicia J.; Lin, Kuo-Wan; Earle, Paul S.; Marano, Kristin D.

    2008-01-01

    An atlas of maps of peak ground motions and intensity 'ShakeMaps' has been developed for almost 5,000 recent and historical global earthquakes. These maps are produced using established ShakeMap methodology (Wald and others, 1999c; Wald and others, 2005) and constraints from macroseismic intensity data, instrumental ground motions, regional topographically-based site amplifications, and published earthquake-rupture models. Applying the ShakeMap methodology allows a consistent approach to combine point observations with ground-motion predictions to produce descriptions of peak ground motions and intensity for each event. We also calculate an estimated ground-motion uncertainty grid for each earthquake. The Atlas of ShakeMaps provides a consistent and quantitative description of the distribution and intensity of shaking for recent global earthquakes (1973-2007) as well as selected historic events. As such, the Atlas was developed specifically for calibrating global earthquake loss estimation methodologies to be used in the U.S. Geological Survey Prompt Assessment of Global Earthquakes for Response (PAGER) Project. PAGER will employ these loss models to rapidly estimate the impact of global earthquakes as part of the USGS National Earthquake Information Center's earthquake-response protocol. The development of the Atlas of ShakeMaps has also led to several key improvements to the Global ShakeMap system. The key upgrades include: addition of uncertainties in the ground motion mapping, introduction of modern ground-motion prediction equations, improved estimates of global seismic-site conditions (VS30), and improved definition of stable continental region polygons. Finally, we have merged all of the ShakeMaps in the Atlas to provide a global perspective of earthquake ground shaking for the past 35 years, allowing comparison with probabilistic hazard maps. The online Atlas and supporting databases can be found at http://earthquake.usgs.gov/eqcenter/shakemap/atlas.php/.

  13. Middleware Design for Swarm-Driving Robots Accompanying Humans

    Directory of Open Access Journals (Sweden)

    Min Su Kim

    2017-02-01

    Full Text Available Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves.

  14. Estimating the macroseismic parameters of earthquakes in eastern Iran

    Science.gov (United States)

    Amini, H.; Gasperini, P.; Zare, M.; Vannucci, G.

    2017-10-01

    Macroseismic intensity values allow assessing the macroseismic parameters of earthquakes such as location, magnitude, and fault orientation. This information is particularly useful for historical earthquakes whose parameters were estimated with low accuracy. Eastern Iran (56°-62°E, 29.5°-35.5°N), which is characterized by several active faults, was selected for this study. Among all earthquakes occurred in this region, only 29 have some macroseismic information. Their intensity values were reported in various intensity scales. After collecting the descriptions, their intensity values were re-estimated in a uniform intensity scale. Thereafter, Boxer method was applied to estimate their corresponding macroseismic parameters. Boxer estimates of macroseismic parameters for instrumental earthquakes (after 1964) were found to be consistent with those published by Global Centroid Moment Tensor Catalog (GCMT). Therefore, this method was applied to estimate location, magnitude, source dimension, and orientation of these earthquakes with macroseismic description in the period 1066-2012. Macroseismic parameters seem to be more reliable than instrumental ones not only for historical earthquakes but also for instrumental earthquakes especially for the ones occurred before 1960. Therefore, as final results of this study we propose to use the macroseismically determined parameters in preparing a catalog for earthquakes before 1960.

  15. Injection-induced earthquakes

    National Research Council Canada - National Science Library

    Ellsworth, William L

    2013-01-01

    ...s. It has long been understood that earthquakes can be induced by impoundment of reservoirs, surface and underground mining, withdrawal of fluids and gas from the subsurface, and injection of fluids...

  16. 1988 Spitak Earthquake Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 1988 Spitak Earthquake database is an extensive collection of geophysical and geological data, maps, charts, images and descriptive text pertaining to the...

  17. Earthquakes and plate tectonics

    Science.gov (United States)

    Spall, H.

    1977-01-01

    The world's earthquakes are not randomly distributed over the Earth's surface. They tend to be concentrated in narrow zones. Why is this? And why are volcanoes and mountain ranges also found in these zones too?

  18. Tweet Earthquake Dispatch (TED)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS is offering earthquake alerts via two twitter accounts: @USGSted and @USGSBigQuakes. On average, @USGSted and @USGSBigQuakes will produce about one tweet...

  19. Earthquake Damage to Schools

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This set of slides graphically illustrates the potential danger that major earthquakes pose to school structures and to the children and adults who happen to be...

  20. Earthquake Ground Motion Selection

    Science.gov (United States)

    2012-05-01

    Nonlinear analyses of soils, structures, and soil-structure systems offer the potential for more accurate characterization of geotechnical and structural response under strong earthquake shaking. The increasing use of advanced performance-based desig...

  1. Exponential decline of aftershocks of the M7.9 1868 great Kau earthquake, Hawaii, through the 20th century

    Science.gov (United States)

    Klein, F.W.; Wright, Tim

    2008-01-01

    The remarkable catalog of Hawaiian earthquakes going back to the 1820s is based on missionary diaries, newspaper accounts, and instrumental records and spans the great M7.9 Kau earthquake of April 1868 and its aftershock sequence. The earthquake record since 1868 defines a smooth curve complete to M5.2 of the declining rate into the 21st century, after five short volcanic swarms are removed. A single aftershock curve fits the earthquake record, even with numerous M6 and 7 main shocks and eruptions. The timing of some moderate earthquakes may be controlled by magmatic stresses, but their overall long-term rate reflects one of aftershocks of the Kau earthquake. The 1868 earthquake is, therefore, the largest and most controlling stress event in the 19th and 20th centuries. We fit both the modified Omori (power law) and stretched exponential (SE) functions to the earthquakes. We found that the modified Omori law is a good fit to the M ??? 5.2 earthquake rate for the first 10 years or so and the more rapidly declining SE function fits better thereafter, as supported by three statistical tests. The switch to exponential decay suggests that a possible change in aftershock physics may occur from rate and state fault friction, with no change in the stress rate, to viscoelastic stress relaxation. The 61-year exponential decay constant is at the upper end of the range of geodetic relaxation times seen after other global earthquakes. Modeling deformation in Hawaii is beyond the scope of this paper, but a simple interpretation of the decay suggests an effective viscosity of 1019 to 1020 Pa s pertains in the volcanic spreading of Hawaii's flanks. The rapid decline in earthquake rate poses questions for seismic hazard estimates in an area that is cited as one of the most hazardous in the United States.

  2. The research and application of earthquake disaster comprehensive evaluation

    Science.gov (United States)

    Guo, Hongmei; Chen, Weifeng

    2017-04-01

    -source heterogeneous earthquake disaster information; to give full play to experts in various fields to achieve long-range real-time disaster expert collaborative judgment; finally realize real-time dynamic correction of earthquake disaster, so as to provide more timely, comprehensive, accurate and detailed earthquake disaster information for earthquake emergency disposal work. The system has been applied in earthquake emergency work of LiTang 4.9 and 5.1 earthquake in sichuan province on September 23, 2016, which provides very important support for earthquake emergency disposal work and intensity mapping.

  3. Prospective Tests of Southern California Earthquake Forecasts

    Science.gov (United States)

    Jackson, D. D.; Schorlemmer, D.; Gerstenberger, M.; Kagan, Y. Y.; Helmstetter, A.; Wiemer, S.; Field, N.

    2004-12-01

    We are testing earthquake forecast models prospectively using likelihood ratios. Several investigators have developed such models as part of the Southern California Earthquake Center's project called Regional Earthquake Likelihood Models (RELM). Various models are based on fault geometry and slip rates, seismicity, geodetic strain, and stress interactions. Here we describe the testing procedure and present preliminary results. Forecasts are expressed as the yearly rate of earthquakes within pre-specified bins of longitude, latitude, magnitude, and focal mechanism parameters. We test models against each other in pairs, which requires that both forecasts in a pair be defined over the same set of bins. For this reason we specify a standard "menu" of bins and ground rules to guide forecasters in using common descriptions. One menu category includes five-year forecasts of magnitude 5.0 and larger. Contributors will be requested to submit forecasts in the form of a vector of yearly earthquake rates on a 0.1 degree grid at the beginning of the test. Focal mechanism forecasts, when available, are also archived and used in the tests. Interim progress will be evaluated yearly, but final conclusions would be made on the basis of cumulative five-year performance. The second category includes forecasts of earthquakes above magnitude 4.0 on a 0.1 degree grid, evaluated and renewed daily. Final evaluation would be based on cumulative performance over five years. Other types of forecasts with different magnitude, space, and time sampling are welcome and will be tested against other models with shared characteristics. Tests are based on the log likelihood scores derived from the probability that future earthquakes would occur where they do if a given forecast were true [Kagan and Jackson, J. Geophys. Res.,100, 3,943-3,959, 1995]. For each pair of forecasts, we compute alpha, the probability that the first would be wrongly rejected in favor of the second, and beta, the probability

  4. Charles Darwin's earthquake reports

    Science.gov (United States)

    Galiev, Shamil

    2010-05-01

    As it is the 200th anniversary of Darwin's birth, 2009 has also been marked as 170 years since the publication of his book Journal of Researches. During the voyage Darwin landed at Valdivia and Concepcion, Chile, just before, during, and after a great earthquake, which demolished hundreds of buildings, killing and injuring many people. Land was waved, lifted, and cracked, volcanoes awoke and giant ocean waves attacked the coast. Darwin was the first geologist to observe and describe the effects of the great earthquake during and immediately after. These effects sometimes repeated during severe earthquakes; but great earthquakes, like Chile 1835, and giant earthquakes, like Chile 1960, are rare and remain completely unpredictable. This is one of the few areas of science, where experts remain largely in the dark. Darwin suggested that the effects were a result of ‘ …the rending of strata, at a point not very deep below the surface of the earth…' and ‘…when the crust yields to the tension, caused by its gradual elevation, there is a jar at the moment of rupture, and a greater movement...'. Darwin formulated big ideas about the earth evolution and its dynamics. These ideas set the tone for the tectonic plate theory to come. However, the plate tectonics does not completely explain why earthquakes occur within plates. Darwin emphasised that there are different kinds of earthquakes ‘...I confine the foregoing observations to the earthquakes on the coast of South America, or to similar ones, which seem generally to have been accompanied by elevation of the land. But, as we know that subsidence has gone on in other quarters of the world, fissures must there have been formed, and therefore earthquakes...' (we cite the Darwin's sentences following researchspace. auckland. ac. nz/handle/2292/4474). These thoughts agree with results of the last publications (see Nature 461, 870-872; 636-639 and 462, 42-43; 87-89). About 200 years ago Darwin gave oneself airs by the

  5. Modelling Oil-Spill Detection with Swarm Drones

    Directory of Open Access Journals (Sweden)

    F. Aznar

    2014-01-01

    Full Text Available Nowadays, swarm robotics research is having a great increase due to the benefits derived from its use, such as robustness, parallelism, and flexibility. Unlike distributed robotic systems, swarm robotics emphasizes a large number of robots, and promotes scalability. Among the multiple applications of such systems we could find are exploring unstructured environments, resource monitoring, or distributed sensing. Two of these applications, monitoring, and perimeter/area detection of a given resource, have several ecological uses. One of them is the detection and monitoring of pollutants to delimit their perimeter and area accurately. Maritime activity has been increasing gradually in recent years. Many ships carry products such as oil that can adversely affect the environment. Such products can produce high levels of pollution in case of being spilled into sea. In this paper we will present a distributed system which monitors, covers, and surrounds a resource by using a swarm of homogeneous low cost drones. These drones only use their local sensory information and do not require any direct communication between them. Taking into account the properties of this kind of oil spills we will present a microscopic model for a swarm of drones, capable of monitoring these spills properly. Furthermore, we will analyse the proper macroscopic operation of the swarm. The analytical and experimental results presented here show the proper evolution of our system.

  6. Hierarchical Swarm Model: A New Approach to Optimization

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2010-01-01

    Full Text Available This paper presents a novel optimization model called hierarchical swarm optimization (HSO, which simulates the natural hierarchical complex system from where more complex intelligence can emerge for complex problems solving. This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. This performance improvement is obtained by constructing the HSO hierarchies, which means that an agent in a higher level swarm can be composed of swarms of other agents from lower level and different swarms of different levels evolve on different spatiotemporal scale. A novel optimization algorithm (named PS2O, based on the HSO model, is instantiated and tested to illustrate the ideas of HSO model clearly. Experiments were conducted on a set of 17 benchmark optimization problems including both continuous and discrete cases. The results demonstrate remarkable performance of the PS2O algorithm on all chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms.

  7. Swarms of repeating stick-slip glacierquakes triggered by snow loading at Mount Rainier volcano

    Science.gov (United States)

    Allstadt, K.; Malone, S. D.; Shean, D. E.; Fahnestock, M. A.; Vidale, J. E.

    2013-12-01

    We have detected over 150,000 low-frequency (~1-5 Hz) repeating earthquakes over the past decade at Mount Rainier volcano by scanning continuous seismic data from the permanent seismic network. Most of these were previously undetected due to their small size (M3000 m) on the glacier-covered part of the edifice. They occur primarily in week- to month-long swarms of activity that strongly correlate with precipitation, namely snowfall, with a lag of about 1-2 days. Furthermore, there is a linear relationship between inter-event repeat time and the size of the subsequent event - consistent with slip-predictable stick-slip behavior. This pattern suggests that the additional load imparted by the sudden added weight of snow during winter storms triggers a temporary change from smooth aseismic sliding to seismic stick-slip basal sliding in locations where basal conditions are close to frictional instability. This sensitivity is analogous to the triggering of repeating earthquakes due to tiny overall stress changes in more traditional tectonic environments (e.g., tremor modulated by tides, dynamic triggering of repeating earthquakes). Using codawave interferometry on stacks of the repeating waveforms of the families with the most events, we found that the sources move at speeds of ~1 m/day. Using a GAMMA ground based radar interferometer, we collected spatially continuous line-of-sight velocities of several glaciers at Mount Rainier in both summer and late fall. We found that the faster parts of the glaciers also move at ~1 m/day or faster, even in late fall. Movement of the sources of these repeating earthquakes at glacial speeds indicates that the asperities are dirty patches that move with the ice rather than stationary bedrock bumps. The reappearance of some event families up to several years apart suggests that certain areas at the base of certain glaciers are prodigious producers of conditions favorable to this behavior. Stick-slip basal sliding of glaciers is

  8. Swarm prevention and spring treatment against Varroa destructor in honey bee colonies (Apis mellifera)

    NARCIS (Netherlands)

    Cornelissen, B.; Gerritsen, L.J.M.

    2006-01-01

    In 2004 and 2005 experiments were carried out to test the efficacy and efficiency of Varroa control combined with swarm prevention methods in spring. Honey bee colonies were split in an artificial swarm and a brood carrier. Hereafter the swarms were treated with oxalic acid and the brood carriers

  9. Volcano-tectonic earthquakes: A new tool for estimating intrusive volumes and forecasting eruptions

    Science.gov (United States)

    White, Randall A.; McCausland, Wendy

    2016-01-01

    We present data on 136 high-frequency earthquakes and swarms, termed volcano-tectonic (VT) seismicity, which preceded 111 eruptions at 83 volcanoes, plus data on VT swarms that preceded intrusions at 21 other volcanoes. We find that VT seismicity is usually the earliest reported seismic precursor for eruptions at volcanoes that have been dormant for decades or more, and precedes eruptions of all magma types from basaltic to rhyolitic and all explosivities from VEI 0 to ultraplinian VEI 6 at such previously long-dormant volcanoes. Because large eruptions occur most commonly during resumption of activity at long-dormant volcanoes, VT seismicity is an important precursor for the Earth's most dangerous eruptions. VT seismicity precedes all explosive eruptions of VEI ≥ 5 and most if not all VEI 4 eruptions in our data set. Surprisingly we find that the VT seismicity originates at distal locations on tectonic fault structures at distances of one or two to tens of kilometers laterally from the site of the eventual eruption, and rarely if ever starts beneath the eruption site itself. The distal VT swarms generally occur at depths almost equal to the horizontal distance of the swarm from the summit out to about 15 km distance, beyond which hypocenter depths level out. We summarize several important characteristics of this distal VT seismicity including: swarm-like nature, onset days to years prior to the beginning of magmatic eruptions, peaking of activity at the time of the initial eruption whether phreatic or magmatic, and large non-double couple component to focal mechanisms. Most importantly we show that the intruded magma volume can be simply estimated from the cumulative seismic moment of the VT seismicity from:

  10. Characterizing Offshore Earthquakes at Hawaii Recorded by the First PLUME Temporary Ocean-Bottom Seismometer Network

    Science.gov (United States)

    Anchieta, M. C.; Wolfe, C. J.; Laske, G.; Collins, J. A.; Solomon, S. C.; Detrick, R. S.; Orcutt, J. A.; Bercovici, D. A.; Hauri, E. H.; Pavlis, G. L.; Eakins, J. A.; Vernon, F. L.

    2007-12-01

    In 2005-2006 and again in 2006-2007, the Plume-Lithosphere Undersea Melt Experiment (PLUME) deployed successive networks of ocean-bottom seismometers (OBSs) around the Hawaiian Islands. The experiment consisted of a 2-year deployment of broadband land seismometers and two year-long deployments of broadband OBSs, the first with a station spacing of about 75 km centered on the island of Hawaii and the second with larger spacing of about 200 km. PLUME's major objective was to determine the mantle structure beneath the Hawaiian hotspot and swell; however, these unique data are also potentially valuable to the study of small offshore earthquakes. The Hawaiian Islands are marked by significant and continuous seismic activity. In addition to the thousands of microearthquakes that are detected and located by the USGS Hawaiian Volcano Observatory (HVO) seismic network each year, Hawaii also experiences occasional large, damaging earthquakes. Several of these large events occurred in Hawaii's offshore region (e.g., the 1871 Lanai earthquake, the 1938 Maui earthquake, and the 2006 Kiholo Bay earthquake), and such events pose a significant seismic hazard for the state. We assess whether data from the first PLUME OBS deployment and land data can improve the detection and location of offshore microearthquakes around Hawaii. We are particularly interested in whether the PLUME data set may reveal offshore fault zones not detected to date by the HVO seismic network. Initial tests indicate that many offshore earthquakes already in the HVO catalog produce detectable P and S waves on the PLUME three- component seismometers, and earthquake detection rates are improved when seismograms are high-pass filtered above about 5 Hz to reduce the seismic noise from wind-generated waves. Differential pressure gauge data yield far fewer detectable events (with the exception of a swarm of Loihi earthquakes in December 2005) and appear less promising for improving our knowledge of offshore

  11. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  12. A Novel Distributed Quantum-Behaved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Yangyang Li

    2017-01-01

    Full Text Available Quantum-behaved particle swarm optimization (QPSO is an improved version of particle swarm optimization (PSO and has shown superior performance on many optimization problems. But for now, it may not always satisfy the situations. Nowadays, problems become larger and more complex, and most serial optimization algorithms cannot deal with the problem or need plenty of computing cost. Fortunately, as an effective model in dealing with problems with big data which need huge computation, MapReduce has been widely used in many areas. In this paper, we implement QPSO on MapReduce model and propose MapReduce quantum-behaved particle swarm optimization (MRQPSO which achieves parallel and distributed QPSO. Comparisons are made between MRQPSO and QPSO on some test problems and nonlinear equation systems. The results show that MRQPSO could complete computing task with less time. Meanwhile, from the view of optimization performance, MRQPSO outperforms QPSO in many cases.

  13. Composite Particle Swarm Optimizer With Historical Memory for Function Optimization.

    Science.gov (United States)

    Li, Jie; Zhang, JunQi; Jiang, ChangJun; Zhou, MengChu

    2015-10-01

    Particle swarm optimization (PSO) algorithm is a population-based stochastic optimization technique. It is characterized by the collaborative search in which each particle is attracted toward the global best position (gbest) in the swarm and its own best position (pbest). However, all of particles' historical promising pbests in PSO are lost except their current pbests. In order to solve this problem, this paper proposes a novel composite PSO algorithm, called historical memory-based PSO (HMPSO), which uses an estimation of distribution algorithm to estimate and preserve the distribution information of particles' historical promising pbests. Each particle has three candidate positions, which are generated from the historical memory, particles' current pbests, and the swarm's gbest. Then the best candidate position is adopted. Experiments on 28 CEC2013 benchmark functions demonstrate the superiority of HMPSO over other algorithms.

  14. Recent advances in swarm intelligence and evolutionary computation

    CERN Document Server

    2015-01-01

    This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

  15. A Diversity-Guided Particle Swarm Optimizer - the ARPSO

    DEFF Research Database (Denmark)

    Vesterstrøm, Jacob Svaneborg; Riget, Jacques

    2002-01-01

    The particle swarm optimization (PSO) algorithm is a new population based search strat- egy, which has exhibited good performance on well-known numerical test problems. How- ever, on strongly multi-modal test problems the PSO tends to suffer from premature convergence. This is due to a decrease......) in trying to overcome the problem of premature convergence. It uses a diversity measure to control the swarm. The result is an algorithm that alternates between phases of attraction and repulsion. The performance of the ARPSO is compared to a basic PSO (bPSO) and a genetic algorithm (GA). The results show...... that the ARPSO prevents premature convergence to a high degree, but still keeps a rapid convergence like the basic PSO. Thus, it clearly outperforms the basic PSO as well as the implemented GA in multi-modal optimization. Keywords Particle Swarm Optimization, Diversity-Guided Search 1 Introduction The PSO model...

  16. A Novel Particle Swarm Optimization Algorithm for Global Optimization.

    Science.gov (United States)

    Wang, Chun-Feng; Liu, Kui

    2016-01-01

    Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms.

  17. Particle swarm optimization with composite particles in dynamic environments.

    Science.gov (United States)

    Liu, Lili; Yang, Shengxiang; Wang, Dingwei

    2010-12-01

    In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a "worst first" principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.

  18. Implementasi Algoritma Particle Swarm untuk Menyelesaikan Sistem Persamaan Nonlinear

    Directory of Open Access Journals (Sweden)

    Ardiana Rosita

    2012-09-01

    Full Text Available Penyelesaian sistem persamaan nonlinear merupakan salah satu permasalahan yang sulit pada komputasi numerik dan berbagai aplikasi teknik. Beberapa metode telah dikembangkan untuk menyelesaikan sistem persamaan ini dan metode Newton merupakan metode yang paling sering digunakan. Namun metode ini memerlukan perkiraan solusi awal dan memilih perkiraan solusi awal yang baik untuk sebagian besar sistem persamaan nonlinear tidaklah mudah. Pada makalah ini, algoritma Particle Swarm yang diusulkan oleh Jaberipour dan kawan-kawan[1] diimplementasikan. Algoritma ini merupakan pengembangan dari algoritma Particle Swarm Optimization (PSO. Algoritma ini meyelesaikan sistem persamaan nonlinear yang sebelumnya telah diubah menjadi permasalahan optimasi. Uji coba dilakukan terhadap beberapa fungsi dan sistem persamaan nonlinear untuk menguji kinerja dan efisiensi algoritma. Berdasarkan hasil uji coba, beberapa fungsi dan sistem persamaan nonlinear telah konvergen pada iterasi ke 10 sampai 20 dan terdapat fungsi yang konvergen pada iterasi ke 200. Selain itu, solusi yang dihasilkan algoritma Particle Swarm mendekati solusi eksak.

  19. Modified Particle Swarm Optimization using Nonlinear Decreased Inertia Weight

    Directory of Open Access Journals (Sweden)

    Alrijadjis .

    2016-04-01

    Full Text Available Particle Swarm Optimization (PSO has demonstrated great performance in various optimization problems. However, PSO has weaknesses, namely premature convergence and easy to get stuck or fall into local optima for complex multimodal problems. One of the causes of these weaknesses is unbalance between exploration and exploitation ability in PSO. This paper proposes a Modified Particle Swarm Optimization (MPSO using nonlinearly decreased inertia weight called MPSO-NDW to improve the balance. The key idea of the proposed method is to control the period and decreasing rate of exploration-exploitation ability. The investigation with three famous benchmark functions shows that the accuracy, success rate, and convergence speed of the proposed MPSO-NDW is better than the common used PSO with linearly decreased inertia weight or called PSO-LDW Keywords: particle swarm optimization (PSO, premature convergence, local optima, exploration ability, exploitation ability.

  20. Estimation of Valve Stiction Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    S. Sivagamasundari

    2011-06-01

    Full Text Available This paper presents a procedure for quantifying valve stiction in control loops based on particle swarm optimization. Measurements of the Process Variable (PV and Controller Output (OP are used to estimate the parameters of a Hammerstein system, consisting of connection of a non linear control valve stiction model and a linear process model. The parameters of the Hammerstein model are estimated using particle swarm optimization, from the input-output data by minimizing the error between the true model output and the identified model output. Using particle swarm optimization, Hammerstein models with known nonlinear structure and unknown parameters can be identified. A cost-effective optimization technique is adopted to find the best valve stiction models representing a more realistic valve behavior in the oscillating loop. Simulation and practical laboratory control system results are included, which demonstrates the effectiveness and robustness of the identification scheme.

  1. Distinguishing high surf from volcanic long-period earthquakes

    Science.gov (United States)

    Lyons, John; Haney, Matt; Fee, David; Paskievitch, John F.

    2014-01-01

    Repeating long-period (LP) earthquakes are observed at active volcanoes worldwide and are typically attributed to unsteady pressure fluctuations associated with fluid migration through the volcanic plumbing system. Nonvolcanic sources of LP signals include ice movement and glacial outburst floods, and the waveform characteristics and frequency content of these events often make them difficult to distinguish from volcanic LP events. We analyze seismic and infrasound data from an LP swarm recorded at Pagan volcano on 12–14 October 2013 and compare the results to ocean wave data from a nearby buoy. We demonstrate that although the events show strong similarity to volcanic LP signals, the events are not volcanic but due to intense surf generated by a passing typhoon. Seismo-acoustic methods allow for rapid distinction of volcanic LP signals from those generated by large surf and other sources, a critical task for volcano monitoring.

  2. Earthquake impact scale

    Science.gov (United States)

    Wald, D.J.; Jaiswal, K.S.; Marano, K.D.; Bausch, D.

    2011-01-01

    With the advent of the USGS prompt assessment of global earthquakes for response (PAGER) system, which rapidly assesses earthquake impacts, U.S. and international earthquake responders are reconsidering their automatic alert and activation levels and response procedures. To help facilitate rapid and appropriate earthquake response, an Earthquake Impact Scale (EIS) is proposed on the basis of two complementary criteria. On the basis of the estimated cost of damage, one is most suitable for domestic events; the other, on the basis of estimated ranges of fatalities, is generally more appropriate for global events, particularly in developing countries. Simple thresholds, derived from the systematic analysis of past earthquake impact and associated response levels, are quite effective in communicating predicted impact and response needed after an event through alerts of green (little or no impact), yellow (regional impact and response), orange (national-scale impact and response), and red (international response). Corresponding fatality thresholds for yellow, orange, and red alert levels are 1, 100, and 1,000, respectively. For damage impact, yellow, orange, and red thresholds are triggered by estimated losses reaching $1M, $100M, and $1B, respectively. The rationale for a dual approach to earthquake alerting stems from the recognition that relatively high fatalities, injuries, and homelessness predominate in countries in which local building practices typically lend themselves to high collapse and casualty rates, and these impacts lend to prioritization for international response. In contrast, financial and overall societal impacts often trigger the level of response in regions or countries in which prevalent earthquake resistant construction practices greatly reduce building collapse and resulting fatalities. Any newly devised alert, whether economic- or casualty-based, should be intuitive and consistent with established lexicons and procedures. Useful alerts should

  3. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

    We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

  4. Rupture, waves and earthquakes

    Science.gov (United States)

    UENISHI, Koji

    2017-01-01

    Normally, an earthquake is considered as a phenomenon of wave energy radiation by rupture (fracture) of solid Earth. However, the physics of dynamic process around seismic sources, which may play a crucial role in the occurrence of earthquakes and generation of strong waves, has not been fully understood yet. Instead, much of former investigation in seismology evaluated earthquake characteristics in terms of kinematics that does not directly treat such dynamic aspects and usually excludes the influence of high-frequency wave components over 1 Hz. There are countless valuable research outcomes obtained through this kinematics-based approach, but “extraordinary” phenomena that are difficult to be explained by this conventional description have been found, for instance, on the occasion of the 1995 Hyogo-ken Nanbu, Japan, earthquake, and more detailed study on rupture and wave dynamics, namely, possible mechanical characteristics of (1) rupture development around seismic sources, (2) earthquake-induced structural failures and (3) wave interaction that connects rupture (1) and failures (2), would be indispensable. PMID:28077808

  5. Rupture, waves and earthquakes.

    Science.gov (United States)

    Uenishi, Koji

    2017-01-01

    Normally, an earthquake is considered as a phenomenon of wave energy radiation by rupture (fracture) of solid Earth. However, the physics of dynamic process around seismic sources, which may play a crucial role in the occurrence of earthquakes and generation of strong waves, has not been fully understood yet. Instead, much of former investigation in seismology evaluated earthquake characteristics in terms of kinematics that does not directly treat such dynamic aspects and usually excludes the influence of high-frequency wave components over 1 Hz. There are countless valuable research outcomes obtained through this kinematics-based approach, but "extraordinary" phenomena that are difficult to be explained by this conventional description have been found, for instance, on the occasion of the 1995 Hyogo-ken Nanbu, Japan, earthquake, and more detailed study on rupture and wave dynamics, namely, possible mechanical characteristics of (1) rupture development around seismic sources, (2) earthquake-induced structural failures and (3) wave interaction that connects rupture (1) and failures (2), would be indispensable.

  6. Swarm intelligence metaheuristics for enhanced data analysis and optimization.

    Science.gov (United States)

    Hanrahan, Grady

    2011-09-21

    The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

  7. MARTIAN SWARM EXPLORATION AND MAPPING USING LASER SLAM

    Directory of Open Access Journals (Sweden)

    S. Nowak

    2013-08-01

    Full Text Available In order to explore planet Mars in detail and search for extra-terrestrial life the observation from orbit is not sufficient. To realize complex exploration tasks the use of automatic operating robots with a robust fault-tolerant method of navigation, independent of any infrastructure is a possibility. This work includes a concept of rotary-wing Unmanned Aerial Vehicles (UAVs and Unmanned Ground Vehicles (UGVs for Martian exploration in a swarm. Besides the scenario of Martian surrounding, with a small number of distinctive landmarks, the challenge consists of a Simultaneous Localization and Mapping (SLAM concept using laser data of all swarm members.

  8. Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

    Science.gov (United States)

    Rahmalia, Dinita

    2017-08-01

    Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

  9. Parameter estimation for chaotic systems using improved bird swarm algorithm

    Science.gov (United States)

    Xu, Chuangbiao; Yang, Renhuan

    2017-12-01

    Parameter estimation of chaotic systems is an important problem in nonlinear science and has aroused increasing interest of many research fields, which can be basically reduced to a multidimensional optimization problem. In this paper, an improved boundary bird swarm algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the good global convergence and robustness of the bird swarm algorithm and the exploitation capability of improved boundary learning strategy. Experiments are conducted on the Lorenz system and the coupling motor system. Numerical simulation results reveal the effectiveness and with desirable performance of IBBSA for parameter estimation of chaotic systems.

  10. Gravity inversion of a fault by Particle swarm optimization (PSO).

    Science.gov (United States)

    Toushmalani, Reza

    2013-01-01

    Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult optimization problems. The technique proved to work efficiently when tested to a number of models.

  11. Optimal PMU Placement By Improved Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Rather, Zakir Hussain; Liu, Leo; Chen, Zhe

    2013-01-01

    This paper presents an improved method of binary particle swarm optimization (IBPSO) technique for optimal phasor measurement unit (PMU) placement in a power network for complete system observability. Various effective improvements have been proposed to enhance the efficiency and convergence rate...... of conventional particle swarm optimization method. The proposed method of IBPSO ensures optimal PMU placement with and without consideration of zero injection measurements. The proposed method has been applied to standard test systems like 17 bus, IEEE 24-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus system...

  12. Nonlinear Adaptive Filters based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Faten BEN ARFIA

    2009-07-01

    Full Text Available This paper presents a particle swarm optimization (PSO algorithm to adjust the parameters of the nonlinear filter and to make this type of the filters more powerful for the elimination of the Gaussian noise and also the impulse noise. In this paper we apply the particle swarm optimization to the rational filters and we completed this work with the comparison between our results and other adaptive nonlinear filters like the LMS adaptive median filters and the no-adaptive rational filter.

  13. Robotic swarm concept for efficient oil spill confrontation.

    Science.gov (United States)

    Kakalis, Nikolaos M P; Ventikos, Yiannis

    2008-06-15

    This paper examines the behaviour of a distributed system/robotic swarm concept for the effective confrontation of oil spills. The system described consists of a number of identical robotic units of high-power autonomy that recover oil mechanically and are able to communicate with each other. A mathematical model that accounts for a multitude of oil weathering processes and for the concerted action of the autonomous units is implemented for this investigation. Computational assessment of the robotic swarm in weathering oil spills indicates the potential effectiveness of the method.

  14. Earthquake Damage to Transportation Systems

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Earthquakes represent one of the most destructive natural hazards known to man. A serious result of large-magnitude earthquakes is the disruption of transportation...

  15. An autocorrelation method to detect low frequency earthquakes within tremor

    Science.gov (United States)

    Brown, J.R.; Beroza, G.C.; Shelly, D.R.

    2008-01-01

    Recent studies have shown that deep tremor in the Nankai Trough under western Shikoku consists of a swarm of low frequency earthquakes (LFEs) that occur as slow shear slip on the down-dip extension of the primary seismogenic zone of the plate interface. The similarity of tremor in other locations suggests a similar mechanism, but the absence of cataloged low frequency earthquakes prevents a similar analysis. In this study, we develop a method for identifying LFEs within tremor. The method employs a matched-filter algorithm, similar to the technique used to infer that tremor in parts of Shikoku is comprised of LFEs; however, in this case we do not assume the origin times or locations of any LFEs a priori. We search for LFEs using the running autocorrelation of tremor waveforms for 6 Hi-Net stations in the vicinity of the tremor source. Time lags showing strong similarity in the autocorrelation represent either repeats, or near repeats, of LFEs within the tremor. We test the method on an hour of Hi-Net recordings of tremor and demonstrates that it extracts both known and previously unidentified LFEs. Once identified, we cross correlate waveforms to measure relative arrival times and locate the LFEs. The results are able to explain most of the tremor as a swarm of LFEs and the locations of newly identified events appear to fill a gap in the spatial distribution of known LFEs. This method should allow us to extend the analysis of Shelly et al. (2007a) to parts of the Nankai Trough in Shikoku that have sparse LFE coverage, and may also allow us to extend our analysis to other regions that experience deep tremor, but where LFEs have not yet been identified. Copyright 2008 by the American Geophysical Union.

  16. a Collaborative Cyberinfrastructure for Earthquake Seismology

    Science.gov (United States)

    Bossu, R.; Roussel, F.; Mazet-Roux, G.; Lefebvre, S.; Steed, R.

    2013-12-01

    One of the challenges in real time seismology is the prediction of earthquake's impact. It is particularly true for moderate earthquake (around magnitude 6) located close to urbanised areas, where the slightest uncertainty in event location, depth, magnitude estimates, and/or misevaluation of propagation characteristics, site effects and buildings vulnerability can dramatically change impact scenario. The Euro-Med Seismological Centre (EMSC) has developed a cyberinfrastructure to collect observations from eyewitnesses in order to provide in-situ constraints on actual damages. This cyberinfrastructure takes benefit of the natural convergence of earthquake's eyewitnesses on EMSC website (www.emsc-csem.org), the second global earthquake information website within tens of seconds of the occurrence of a felt event. It includes classical crowdsourcing tools such as online questionnaires available in 39 languages, and tools to collect geolocated pics. It also comprises information derived from the real time analysis of the traffic on EMSC website, a method named flashsourcing; In case of a felt earthquake, eyewitnesses reach EMSC website within tens of seconds to find out the cause of the shaking they have just been through. By analysing their geographical origin through their IP address, we automatically detect felt earthquakes and in some cases map the damaged areas through the loss of Internet visitors. We recently implemented a Quake Catcher Network (QCN) server in collaboration with Stanford University and the USGS, to collect ground motion records performed by volunteers and are also involved in a project to detect earthquakes from ground motions sensors from smartphones. Strategies have been developed for several social media (Facebook, Twitter...) not only to distribute earthquake information, but also to engage with the Citizens and optimise data collection. A smartphone application is currently under development. We will present an overview of this

  17. Earthquake Hazard and Risk Assessment Based on Unified Scaling Law for Earthquakes: State of Gujarat, India

    Science.gov (United States)

    Parvez, Imtiyaz A.; Nekrasova, Anastasia; Kossobokov, Vladimir

    2017-03-01

    The Gujarat state of India is one of the most seismically active intercontinental regions of the world. Historically, it has experienced many damaging earthquakes including the devastating 1819 Rann of Kachchh and 2001 Bhuj earthquakes. The effect of the later one is grossly underestimated by the Global Seismic Hazard Assessment Program (GSHAP). To assess a more adequate earthquake hazard for the state of Gujarat, we apply Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter recurrence relation taking into account naturally fractal distribution of earthquake loci. USLE has evident implications since any estimate of seismic hazard depends on the size of the territory considered and, therefore, may differ dramatically from the actual one when scaled down to the proportion of the area of interest (e.g. of a city) from the enveloping area of investigation. We cross-compare the seismic hazard maps compiled for the same standard regular grid 0.2° × 0.2° (1) in terms of design ground acceleration based on the neo-deterministic approach, (2) in terms of probabilistic exceedance of peak ground acceleration by GSHAP, and (3) the one resulted from the USLE application. Finally, we present the maps of seismic risks for the state of Gujarat integrating the obtained seismic hazard, population density based on India's Census 2011 data, and a few model assumptions of vulnerability.

  18. Earthquake prediction with electromagnetic phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Hayakawa, Masashi, E-mail: hayakawa@hi-seismo-em.jp [Hayakawa Institute of Seismo Electomagnetics, Co. Ltd., University of Electro-Communications (UEC) Incubation Center, 1-5-1 Chofugaoka, Chofu Tokyo, 182-8585 (Japan); Advanced Wireless & Communications Research Center, UEC, Chofu Tokyo (Japan); Earthquake Analysis Laboratory, Information Systems Inc., 4-8-15, Minami-aoyama, Minato-ku, Tokyo, 107-0062 (Japan); Fuji Security Systems. Co. Ltd., Iwato-cho 1, Shinjyuku-ku, Tokyo (Japan)

    2016-02-01

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary.

  19. Organizational changes at Earthquakes & Volcanoes

    Science.gov (United States)

    Gordon, David W.

    1992-01-01

    Primary responsibility for the preparation of Earthquakes & Volcanoes within the Geological Survey has shifted from the Office of Scientific Publications to the Office of Earthquakes, Volcanoes, and Engineering (OEVE). As a consequence of this reorganization, Henry Spall has stepepd down as Science Editor for Earthquakes & Volcanoes(E&V).

  20. Quantum-behaved particle swarm optimization: analysis of individual particle behavior and parameter selection.

    Science.gov (United States)

    Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo

    2012-01-01

    Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.

  1. A Time-Domain Structural Damage Detection Method Based on Improved Multiparticle Swarm Coevolution Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Shao-Fei Jiang

    2014-01-01

    Full Text Available Optimization techniques have been applied to structural health monitoring and damage detection of civil infrastructures for two decades. The standard particle swarm optimization (PSO is easy to fall into the local optimum and such deficiency also exists in the multiparticle swarm coevolution optimization (MPSCO. This paper presents an improved MPSCO algorithm (IMPSCO firstly and then integrates it with Newmark’s algorithm to localize and quantify the structural damage by using the damage threshold proposed. To validate the proposed method, a numerical simulation and an experimental study of a seven-story steel frame were employed finally, and a comparison was made between the proposed method and the genetic algorithm (GA. The results show threefold: (1 the proposed method not only is capable of localization and quantification of damage, but also has good noise-tolerance; (2 the damage location can be accurately detected using the damage threshold proposed in this paper; and (3 compared with the GA, the IMPSCO algorithm is more efficient and accurate for damage detection problems in general. This implies that the proposed method is applicable and effective in the community of damage detection and structural health monitoring.

  2. The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Wenfu Xu

    2008-09-01

    Full Text Available The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO algorithm to search the unknown parameters. The approach has the following traits: 1 The limits on joint angles, rates and accelerations are included in the planning algorithm; 2 There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3 The attitude singularities do not exist, for the orientation is represented by quaternion; 4 The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.

  3. The Cartesian Path Planning of Free- Floating Space Robot using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Yangsheng Xu

    2008-11-01

    Full Text Available The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO algorithm to search the unknown parameters. The approach has the following traits: 1 The limits on joint angles, rates and accelerations are included in the planning algorithm; 2 There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3 The attitude singularities do not exist, for the orientation is represented by quaternion; 4 The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.

  4. A New Hybrid Nelder-Mead Particle Swarm Optimization for Coordination Optimization of Directional Overcurrent Relays

    Directory of Open Access Journals (Sweden)

    An Liu

    2012-01-01

    Full Text Available Coordination optimization of directional overcurrent relays (DOCRs is an important part of an efficient distribution system. This optimization problem involves obtaining the time dial setting (TDS and pickup current (Ip values of each DOCR. The optimal results should have the shortest primary relay operating time for all fault lines. Recently, the particle swarm optimization (PSO algorithm has been considered an effective tool for linear/nonlinear optimization problems with application in the protection and coordination of power systems. With a limited runtime period, the conventional PSO considers the optimal solution as the final solution, and an early convergence of PSO results in decreased overall performance and an increase in the risk of mistaking local optima for global optima. Therefore, this study proposes a new hybrid Nelder-Mead simplex search method and particle swarm optimization (proposed NM-PSO algorithm to solve the DOCR coordination optimization problem. PSO is the main optimizer, and the Nelder-Mead simplex search method is used to improve the efficiency of PSO due to its potential for rapid convergence. To validate the proposal, this study compared the performance of the proposed algorithm with that of PSO and original NM-PSO. The findings demonstrate the outstanding performance of the proposed NM-PSO in terms of computation speed, rate of convergence, and feasibility.

  5. A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Lizhi Cui

    2014-01-01

    Full Text Available This paper proposes a separation method, based on the model of Generalized Reference Curve Measurement and the algorithm of Particle Swarm Optimization (GRCM-PSO, for the High Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD data set. Firstly, initial parameters are generated to construct reference curves for the chromatogram peaks of the compounds based on its physical principle. Then, a General Reference Curve Measurement (GRCM model is designed to transform these parameters to scalar values, which indicate the fitness for all parameters. Thirdly, rough solutions are found by searching individual target for every parameter, and reinitialization only around these rough solutions is executed. Then, the Particle Swarm Optimization (PSO algorithm is adopted to obtain the optimal parameters by minimizing the fitness of these new parameters given by the GRCM model. Finally, spectra for the compounds are estimated based on the optimal parameters and the HPLC-DAD data set. Through simulations and experiments, following conclusions are drawn: (1 the GRCM-PSO method can separate the chromatogram peaks and spectra from the HPLC-DAD data set without knowing the number of the compounds in advance even when severe overlap and white noise exist; (2 the GRCM-PSO method is able to handle the real HPLC-DAD data set.

  6. State Feedback H∞ Control of Power Units Based on an Improved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Zhongqiang Wu

    2015-01-01

    Full Text Available A new state feedback H∞ control scheme is presented used in the boiler-turbine power units based on an improved particle swarm optimizing algorithm. Firstly, the nonlinear system is transformed into a linear time-varying system; then the H∞ control problem is transformed into the solution of a Riccati equation. The control effect of H∞ controller depends on the selection of matrix P, so an improved particle swarm optimizing (PSO algorithm by introducing differential evolution algorithm is used to solve the Riccati equation. The main purpose is that mutation and crossover are introduced for a new population, and the population diversity is improved. It is beneficial to eliminate stagnation caused by premature convergence, and the algorithm convergence rate is improved. Finally, the real-time optimizing of the controller parameters is realized. Theoretical analysis and simulation results show that a state feedback H∞ controller can be obtained, which can ensure asymptotic stability of the system, and the double objectives of stabilizing system and suppressing the disturbance are got. The system can work well over a large range working point.

  7. Research on Multiaircraft Cooperative Suppression Interference Array Based on an Improved Multiobjective Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Huan Zhang

    2017-01-01

    Full Text Available For the problem of multiaircraft cooperative suppression interference array (MACSIA against the enemy air defense radar network in electronic warfare mission planning, firstly, the concept of route planning security zone is proposed and the solution to get the minimum width of security zone based on mathematical morphology is put forward. Secondly, the minimum width of security zone and the sum of the distance between each jamming aircraft and the center of radar network are regarded as objective function, and the multiobjective optimization model of MACSIA is built, and then an improved multiobjective particle swarm optimization algorithm is used to solve the model. The decomposition mechanism is adopted and the proportional distribution is used to maintain diversity of the new found nondominated solutions. Finally, the Pareto optimal solutions are analyzed by simulation, and the optimal MACSIA schemes of each jamming aircraft suppression against the enemy air defense radar network are obtained and verify that the built multiobjective optimization model is corrected. It also shows that the improved multiobjective particle swarm optimization algorithm for solving the problem of MACSIA is feasible and effective.

  8. Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

    Directory of Open Access Journals (Sweden)

    Wang Chun-Feng

    2014-01-01

    Full Text Available Artificial bee colony (ABC algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.

  9. A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Biwei Tang

    2016-01-01

    Full Text Available This paper develops a particle swarm optimization (PSO based framework for constrained optimization problems (COPs. Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011 algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs.

  10. Sensing the earthquake

    Science.gov (United States)

    Bichisao, Marta; Stallone, Angela

    2017-04-01

    Making science visual plays a crucial role in the process of building knowledge. In this view, art can considerably facilitate the representation of the scientific content, by offering a different perspective on how a specific problem could be approached. Here we explore the possibility of presenting the earthquake process through visual dance. From a choreographer's point of view, the focus is always on the dynamic relationships between moving objects. The observed spatial patterns (coincidences, repetitions, double and rhythmic configurations) suggest how objects organize themselves in the environment and what are the principles underlying that organization. The identified set of rules is then implemented as a basis for the creation of a complex rhythmic and visual dance system. Recently, scientists have turned seismic waves into sound and animations, introducing the possibility of "feeling" the earthquakes. We try to implement these results into a choreographic model with the aim to convert earthquake sound to a visual dance system, which could return a transmedia representation of the earthquake process. In particular, we focus on a possible method to translate and transfer the metric language of seismic sound and animations into body language. The objective is to involve the audience into a multisensory exploration of the earthquake phenomenon, through the stimulation of the hearing, eyesight and perception of the movements (neuromotor system). In essence, the main goal of this work is to develop a method for a simultaneous visual and auditory representation of a seismic event by means of a structured choreographic model. This artistic representation could provide an original entryway into the physics of earthquakes.

  11. PAGER--Rapid assessment of an earthquake?s impact

    Science.gov (United States)

    Wald, D.J.; Jaiswal, K.; Marano, K.D.; Bausch, D.; Hearne, M.

    2010-01-01

    PAGER (Prompt Assessment of Global Earthquakes for Response) is an automated system that produces content concerning the impact of significant earthquakes around the world, informing emergency responders, government and aid agencies, and the media of the scope of the potential disaster. PAGER rapidly assesses earthquake impacts by comparing the population exposed to each level of shaking intensity with models of economic and fatality losses based on past earthquakes in each country or region of the world. Earthquake alerts--which were formerly sent based only on event magnitude and location, or population exposure to shaking--now will also be generated based on the estimated range of fatalities and economic losses.

  12. Earthquake history of Virginia

    Science.gov (United States)

    von Hake, C. A.

    1977-01-01

    Virginia is a State of considerable seismic activity, although the earthquakes are rarely strong. Thirty-five shocks, intensity MM V or greater (Modified Mercalli Scale), are listed with epicenters within its borders. The locations of several of the older events are not precise; thus, the above count i subject to alteration. A detailed study of Virginia earthquakes by G. A. Bollinger and M. G. Hopper of the Virginia Polytechnic Institute and State University listed 137 shocks (71 from 1774 to 1899, 66 from 1900 to 1970). Many of these were felt with intensities below MM V. 

  13. Improving high-altitude emp modeling capabilities by using a non-equilibrium electron swarm model to monitor conduction electron evolution

    Science.gov (United States)

    Pusateri, Elise Noel

    additional physical parameters such as the O2 electron attachment rate, recombination rate, and mutual neutralization rate. This necessitates tracking the positive and negative ion densities in the swarm model. Adding these parameters, especially electron attachment, is important at lower EMP altitudes where atmospheric density is high. We compare swarm model equilibrium temperatures and times using the HLO and BOLSIG+ coefficients for a uniform electric field of 1 StatV/cm for a range of atmospheric heights. This is done in order to test sensitivity to the swarm parameters used in the swarm model. It is shown that the equilibrium temperature and time are sensitive to the modifications in the collision frequency and ionization rate based on the updated electron interaction cross sections. We validate the swarm model by comparing ionization coefficients and equilibrium drift velocities to experimental results over a wide range of reduced electric field values. The final part of the PhD thesis work includes integrating the swarm model into CHAP-LA. We discuss the physics included in the CHAP-LA EMP model and demonstrate EMP damping behavior caused by the ohmic model at high altitudes. We report on numerical techniques for incorporation of the swarm model into CHAP-LA's Maxwell solver. This includes a discussion of integration techniques for Maxwell's equations in CHAP-LA using the swarm model calculated conduction current. We show improvements on EMP parameter calculations when modeling a high altitude, upward EMP scenario. This provides a novel computational capability that will have an important impact on the atmospheric and EMP research community.

  14. Swarming populations of Salmonella represent a unique physiological state coupled to multiple mechanisms of antibiotic resistance

    Directory of Open Access Journals (Sweden)

    Kim Wook

    2003-01-01

    Full Text Available Salmonella enterica serovar Typhimurium is capable of swarming over semi-solid surfaces. Although its swarming behavior shares many readily observable similarities with other swarming bacteria, the phenomenon remains somewhat of an enigma in this bacterium since some attributes skew away from the better characterized systems. Swarming is quite distinct from the classic swimming motility, as there is a prerequisite for cells to first undergo a morphological transformation into swarmer cells. In some organisms, swarming is controlled by quorum sensing, and in others, swarming has been shown to be coupled to increased expression of important virulence factors. Swarming in serovar Typhimurium is coupled to elevated resistance to a wide variety of structurally and functionally distinct classes of antimicrobial compounds. As serovar Typhimurium differentiates into swarm cells, the pmrHFIJKLM operon is up-regulated, resulting in a more positively charged LPS core. Furthermore, as swarm cells begin to de-differentiate, the pmr operon expression is down-regulated, rapidly reaching the levels observed in swim cells. This is one potential mechanism which confers swarm cells increased resistance to antibiotics such as the cationic antimicrobial peptides. However, additional mechanisms are likely associated with the cells in the swarm state that confer elevated resistance to such a broad spectrum of antimicrobial agents.

  15. Effects of physical factors on the swarming motility of text itPseudomonas aeruginosa

    Science.gov (United States)

    Si, Tieyan; Ma, Zidong; Tang, Wai Shing; Yang, Alexander; Tang, Jay

    Many species of bacteria can spread over a semi-solid surface via a particular form of collective motion known as surface swarming. Using Pseudomonas aeruginosa as a model organism, we investigate physical factors that either facilitate or restrict the swarming motility. The semi-solid surface is typically formed by 0.5-1% agar containing essential nutrients for the bacterial growth and proliferation. Most bacterial species, including P. aeruginosa, synthesize bio-surfactants to aid in swarming. We found addition of exogenous surfactants such as triton into the agar matrix enhances the swarming. In contrast, increasing agar percentage, infusing osmolites, and adding viscous agents all decrease swarming. We propose that the swarming speed is restricted by the rate of water supply from within the agar gel and by the line tension at the swarm front involving three materials in contact: the air, the bacteria propelled liquid film, and the agar substrate.

  16. Earthquakes and submarine volcanism in the Northeast Pacific: Exploration in the time domain based on 21-years of hydroacoustic monitoring

    Science.gov (United States)

    Hammond, S. R.; Dziak, R. P.; Fox, C. G.

    2012-12-01

    Monitoring of regional seismic activity in the Northeast Pacific has been accomplished for the past 21 years using US Navy's Sound Surveillance System (SOSUS) hydrophone arrays. Seafloor seismic activity in this region occurs along the spreading center and transform boundaries between the Juan de Fuca, Pacific and North American plates. During the time span, from 1991 through 2011, nearly 50,000 earthquakes were detected and located. The majority of these events were associated with these tectonic boundaries but sections of several plate boundaries were largely aseismic during the this time span. While most of the earthquakes were associated with geological structures revealed in bathymetric maps of the region, there were also less easily explained intraplate events including a swarm of events within the interior of the southern portion of the Juan de Fuca plate. The location and sequential timing of events on portions of the plate boundaries also suggests ordered patterns of stress release. Among the most scientifically significant outcomes of acoustic monitoring was the discovery that deep seafloor magmatic activity can be accompanied by intense (> 1000 events/day) earthquake swarms. The first swarm detected by SOSUS, in 1993, was confirmed to have been associated with an extrusive volcanic eruption which occurred along a segment of the Juan de Fuca spreading center. Notably, this was the first deep spreading center eruption detected, located, and studied while it was active. Subsequently, two more swarms were confirmed to have been associated with volcanic eruptions, one on the Gorda spreading center in 1996 and the other at Axial volcano in 1998. One characteristic of these swarm events is migration of their earthquake locations 10s of km along the ridge axis tracking the movement of magma down-rift. The most rapid magma propagation events have been shown to be associated with seafloor eruptions and dramatic, transient changes in hydrothermal circulation as

  17. On the premature convergence of particle swarm optimization

    DEFF Research Database (Denmark)

    Larsen, Rie B.; Jouffroy, Jerome; Lassen, Benny

    2016-01-01

    This paper discusses convergence issues of the basic particle swarm optimization algorithm for different pa- rameters. For the one-dimensional case, it is shown that, for a specific range of parameters, the particles will converge prematurely, i.e. away from the actual minimum of the objective...

  18. Swimming and swarming motility properties of peanut-nodulating rhizobia.

    Science.gov (United States)

    Vicario, Julio C; Dardanelli, Marta S; Giordano, Walter

    2015-01-01

    Motility allows populations of bacteria to rapidly reach and colonize new microniches or microhabitats. The motility of rhizobia (symbiotic nitrogen-fixing bacteria that nodulate legume roots) is an important factor determining their competitive success. We evaluated the effects of temperature, incubation time, and seed exudates on swimming and swarming motility of five strains of Bradyrhizobium sp. (peanut-nodulating rhizobia). Swimming motility was increased by exudate exposure for all strains except native Pc34. In contrast, swarming motility was increased by exudate exposure for native 15A but unchanged for the other four strains. All five strains displayed the ability to differentiate into swarm cells. Morphological examination by scanning electron microscopy showed that the length of the swarm cells was variable, but generally greater than that of vegetative cells. Our findings suggest the importance of differential motility properties of peanut-nodulating rhizobial strains during agricultural inoculation and early steps of symbiotic interaction with the host. © FEMS 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Analysis of lineament swarms in a Precambrian metamorphic rocks ...

    Indian Academy of Sciences (India)

    Addressing the geologic significance of lineaments and their correlation with joints/fractures is still unclear. The present study attempts to analyse the lineament swarms developed in a Precambrian metamorphic terrain in India using both unfiltered and filtered techniques. The unfiltered analysis technique shows that the ...

  20. Handbook of swarm intelligence concepts, principles and applications

    CERN Document Server

    Shi, Yuhui; Panigrahi, Bijaya Ketan

    2011-01-01

    Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational problem-solving techniques. This volume is both an introduction to the topic and a survey of leading-edge research.

  1. Collective behaviour without collective order in wild swarms of midges.

    Directory of Open Access Journals (Sweden)

    Alessandro Attanasi

    2014-07-01

    Full Text Available Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.

  2. Optimal power flow by particle swarm optimization with an aging ...

    African Journals Online (AJOL)

    DR OKE

    All rights reserved. Optimal power flow by particle swarm optimization with an aging leader and challengers. Rudra Pratap Singh. 1. *, V. Mukherjee, S.P. Ghoshal. 1*Department of Electrical Engineering, Asansol Engineering College, INDIA. 2 Department of Electrical Engineering, Indian School of Mines Dhanabd, INDIA.

  3. Camera Network Coverage Improving by Particle Swarm Optimization

    NARCIS (Netherlands)

    Xu, Y.C.; Lei, B.; Hendriks, E.A.

    2011-01-01

    This paper studies how to improve the field of view (FOV) coverage of a camera network. We focus on a special but practical scenario where the cameras are randomly scattered in a wide area and each camera may adjust its orientation but cannot move in any direction. We propose a particle swarm

  4. Particle swarm optimization of a neural network model in a ...

    Indian Academy of Sciences (India)

    This paper presents a particle swarm optimization (PSO) technique to train an artificial neural network (ANN) for prediction of flank wear in drilling, and compares the network performance with that of the back propagation neural network (BPNN). This analysis is carried out following a series of experiments employing high ...

  5. Particle swarm optimization of a neural network model in a ...

    Indian Academy of Sciences (India)

    sets of cutting conditions and noting the root mean square (RMS) value of spindle motor current as well as ... A multi- objective optimization of hard turning using neural network modelling and swarm intelligence ... being used in this study), and these activated values in turn become the starting signals for the next adjacent ...

  6. Quantitative analysis of distributed control paradigms of robot swarms

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2010-01-01

    Given a task of designing controller for mobile robots in swarms, one might wonder which distributed control paradigms should be selected. Until now, paradigms of robot controllers have been within either behaviour based control or neural network based control, which have been recognized as two...

  7. Swarm-based wayfinding support in open and distance learning

    NARCIS (Netherlands)

    Tattersall, Colin; Manderveld, Jocelyn; Van den Berg, Bert; Van Es, René; Janssen, José; Koper, Rob

    2005-01-01

    Please refer to the original source: Tattersall, C. Manderveld, J., Van den Berg, B., Van Es, R., Janssen, J., & Koper, R. (2005). Swarm-based wayfinding support in open and distance learning. In Alkhalifa, E.M. (Ed). Cognitively Informed Systems: Utilizing Practical Approaches to Enrich Information

  8. Particle Swarm Optimization Based of the Maximum Photovoltaic ...

    African Journals Online (AJOL)

    A photovoltaic system including a solar panel and PSO MPP tracker is modelled and simulated, it has been has been carried out which has shown the effectiveness of PSO to draw much energy and fast response against change in working conditions. Keywords: Particle Swarm Optimization (PSO), photovoltaic system, ...

  9. Swarming modulatory effects of some amino acids on Proteus ...

    African Journals Online (AJOL)

    TonukariJ

    (Lopatkin et al., 2001; Pfau and Sacks, 1992). The re- occurrence of these diseases have been attributed to polymicrobial etiology through cultures, which is sometimes undetected (van Asten and Gaastra, 1999). Proteus exhibits swarming motility, a growth behavior that may overwhelm the growth of other pathogens.

  10. An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm.

    Science.gov (United States)

    Zhu, Qingling; Lin, Qiuzhen; Chen, Weineng; Wong, Ka-Chun; Coello Coello, Carlos A; Li, Jianqiang; Chen, Jianyong; Zhang, Jun

    2017-09-01

    The selection of swarm leaders (i.e., the personal best and global best), is important in the design of a multiobjective particle swarm optimization (MOPSO) algorithm. Such leaders are expected to effectively guide the swarm to approach the true Pareto optimal front. In this paper, we present a novel external archive-guided MOPSO algorithm (AgMOPSO), where the leaders for velocity update are all selected from the external archive. In our algorithm, multiobjective optimization problems (MOPs) are transformed into a set of subproblems using a decomposition approach, and then each particle is assigned accordingly to optimize each subproblem. A novel archive-guided velocity update method is designed to guide the swarm for exploration, and the external archive is also evolved using an immune-based evolutionary strategy. These proposed approaches speed up the convergence of AgMOPSO. The experimental results fully demonstrate the superiority of our proposed AgMOPSO in solving most of the test problems adopted, in terms of two commonly used performance measures. Moreover, the effectiveness of our proposed archive-guided velocity update method and immune-based evolutionary strategy is also experimentally validated on more than 30 test MOPs.

  11. Progressive Particle Swarm Optimization Algorithm for Solving Reactive Power Problem

    Directory of Open Access Journals (Sweden)

    Kanagasabai Lenin

    2015-11-01

    Full Text Available In this paper a Progressive particle swarm optimization algorithm (PPS is used to solve optimal reactive power problem. A Particle Swarm Optimization algorithm maintains a swarm of particles, where each particle has position vector and velocity vector which represents the potential solutions of the particles. These vectors are modernized from the information of global best (Gbest and personal best (Pbest of the swarm. All particles move in the search space to obtain optimal solution. In this paper a new concept is introduced of calculating the velocity of the particles with the help of Euclidian Distance conception. This new-fangled perception helps in finding whether the particle is closer to Pbest or Gbest and updates the velocity equation consequently. By this we plan to perk up the performance in terms of the optimal solution within a rational number of generations. The projected PPS has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss with control variables are within the limits.

  12. Auto-Clustering using Particle Swarm Optimization and Bacterial Foraging

    DEFF Research Database (Denmark)

    Rutkowski Olesen, Jakob; Cordero, Jorge; Zeng, Yifeng

    2009-01-01

    This paper presents a hybrid approach for clustering based on particle swarm optimization (PSO) and bacteria foraging algorithms (BFA). The new method AutoCPB (Auto-Clustering based on particle bacterial foraging) makes use of autonomous agents whose primary objective is to cluster chunks of data...

  13. Youth on YouTube as Smart Swarms

    Science.gov (United States)

    Duncum, Paul

    2014-01-01

    Viewing YouTube culture as a creative, collaborative process similar to animal swarms can help art educators understand and embrace youth's digital practices. School-age youth are among the most prolific contributors to YouTube, not just as viewers, but also as producers. Even preschoolers now produce videos (McClure, 2010). So pervasive,…

  14. Particle swarm optimization based optimal bidding strategy in an ...

    African Journals Online (AJOL)

    user

    compared with the Genetic Algorithm (GA) approach. Test results indicate that the proposed algorithm outperforms the Genetic. Algorithm approach with respect to total profit and convergence time. Keywords: Electricity Market, Market Clearing Price (MCP), Optimal bidding strategy, Particle Swarm Optimization (PSO).

  15. Steering Micro-Robotic Swarm by Dynamic Actuating Fields

    NARCIS (Netherlands)

    Chao, Q.; Yu, J; Dai, C.; Xu, T; Zhang, L.; Wang, C.C.; Jin, X.

    2016-01-01

    We present a general solution for steering microrobotic
    swarm by dynamic actuating fields. In our approach, the
    motion of micro-robots is controlled by changing the actuating
    direction of a field applied to them. The time-series sequence
    of actuating field’s directions can be

  16. Optimal power flow by particle swarm optimization with an aging ...

    African Journals Online (AJOL)

    In this paper, a particle swarm optimization (PSO) with an aging leader and challengers (ALC-PSO) is applied for the solution of OPF problem of power system. This study is implemented on modified IEEE 30-bus test power system with different objectives that reflect minimization of either fuel cost or active power loss or sum ...

  17. Analysis of lineament swarms in a Precambrian metamorphic rocks ...

    Indian Academy of Sciences (India)

    Addressing the geologic significance of lineaments and their correlation with joints/fractures is still unclear. The present study attempts to analyse the lineament swarms developed in a Precambrian meta- morphic terrain in India using both unfiltered and filtered techniques. The unfiltered analysis technique shows that the ...

  18. Reversals and collisions optimize protein exchange in bacterial swarms

    Energy Technology Data Exchange (ETDEWEB)

    Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy; Christley, Scott; Shrout, Joshua D.; Aranson, Igor S.; Alber, Mark

    2017-03-01

    Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as amechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthus optimizes the connection rate between cells and maximizes the spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that predesigned motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.

  19. THE OCCURENCE OF A HYBRID SWARM INVOLVING A. CHEV ...

    African Journals Online (AJOL)

    BIG TIMMY

    By the year 2000, the population of had declined and, by the year 2010, the population of had given way to as a result of massive rice farming. The intermediate plant forms that lined the bank of the largest impoundment had also disappeared. RESULTS AND OBSERVATIONS. Bolaji et al.: The Occurence of a Hybrid Swarm.

  20. Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem

    Directory of Open Access Journals (Sweden)

    Ibidun Christiana Obagbuwa

    2016-09-01

    Full Text Available The Cockroach Swarm Optimization (CSO algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully. The original CSO algorithm and its variants operate mainly in continuous search space and cannot solve binary-coded optimization problems directly. Many optimization problems have their decision variables in binary. Binary Cockroach Swarm Optimization (BCSO is proposed in this paper to tackle such problems and was evaluated on the popular Traveling Salesman Problem (TSP, which is considered to be an NP-hard Combinatorial Optimization Problem (COP. A transfer function was employed to map a continuous search space CSO to binary search space. The performance of the proposed algorithm was tested firstly on benchmark functions through simulation studies and compared with the performance of existing binary particle swarm optimization and continuous space versions of CSO. The proposed BCSO was adapted to TSP and applied to a set of benchmark instances of symmetric TSP from the TSP library. The results of the proposed Binary Cockroach Swarm Optimization (BCSO algorithm on TSP were compared to other meta-heuristic algorithms.

  1. Validation of Swarm accelerometer data by modelled nongravitational forces

    Czech Academy of Sciences Publication Activity Database

    Bezděk, Aleš; Sebera, J.; Klokočník, Jaroslav

    2017-01-01

    Roč. 59, č. 10 (2017), s. 2512-2521 ISSN 0273-1177 R&D Projects: GA MŠk(CZ) LG15003 Institutional support: RVO:67985815 Keywords : space-borne accelerometers * nongravitational accelerations * swarm mission Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.401, year: 2016

  2. Earthquake science in resilient societies

    Science.gov (United States)

    Stahl, T.; Clark, M. K.; Zekkos, D.; Athanasopoulos-Zekkos, A.; Willis, M.; Medwedeff, William; Knoper, Logan; Townsend, Kirk; Jin, Jonson

    2017-04-01

    Earthquake science is critical in reducing vulnerability to a broad range of seismic hazards. Evidence-based studies drawing from several branches of the Earth sciences and engineering can effectively mitigate losses experienced in earthquakes. Societies that invest in this research have lower fatality rates in earthquakes and can recover more rapidly. This commentary explores the scientific pathways through which earthquake-resilient societies are developed. We highlight recent case studies of evidence-based decision making and how modern research is improving the way societies respond to earthquakes.

  3. Earthquake forecasting test for Kanto district to reduce vulnerability of urban mega earthquake disasters

    Science.gov (United States)

    Yokoi, S.; Tsuruoka, H.; Nanjo, K.; Hirata, N.

    2012-12-01

    Collaboratory for the Study of Earthquake Predictability (CSEP) is a global project on earthquake predictability research. The final goal of this project is to search for the intrinsic predictability of the earthquake rupture process through forecast testing experiments. The Earthquake Research Institute, the University of Tokyo joined CSEP and started the Japanese testing center called as CSEP-Japan. This testing center provides an open access to researchers contributing earthquake forecast models applied to Japan. Now more than 100 earthquake forecast models were submitted on the prospective experiment. The models are separated into 4 testing classes (1 day, 3 months, 1 year and 3 years) and 3 testing regions covering an area of Japan including sea area, Japanese mainland and Kanto district. We evaluate the performance of the models in the official suite of tests defined by CSEP. The total number of experiments was implemented for approximately 300 rounds. These results provide new knowledge concerning statistical forecasting models. We started a study for constructing a 3-dimensional earthquake forecasting model for Kanto district in Japan based on CSEP experiments under the Special Project for Reducing Vulnerability for Urban Mega Earthquake Disasters. Because seismicity of the area ranges from shallower part to a depth of 80 km due to subducting Philippine Sea plate and Pacific plate, we need to study effect of depth distribution. We will develop models for forecasting based on the results of 2-D modeling. We defined the 3D - forecasting area in the Kanto region with test classes of 1 day, 3 months, 1 year and 3 years, and magnitudes from 4.0 to 9.0 as in CSEP-Japan. In the first step of the study, we will install RI10K model (Nanjo, 2011) and the HISTETAS models (Ogata, 2011) to know if those models have good performance as in the 3 months 2-D CSEP-Japan experiments in the Kanto region before the 2011 Tohoku event (Yokoi et al., in preparation). We use CSEP

  4. Non-stationary ETAS to model earthquake occurrences affected by episodic aseismic transients

    Science.gov (United States)

    Kattamanchi, Sasi; Tiwari, Ram Krishna; Ramesh, Durbha Sai

    2017-11-01

    We present a non-stationary epidemic-type aftershock sequence (ETAS) model in which the usual assumption of stationary background rate is relaxed. Such a model could be used for modeling seismic sequences affected by aseismic transients such as fluid/magma intrusion, slow slip earthquakes (SSEs), etc. The non-stationary background rate is expressed as a linear combination of B-splines, and a method is proposed that allows for simultaneous estimation of background rate as well as other ETAS model parameters. We also present an extension to this non-stationary ETAS model where an adaptive roughness penalty function is used and consequently provides better estimates of rapidly varying background rate functions. The performance of the proposed methods is demonstrated on synthetic catalogs and an application to detect earthquake swarms (possibly associated with SSEs) in Hikurangi margin (North Island, New Zealand) is presented.[Figure not available: see fulltext.

  5. A dasymetric data supported earthquake disaster loss quick assessment method for emergency response in China

    Science.gov (United States)

    Xu, J.; An, J.; Nie, G.

    2015-02-01

    Improving earthquake disaster loss estimation speed and accuracy is one of key factors in effective earthquake response and rescue. The presentation of exposure data by applying a dasymetric map approach has good potential for addressing this issue. With the support of 30'' × 30'' areal exposure data (population and building data in China), this paper presents a new two-phase earthquake disaster loss estimation method for emergency response situations. This method has two phases: a pre-earthquake phase and a co-earthquake phase. In the pre-earthquake phase, we pre-calculate the earthquake loss related to different seismic intensities and store them in a 30'' × 30'' grid format, which has four stages: determining the earthquake loss calculation factor, gridding possible damage matrixes, the building damage calculation and the people loss calculation. The dasymetric map approach makes this possible. Then, in the co-earthquake phase, there are two stages of estimating loss: generating a theoretical isoseismal map to depict the spatial distribution of the seismic intensity field; then, using the seismic intensity field to extract statistics of disaster loss from pre-calculated loss estimation data to obtain the final estimation results. The method is validated by four actual earthquakes that occurred in China. The method not only significant improves the speed and accuracy of loss estimation, but gives spatial distribution for the loss, which will be effective in aiding earthquake emergency response and rescue. Additionally, related pre-calculated earthquake loss estimation data in China could serve to provide disaster risk analysis before earthquakes happen. Currently, the pre-calculated loss estimation data and the two-phase estimation method are used by the China Earthquake Administration.

  6. A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

    Science.gov (United States)

    Xu, Jinghai; An, Jiwen; Nie, Gaozong

    2016-04-01

    Improving earthquake disaster loss estimation speed and accuracy is one of the key factors in effective earthquake response and rescue. The presentation of exposure data by applying a dasymetric map approach has good potential for addressing this issue. With the support of 30'' × 30'' areal exposure data (population and building data in China), this paper presents a new earthquake disaster loss estimation method for emergency response situations. This method has two phases: a pre-earthquake phase and a co-earthquake phase. In the pre-earthquake phase, we pre-calculate the earthquake loss related to different seismic intensities and store them in a 30'' × 30'' grid format, which has several stages: determining the earthquake loss calculation factor, gridding damage probability matrices, calculating building damage and calculating human losses. Then, in the co-earthquake phase, there are two stages of estimating loss: generating a theoretical isoseismal map to depict the spatial distribution of the seismic intensity field; then, using the seismic intensity field to extract statistics of losses from the pre-calculated estimation data. Thus, the final loss estimation results are obtained. The method is validated by four actual earthquakes that occurred in China. The method not only significantly improves the speed and accuracy of loss estimation but also provides the spatial distribution of the losses, which will be effective in aiding earthquake emergency response and rescue. Additionally, related pre-calculated earthquake loss estimation data in China could serve to provide disaster risk analysis before earthquakes occur. Currently, the pre-calculated loss estimation data and the two-phase estimation method are used by the China Earthquake Administration.

  7. Generic, scalable and decentralized fault detection for robot swarms

    Science.gov (United States)

    Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. PMID:28806756

  8. Generic, scalable and decentralized fault detection for robot swarms.

    Science.gov (United States)

    Tarapore, Danesh; Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.

  9. Dynamic strains for earthquake source characterization

    Science.gov (United States)

    Barbour, Andrew J.; Crowell, Brendan W

    2017-01-01

    Strainmeters measure elastodynamic deformation associated with earthquakes over a broad frequency band, with detection characteristics that complement traditional instrumentation, but they are commonly used to study slow transient deformation along active faults and at subduction zones, for example. Here, we analyze dynamic strains at Plate Boundary Observatory (PBO) borehole strainmeters (BSM) associated with 146 local and regional earthquakes from 2004–2014, with magnitudes from M 4.5 to 7.2. We find that peak values in seismic strain can be predicted from a general regression against distance and magnitude, with improvements in accuracy gained by accounting for biases associated with site–station effects and source–path effects, the latter exhibiting the strongest influence on the regression coefficients. To account for the influence of these biases in a general way, we include crustal‐type classifications from the CRUST1.0 global velocity model, which demonstrates that high‐frequency strain data from the PBO BSM network carry information on crustal structure and fault mechanics: earthquakes nucleating offshore on the Blanco fracture zone, for example, generate consistently lower dynamic strains than earthquakes around the Sierra Nevada microplate and in the Salton trough. Finally, we test our dynamic strain prediction equations on the 2011 M 9 Tohoku‐Oki earthquake, specifically continuous strain records derived from triangulation of 137 high‐rate Global Navigation Satellite System Earth Observation Network stations in Japan. Moment magnitudes inferred from these data and the strain model are in agreement when Global Positioning System subnetworks are unaffected by spatial aliasing.

  10. Probabilistic approach to earthquake prediction.

    Directory of Open Access Journals (Sweden)

    G. D'Addezio

    2002-06-01

    Full Text Available The evaluation of any earthquake forecast hypothesis requires the application of rigorous statistical methods. It implies a univocal definition of the model characterising the concerned anomaly or precursor, so as it can be objectively recognised in any circumstance and by any observer.A valid forecast hypothesis is expected to maximise successes and minimise false alarms. The probability gain associated to a precursor is also a popular way to estimate the quality of the predictions based on such precursor. Some scientists make use of a statistical approach based on the computation of the likelihood of an observed realisation of seismic events, and on the comparison of the likelihood obtained under different hypotheses. This method can be extended to algorithms that allow the computation of the density distribution of the conditional probability of earthquake occurrence in space, time and magnitude. Whatever method is chosen for building up a new hypothesis, the final assessment of its validity should be carried out by a test on a new and independent set of observations. The implementation of this test could, however, be problematic for seismicity characterised by long-term recurrence intervals. Even using the historical record, that may span time windows extremely variable between a few centuries to a few millennia, we have a low probability to catch more than one or two events on the same fault. Extending the record of earthquakes of the past back in time up to several millennia, paleoseismology represents a great opportunity to study how earthquakes recur through time and thus provide innovative contributions to time-dependent seismic hazard assessment. Sets of paleoseimologically dated earthquakes have been established for some faults in the Mediterranean area: the Irpinia fault in Southern Italy, the Fucino fault in Central Italy, the El Asnam fault in Algeria and the Skinos fault in Central Greece. By using the age of the

  11. The HayWired earthquake scenario—Earthquake hazards

    Science.gov (United States)

    Detweiler, Shane T.; Wein, Anne M.

    2017-01-01

    The HayWired scenario is a hypothetical earthquake sequence that is being used to better understand hazards for the San Francisco Bay region during and after an earthquake of magnitude 7 on the Hayward Fault. The 2014 Working Group on California Earthquake Probabilities calculated that there is a 33-percent likelihood of a large (magnitude 6.7 or greater) earthquake occurring on the Hayward Fault within three decades. A large Hayward Fault earthquake will produce strong ground shaking, permanent displacement of the Earth’s surface, landslides, liquefaction (soils becoming liquid-like during shaking), and subsequent fault slip, known as afterslip, and earthquakes, known as aftershocks. The most recent large earthquake on the Hayward Fault occurred on October 21, 1868, and it ruptured the southern part of the fault. The 1868 magnitude-6.8 earthquake occurred when the San Francisco Bay region had far fewer people, buildings, and infrastructure (roads, communication lines, and utilities) than it does today, yet the strong ground shaking from the earthquake still caused significant building damage and loss of life. The next large Hayward Fault earthquake is anticipated to affect thousands of structures and disrupt the lives of millions of people. Earthquake risk in the San Francisco Bay region has been greatly reduced as a result of previous concerted efforts; for example, tens of billions of dollars of investment in strengthening infrastructure was motivated in large part by the 1989 magnitude 6.9 Loma Prieta earthquake. To build on efforts to reduce earthquake risk in the San Francisco Bay region, the HayWired earthquake scenario comprehensively examines the earthquake hazards to help provide the crucial scientific information that the San Francisco Bay region can use to prepare for the next large earthquake, The HayWired Earthquake Scenario—Earthquake Hazards volume describes the strong ground shaking modeled in the scenario and the hazardous movements of

  12. Slip pulse and resonance of the Kathmandu basin during the 2015 Gorkha earthquake, Nepal

    OpenAIRE

    Galetzka, John; Melgar, Diego; Genrich, Joachim F.; Geng, Jianghui; Owen, Susan; Lindsey, Eric O.; Xu, Xiaohua; Bock, Yehuda; Avouac, Jean-Philippe; Adhikari, Lok Bijaya; Upreti, Bishal Nath; Pratt-Sitaula, Beth; Bhattarai, Tara Nidhi; Sitaula, Bhairab P.; Moore, Angelyn

    2015-01-01

    This is the author accepted manuscript. The final version is available from AAAS via http://dx.doi.org/10.1126/science.aac6383 Detailed geodetic imaging of earthquake rupture enhances our understanding of earthquake physics and induced ground shaking. The April 25, 2015 Mw 7.8 Gorkha, Nepal earthquake is the first example of a large continental megathrust rupture beneath a high-rate (5 Hz) GPS network. We use GPS and InSAR data to model the earthquake rupture as a slip pulse of ~20 km widt...

  13. Surface hardness impairment of quorum sensing and swarming for Pseudomonas aeruginosa.

    Directory of Open Access Journals (Sweden)

    Nachiket G Kamatkar

    Full Text Available The importance of rhamnolipid to swarming of the bacterium Pseudomonas aeruginosa is well established. It is frequently, but not exclusively, observed that P. aeruginosa swarms in tendril patterns--formation of these tendrils requires rhamnolipid. We were interested to explain the impact of surface changes on P. aeruginosa swarm tendril development. Here we report that P. aeruginosa quorum sensing and rhamnolipid production is impaired when growing on harder semi-solid surfaces. P. aeruginosa wild-type swarms showed huge variation in tendril formation with small deviations to the "standard" swarm agar concentration of 0.5%. These macroscopic differences correlated with microscopic investigation of cells close to the advancing swarm edge using fluorescent gene reporters. Tendril swarms showed significant rhlA-gfp reporter expression right up to the advancing edge of swarming cells while swarms without tendrils (grown on harder agar showed no rhlA-gfp reporter expression near the advancing edge. This difference in rhamnolipid gene expression can be explained by the necessity of quorum sensing for rhamnolipid production. We provide evidence that harder surfaces seem to limit induction of quorum sensing genes near the advancing swarm edge and these localized effects were sufficient to explain the lack of tendril formation on hard agar. We were unable to artificially stimulate rhamnolipid tendril formation with added acyl-homoserine lactone signals or increasing the carbon nutrients. This suggests that quorum sensing on surfaces is controlled in a manner that is not solely population dependent.

  14. Exopolysaccharides play a role in the swarming of the benthic bacterium Pseudoalteromonas sp. SM9913

    Directory of Open Access Journals (Sweden)

    Ang eLiu

    2016-04-01

    Full Text Available Most marine bacteria secrete exopolysaccharide (EPS, which is important for bacterial survival in the marine environment. However, it is still unclear whether the self-secreted EPS is involved in marine bacterial motility. Here we studied the role of EPS in the lateral flagella-driven swarming motility of benthic bacterium Pseudoalteromonas sp. SM9913 (SM9913 by a comparison of wild SM9913 and ΔepsT, an EPS synthesis defective mutant. Reduction of EPS production in ΔepsT did not affect the growth rate or the swimming motility, but significantly decreased the swarming motility on a swarming plate, suggesting that the EPS may play a role in SM9913 swarming. However, the expression and assembly of lateral flagella in ΔepsT were not affected. Instead, ΔepsT had a different swarming behavior from wild SM9913. The swarming of ΔepsT did not have an obvious rapid swarming period, and its rate became much lower than that of wild SM9913 after 35 h incubation. An addition of surfactin or SM9913 EPS on the surface of the swarming plate could rescue the swarming level. These results indicate that the self-secreted EPS is required for the swarming of SM9913. This study widens our understanding of the function of the EPS of benthic bacteria.

  15. Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization

    Science.gov (United States)

    Zhidi, Jiang; Zhenhai, Wang; Pengjun, Wang

    2013-06-01

    Polarity optimization for mixed polarity Reed—Muller (MPRM) circuits is a combinatorial issue. Based on the study on discrete particle swarm optimization (DPSO) and mixed polarity, the corresponding relation between particle and mixed polarity is established, and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly, mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO (HDPSO). Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model. Finally, the proposed algorithm is testified by MCNC Benchmarks. Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits.

  16. Application of Swarm Intelligence Based Routingprotocols for Wireless Adhoc Sensor Network

    Directory of Open Access Journals (Sweden)

    Mrutyunjaya PANDA

    2011-07-01

    Full Text Available The enormous growth of wireless sensor network (WSN research has opined challenges about their ease in implementation and performance evaluation. Efficient swarm intelligence based routing protocols that can be used to obtain the application specific service guarantee are the key design issues in designing a WSN model. In this paper, an experimental testbed is designed with 100 sensor nodes deployed in a dense environment to address the scalability and performance issues of WSN. In this paper, we use Flooded Piggyback (FP and SC-MCBR ant colony based routing along with AODV and MCBR Tree in order to design an efficient WSN model. Finally, simulation results are presented with various performance measures to understand the efficacy of the proposed WSN design.

  17. A combination of genetic algorithm and particle swarm optimization method for solving traveling salesman problem

    Directory of Open Access Journals (Sweden)

    Keivan Borna

    2015-12-01

    Full Text Available Traveling salesman problem (TSP is a well-established NP-complete problem and many evolutionary techniques like particle swarm optimization (PSO are used to optimize existing solutions for that. PSO is a method inspired by the social behavior of birds. In PSO, each member will change its position in the search space, according to personal or social experience of the whole society. In this paper, we combine the principles of PSO and crossover operator of genetic algorithm to propose a heuristic algorithm for solving the TSP more efficiently. Finally, some experimental results on our algorithm are applied in some instances in TSPLIB to demonstrate the effectiveness of our methods which also show that our algorithm can achieve better results than other approaches.

  18. A New Logistic Dynamic Particle Swarm Optimization Algorithm Based on Random Topology

    Directory of Open Access Journals (Sweden)

    Qingjian Ni

    2013-01-01

    Full Text Available Population topology of particle swarm optimization (PSO will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

  19. Multi-objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm

    Science.gov (United States)

    Cui, Xue; Gao, Jian; Feng, Yunbin; Zou, Chenlu; Liu, Huanlei

    2018-01-01

    In this paper, an optimization model with the minimum active power loss and minimum voltage deviation of node and maximum static voltage stability margin as the optimization objective is proposed for the reactive power optimization problems. By defining the index value of reactive power compensation, the optimal reactive power compensation node was selected. The particle swarm optimization algorithm was improved, and the selection pool of global optimal and the global optimal of probability (p-gbest) were introduced. A set of Pareto optimal solution sets is obtained by this algorithm. And by calculating the fuzzy membership value of the pareto optimal solution sets, individuals with the smallest fuzzy membership value were selected as the final optimization results. The above improved algorithm is used to optimize the reactive power of IEEE14 standard node system. Through the comparison and analysis of the results, it has been proven that the optimization effect of this algorithm was very good.

  20. Simulation on Vessel Intelligent Collision Avoidance Based on Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Li Weifeng

    2016-10-01

    Full Text Available TAs the rapid development of the ship equipments and navigation technology, vessel intelligent collision avoidance theory was researched world widely. Meantime, more and more ship intelligent collision avoidance products are put into use. It not only makes the ship much safer, but also lighten the officers work intensity and improve the ship’s economy. The paper based on the International Regulation for Preventing Collision at sea and ship domain theories, with the ship proceeding distance when collision avoidance as the objective function, through the artificial fish swarm algorithm to optimize the collision avoidance path, and finally simulates overtaking situation, crossing situation and head-on situation three classic meeting situation of ships on the sea by VC++ computer language. Calculation and simulation results are basically consistent with the actual situation which certifies that its validity.

  1. Dynamic path planning for mobile robot based on particle swarm optimization

    Science.gov (United States)

    Wang, Yong; Cai, Feng; Wang, Ying

    2017-08-01

    In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

  2. DOA estimation for local scattered CDMA signals by particle swarm optimization.

    Science.gov (United States)

    Chang, Jhih-Chung

    2012-01-01

    This paper deals with the direction-of-arrival (DOA) estimation of local scattered code-division multiple access (CDMA) signals based on a particle swarm optimization (PSO) search. For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search. In order to obtain high-resolution and accurate DOA estimation, a smaller grid size is needed. This is time consuming and it is unclear how to determine the required number of search grids. In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering. Finally, several computer simulations are provided for illustration and comparison.

  3. A new logistic dynamic particle swarm optimization algorithm based on random topology.

    Science.gov (United States)

    Ni, Qingjian; Deng, Jianming

    2013-01-01

    Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

  4. Optimal Sensor Placement for Latticed Shell Structure Based on an Improved Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Xun Zhang

    2014-01-01

    Full Text Available Optimal sensor placement is a key issue in the structural health monitoring of large-scale structures. However, some aspects in existing approaches require improvement, such as the empirical and unreliable selection of mode and sensor numbers and time-consuming computation. A novel improved particle swarm optimization (IPSO algorithm is proposed to address these problems. The approach firstly employs the cumulative effective modal mass participation ratio to select mode number. Three strategies are then adopted to improve the PSO algorithm. Finally, the IPSO algorithm is utilized to determine the optimal sensors number and configurations. A case study of a latticed shell model is implemented to verify the feasibility of the proposed algorithm and four different PSO algorithms. The effective independence method is also taken as a contrast experiment. The comparison results show that the optimal placement schemes obtained by the PSO algorithms are valid, and the proposed IPSO algorithm has better enhancement in convergence speed and precision.

  5. Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

    Science.gov (United States)

    Jin, Junchen

    2016-01-01

    The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

  6. Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jiaxi Wang

    2016-01-01

    Full Text Available The shunting schedule of electric multiple units depot (SSED is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality.

  7. Collective Information Processing and Pattern Formation in swarms, flocks and crowds

    CERN Document Server

    Moussaid, Mehdi; Theraulaz, Guy; Helbing, Dirk

    2010-01-01

    The spontaneous organization of collective activities in animal groups and societies has attracted a considerable amount of attention over the last decade. This kind of coordination often permits group-living species to achieve collective tasks that are far beyond single individuals capabilities. In particular, a key benefit lies in the integration of partial knowledge of the environment at the collective level. In this contribution we discuss various self-organization phenomena in animal swarms and human crowds from the point of view of information exchange among individuals. In particular, we provide a general description of collective dynamics across species and introduce a classification of these dynamics not only with respect to the way information is transferred among individuals, but also with regard to the knowledge processing at the collective level. Finally, we highlight the fact that the individuals' ability to learn from past experiences can have a feedback effect on the collective dynamics, as ex...

  8. Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Saraiva J. T.

    2012-10-01

    Full Text Available The basic objective of Transmission Expansion Planning (TEP is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.

  9. Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

    Science.gov (United States)

    Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

    2017-02-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

  10. Historical earthquake research in Austria

    Science.gov (United States)

    Hammerl, Christa

    2017-12-01

    Austria has a moderate seismicity, and on average the population feels 40 earthquakes per year or approximately three earthquakes per month. A severe earthquake with light building damage is expected roughly every 2 to 3 years in Austria. Severe damage to buildings ( I 0 > 8° EMS) occurs significantly less frequently, the average period of recurrence is about 75 years. For this reason the historical earthquake research has been of special importance in Austria. The interest in historical earthquakes in the past in the Austro-Hungarian Empire is outlined, beginning with an initiative of the Austrian Academy of Sciences and the development of historical earthquake research as an independent research field after the 1978 "Zwentendorf plebiscite" on whether the nuclear power plant will start up. The applied methods are introduced briefly along with the most important studies and last but not least as an example of a recently carried out case study, one of the strongest past earthquakes in Austria, the earthquake of 17 July 1670, is presented. The research into historical earthquakes in Austria concentrates on seismic events of the pre-instrumental period. The investigations are not only of historical interest, but also contribute to the completeness and correctness of the Austrian earthquake catalogue, which is the basis for seismic hazard analysis and as such benefits the public, communities, civil engineers, architects, civil protection, and many others.

  11. Defect Detection of Adhesive Layer of Thermal Insulation Materials Based on Improved Particle Swarm Optimization of ECT

    Directory of Open Access Journals (Sweden)

    Yintang Wen

    2017-10-01

    Full Text Available This paper studies the defect detection problem of adhesive layer of thermal insulation materials. A novel detection method based on an improved particle swarm optimization (PSO algorithm of Electrical Capacitance Tomography (ECT is presented. Firstly, a least squares support vector machine is applied for data processing of measured capacitance values. Then, the improved PSO algorithm is proposed and applied for image reconstruction. Finally, some experiments are provided to verify the effectiveness of the proposed method in defect detection for adhesive layer of thermal insulation materials. The performance comparisons demonstrate that the proposed method has higher precision by comparing with traditional ECT algorithms.

  12. Defect Detection of Adhesive Layer of Thermal Insulation Materials Based on Improved Particle Swarm Optimization of ECT.

    Science.gov (United States)

    Wen, Yintang; Jia, Yao; Zhang, Yuyan; Luo, Xiaoyuan; Wang, Hongrui

    2017-10-25

    This paper studies the defect detection problem of adhesive layer of thermal insulation materials. A novel detection method based on an improved particle swarm optimization (PSO) algorithm of Electrical Capacitance Tomography (ECT) is presented. Firstly, a least squares support vector machine is applied for data processing of measured capacitance values. Then, the improved PSO algorithm is proposed and applied for image reconstruction. Finally, some experiments are provided to verify the effectiveness of the proposed method in defect detection for adhesive layer of thermal insulation materials. The performance comparisons demonstrate that the proposed method has higher precision by comparing with traditional ECT algorithms.

  13. Swarm Deployable Boom Assembly (DBA) Development of a Deployable Magnetometer Boom for the Swarm Spacecraft

    Science.gov (United States)

    McMahon, Paul; Jung, Hans-Juergen; Edwards, Jeff

    2013-09-01

    The Swarm programme consists of 3 magnetically clean satellites flying in close formation designed to measure the Earth's magnetic field using 2 Magnetometers mounted on a 4.3m long deployable boom.Deployment is initiated by releasing 3 HDRMs, once released the boom oscillates back and forth on a pair of pivots, similar to a restaurant kitchen door hinge, for around 120 seconds before coming to rest on 3 kinematic mounts which are used to provide an accurate reference location in the deployed position. Motion of the boom is damped through a combination of friction, spring hysteresis and flexing of the 120+ cables crossing the hinge. Considerable development work and accurate numerical modelling of the hinge motion was required to predict performance across a wide temperature range and ensure that during the 1st overshoot the boom did not damage itself, the harness or the spacecraft.Due to the magnetic cleanliness requirements of the spacecraft no magnetic materials could be used in the design of the hardware.

  14. Earthquake engineering for nuclear facilities

    CERN Document Server

    Kuno, Michiya

    2017-01-01

    This book is a comprehensive compilation of earthquake- and tsunami-related technologies and knowledge for the design and construction of nuclear facilities. As such, it covers a wide range of fields including civil engineering, architecture, geotechnical engineering, mechanical engineering, and nuclear engineering, for the development of new technologies providing greater resistance against earthquakes and tsunamis. It is crucial both for students of nuclear energy courses and for young engineers in nuclear power generation industries to understand the basics and principles of earthquake- and tsunami-resistant design of nuclear facilities. In Part I, "Seismic Design of Nuclear Power Plants", the design of nuclear power plants to withstand earthquakes and tsunamis is explained, focusing on buildings, equipment's, and civil engineering structures. In Part II, "Basics of Earthquake Engineering", fundamental knowledge of earthquakes and tsunamis as well as the dynamic response of structures and foundation ground...

  15. Do Earthquakes Shake Stock Markets?

    Science.gov (United States)

    Ferreira, Susana; Karali, Berna

    2015-01-01

    This paper examines how major earthquakes affected the returns and volatility of aggregate stock market indices in thirty-five financial markets over the last twenty years. Results show that global financial markets are resilient to shocks caused by earthquakes even if these are domestic. Our analysis reveals that, in a few instances, some macroeconomic variables and earthquake characteristics (gross domestic product per capita, trade openness, bilateral trade flows, earthquake magnitude, a tsunami indicator, distance to the epicenter, and number of fatalities) mediate the impact of earthquakes on stock market returns, resulting in a zero net effect. However, the influence of these variables is market-specific, indicating no systematic pattern across global capital markets. Results also demonstrate that stock market volatility is unaffected by earthquakes, except for Japan.

  16. Earthquake forecast models for Italy based on the RI algorithm

    Directory of Open Access Journals (Sweden)

    Kazuyoshi Z. Nanjo

    2010-11-01

    Full Text Available This study provides an overview of relative-intensity (RI-based earthquake forecast models that have been submitted for the 5-year and 10-year testing classes and the 3-month class of the Italian experiment within the Collaboratory for the Study of Earthquake Predictability (CSEP. The RI algorithm starts as a binary forecast system based on the working assumption that future large earthquakes are considered likely to occur at sites of higher seismic activity in the past. The measure of RI is the simply counting of the number of past earthquakes, which is known as the RI of seismicity. To improve the RI forecast performance, we first expand the RI algorithm to become part of a general class of smoothed seismicity models. We then convert the RI representation from a binary system into a testable CSEP model that forecasts the numbers of earthquakes for the predefined magnitudes. Our parameter tuning for the CSEP models is based on the past seismicity. The final submission is a set of two numerical data files that were created by tuned 5-year and 10-year models and an executable computer code of a tuned 3-month model, to examine which testing class is more meaningful in terms of the RI hypothesis. The main purpose of our participation is to better understand the importance (or lack of importance of RI of seismicity for earthquake forecastability.

  17. Earthquake technology fights crime

    Science.gov (United States)

    Lahr, John C.; Ward, Peter L.; Stauffer, Peter H.; Hendley, James W.

    1996-01-01

    Scientists with the U.S. Geological Survey have adapted their methods for quickly finding the exact source of an earthquake to the problem of locating gunshots. On the basis of this work, a private company is now testing an automated gunshot-locating system in a San Francisco Bay area community. This system allows police to rapidly pinpoint and respond to illegal gunfire, helping to reduce crime in our neighborhoods.

  18. Earthquake Source Mechanics

    Science.gov (United States)

    The past 2 decades have seen substantial progress in our understanding of the nature of the earthquake faulting process, but increasingly, the subject has become an interdisciplinary one. Thus, although the observation of radiated seismic waves remains the primary tool for studying earthquakes (and has been increasingly focused on extracting the physical processes occurring in the “source”), geological studies have also begun to play a more important role in understanding the faulting process. Additionally, defining the physical underpinning for these phenomena has come to be an important subject in experimental and theoretical rock mechanics.In recognition of this, a Maurice Ewing Symposium was held at Arden House, Harriman, N.Y. (the former home of the great American statesman Averill Harriman), May 20-23, 1985. The purpose of the meeting was to bring together the international community of experimentalists, theoreticians, and observationalists who are engaged in the study of various aspects of earthquake source mechanics. The conference was attended by more than 60 scientists from nine countries (France, Italy, Japan, Poland, China, the United Kingdom, United States, Soviet Union, and the Federal Republic of Germany).

  19. Fault lubrication during earthquakes.

    Science.gov (United States)

    Di Toro, G; Han, R; Hirose, T; De Paola, N; Nielsen, S; Mizoguchi, K; Ferri, F; Cocco, M; Shimamoto, T

    2011-03-24

    The determination of rock friction at seismic slip rates (about 1 m s(-1)) is of paramount importance in earthquake mechanics, as fault friction controls the stress drop, the mechanical work and the frictional heat generated during slip. Given the difficulty in determining friction by seismological methods, elucidating constraints are derived from experimental studies. Here we review a large set of published and unpublished experiments (∼300) performed in rotary shear apparatus at slip rates of 0.1-2.6 m s(-1). The experiments indicate a significant decrease in friction (of up to one order of magnitude), which we term fault lubrication, both for cohesive (silicate-built, quartz-built and carbonate-built) rocks and non-cohesive rocks (clay-rich, anhydrite, gypsum and dolomite gouges) typical of crustal seismogenic sources. The available mechanical work and the associated temperature rise in the slipping zone trigger a number of physicochemical processes (gelification, decarbonation and dehydration reactions, melting and so on) whose products are responsible for fault lubrication. The similarity between (1) experimental and natural fault products and (2) mechanical work measures resulting from these laboratory experiments and seismological estimates suggests that it is reasonable to extrapolate experimental data to conditions typical of earthquake nucleation depths (7-15 km). It seems that faults are lubricated during earthquakes, irrespective of the fault rock composition and of the specific weakening mechanism involved.

  20. The Effect of Monoterpenes on Swarming Differentiation and Haemolysin Activity in Proteus mirabilis

    Directory of Open Access Journals (Sweden)

    Sergio Echeverrigaray

    2008-12-01

    Full Text Available Urinary tract infection by Proteus mirabilis depends on several virulence properties that are coordinately regulated with swarming differentiation. Here we report the antibacterial and anti-swarming effect of seventeen terpenoids, and the effect of subinhibitory concentrations of five selected terpenoids on swarming, biofilm formation and haemolysin activity. The results showed that all the terpenes evaluated, particularly oxygenated terpenoids, inhibited P. mirabilis with MIC values ranging between 3 and 10 mg/L. Moreover, citral, citronellol and geraniol effectively inhibit P. mirabilis swarming in a dose dependent manner, reducing swimming/swarming cell differentiation and haemolysin activity at 1/10 MIC concentration. The inhibition of P. mirabilis swarming and virulence factor expression by selected oxygenated terpenoids suggest that essential oils with high concentration of these compounds have the potential to be developed as products for preventing P. mirabilis infections.

  1. Analysis of the Emergence in Swarm Model Based on Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yu Wu

    2011-01-01

    Full Text Available Emergent behaviors of collective intelligence systems, exemplified by swarm model, have attracted broad interests in recent years. However, current research mostly stops at observational interpretations and qualitative descriptions of emergent phenomena and is essentially short of quantitative analysis and evaluation. In this paper, we conduct a quantitative study on the emergence of swarm model by using chaos analysis of complex dynamic systems. This helps to achieve a more exact understanding of emergent phenomena. In particular, we evaluate the emergent behaviors of swarm model quantitatively by using the chaos and stability analysis of swarm model based on largest Lyapunov exponent. It is concluded that swarm model is at the edge of chaos when emergence occurs, and whether chaotic or stable at the beginning, swarm model will converge to stability with the elapse of time along with interactions among agents.

  2. Creating Virtual Communities by Means of Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Lucian Hancu

    2011-01-01

    Full Text Available

    During centuries, observing the behavior of wild species has always been fascinating and full of mysteries. Modeling human interactions based on those revealed on the wilderness conducts to innovative solutions, but also poses unexpected issues. In this article, we describe our approach of creating communities of virtual entities by means of swarm intelligence. We discuss the algorithm of creating the virtual communities along with the issues that arise when modeling business entities as individuals of the swarm.

  3. Glowworm Swarm Optimization and Its Application to Blind Signal Separation

    Directory of Open Access Journals (Sweden)

    Zhucheng Li

    2016-01-01

    Full Text Available Traditional optimization algorithms for blind signal separation (BSS are mainly based on the gradient, which requires the objective function to be continuous and differentiable, so the applications of these algorithms are very limited. Moreover, these algorithms have problems with the convergence speed and accuracy. To overcome these drawbacks, this paper presents a modified glowworm swarm optimization (MGSO algorithm based on a novel step adjustment rule and then applies MGSO to BSS. Taking kurtosis of the mixed signals as the objective function of BSS, MGSO-BSS succeeds in separating the mixed signals in Matlab environment. The simulation results prove that MGSO is more effective in capturing the global optimum of the objective function of the BSS algorithm and has faster convergence speed and higher accuracy, compared with particle swarm optimization (PSO and GSO.

  4. Celestial Navigation Fix Based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Tsou Ming-Cheng

    2015-09-01

    Full Text Available A technique for solving celestial fix problems is proposed in this study. This method is based on Particle Swarm Optimization from the field of swarm intelligence, utilizing its superior optimization and searching abilities to obtain the most probable astronomical vessel position. In addition to being applicable to two-body fix, multi-body fix, and high-altitude observation problems, it is also less reliant on the initial dead reckoning position. Moreover, by introducing spatial data processing and display functions in a Geographical Information System, calculation results and chart work used in Circle of Position graphical positioning can both be integrated. As a result, in addition to avoiding tedious and complicated computational and graphical procedures, this work has more flexibility and is more robust when compared to other analytical approaches.

  5. A hierarchical particle swarm optimizer and its adaptive variant.

    Science.gov (United States)

    Janson, Stefan; Middendorf, Martin

    2005-12-01

    A hierarchical version of the particle swarm optimization (PSO) metaheuristic is introduced in this paper. In the new method called H-PSO, the particles are arranged in a dynamic hierarchy that is used to define a neighborhood structure. Depending on the quality of their so-far best-found solution, the particles move up or down the hierarchy. This gives good particles that move up in the hierarchy a larger influence on the swarm. We introduce a variant of H-PSO, in which the shape of the hierarchy is dynamically adapted during the execution of the algorithm. Another variant is to assign different behavior to the individual particles with respect to their level in the hierarchy. H-PSO and its variants are tested on a commonly used set of optimization functions and are compared to PSO using different standard neighborhood schemes.

  6. Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Davide Caputo

    2010-01-01

    Full Text Available In recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO and genetic algorithms (GA. This procedure is here implemented to optimize the communication energy consumption in a wireless network by selecting the optimal multihop routing schemes, with a suitable hybridization of different routing criteria, confirming itself as a flexible and useful tool for engineering applications.

  7. Towards diagnostic tools for analysing Swarm data through model retrievals

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Plank, Gernot; Haagmans, R.

    polar orbits between 300 and 550 km altitude. Goal of the current study is to build tools and to analyze datasets, in order to allow a fast diagnosis of the Swarm system performance in orbit during the commission phase and operations of the spacecraft. The effects on the reconstruction of the magnetic......, position errors and data gaps. The magnitude of the different error sources is kept variable so that we not only compare the impact of different error sources, but investigate also the effects on the magnetic field reconstruction for different noise levels. Further extension of this approach will allow...... to test the influence of ionospheric residual signal or the impact of data selection on the lithospheric retrieval. Initially, the study considers one satellite and emphasises on the lithospheric field reconstruction, but in a second step it is extended to a realistic Swarm constellation of three...

  8. Intrinsic Fluctuations and Driven Response of Insect Swarms

    Science.gov (United States)

    Ni, Rui; Puckett, James G.; Dufresne, Eric R.; Ouellette, Nicholas T.

    2015-09-01

    Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm's frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data.

  9. Learning from physics-based earthquake simulators: a minimal approach

    Science.gov (United States)

    Artale Harris, Pietro; Marzocchi, Warner; Melini, Daniele

    2017-04-01

    Physics-based earthquake simulators are aimed to generate synthetic seismic catalogs of arbitrary length, accounting for fault interaction, elastic rebound, realistic fault networks, and some simple earthquake nucleation process like rate and state friction. Through comparison of synthetic and real catalogs seismologists can get insights on the earthquake occurrence process. Moreover earthquake simulators can be used to to infer some aspects of the statistical behavior of earthquakes within the simulated region, by analyzing timescales not accessible through observations. The develoment of earthquake simulators is commonly led by the approach "the more physics, the better", pushing seismologists to go towards simulators more earth-like. However, despite the immediate attractiveness, we argue that this kind of approach makes more and more difficult to understand which physical parameters are really relevant to describe the features of the seismic catalog at which we are interested. For this reason, here we take an opposite minimal approach and analyze the behavior of a purposely simple earthquake simulator applied to a set of California faults. The idea is that a simple model may be more informative than a complex one for some specific scientific objectives, because it is more understandable. The model has three main components: the first one is a realistic tectonic setting, i.e., a fault dataset of California; the other two components are quantitative laws for earthquake generation on each single fault, and the Coulomb Failure Function for modeling fault interaction. The final goal of this work is twofold. On one hand, we aim to identify the minimum set of physical ingredients that can satisfactorily reproduce the features of the real seismic catalog, such as short-term seismic cluster, and to investigate on the hypothetical long-term behavior, and faults synchronization. On the other hand, we want to investigate the limits of predictability of the model itself.

  10. Future Earth: Reducing Loss By Automating Response to Earthquake Shaking

    Science.gov (United States)

    Allen, R. M.

    2014-12-01

    Earthquakes pose a significant threat to society in the U.S. and around the world. The risk is easily forgotten given the infrequent recurrence of major damaging events, yet the likelihood of a major earthquake in California in the next 30 years is greater than 99%. As our societal infrastructure becomes ever more interconnected, the potential impacts of these future events are difficult to predict. Yet, the same inter-connected infrastructure also allows us to rapidly detect earthquakes as they begin, and provide seconds, tens or seconds, or a few minutes warning. A demonstration earthquake early warning system is now operating in California and is being expanded to the west coast (www.ShakeAlert.org). In recent earthquakes in the Los Angeles region, alerts were generated that could have provided warning to the vast majority of Los Angelinos who experienced the shaking. Efforts are underway to build a public system. Smartphone technology will be used not only to issue that alerts, but could also be used to collect data, and improve the warnings. The MyShake project at UC Berkeley is currently testing an app that attempts to turn millions of smartphones into earthquake-detectors. As our development of the technology continues, we can anticipate ever-more automated response to earthquake alerts. Already, the BART system in the San Francisco Bay Area automatically stops trains based on the alerts. In the future, elevators will stop, machinery will pause, hazardous materials will be isolated, and self-driving cars will pull-over to the side of the road. In this presentation we will review the current status of the earthquake early warning system in the US. We will illustrate how smartphones can contribute to the system. Finally, we will review applications of the information to reduce future losses.

  11. Adaptive Remote-Sensing Techniques Implementing Swarms of Mobile Agents

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Loubriel, G.M.; Rbinett, R.D. III; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1999-04-01

    This paper focuses on our recent work at Sandia National Laboratories toward engineering a physics-based swarm of mobile vehicles for distributed sensing applications. Our goal is to coordinate a sensor array that optimizes sensor coverage and multivariate signal analysis by implementing artificial intelligence and evolutionary computational techniques. These intelligent control systems integrate both globally operating decision-making systems and locally cooperative information-sharing modes using genetically-trained neural networks. Once trained, neural networks have the ability to enhance real-time operational responses to dynamical environments, such as obstacle avoidance, responding to prevailing wind patterns, and overcoming other natural obscurants or interferences (jammers). The swarm realizes a collective set of sensor neurons with simple properties incorporating interactions based on basic community rules (potential fields) and complex interconnecting functions based on various neural network architectures, Therefore, the swarm is capable of redundant heterogeneous measurements which furnishes an additional degree of robustness and fault tolerance not afforded by conventional systems, while accomplishing such cognitive tasks as generalization, error correction, pattern recognition, and sensor fission. The robotic platforms could be equipped with specialized sensor devices including transmit/receive dipole antennas, chemical or biological sniffers in combination with recognition analysis tools, communication modulators, and laser diodes. Our group has been studying the collective behavior of an autonomous, multi-agent system applied to emerging threat applications. To accomplish such tasks, research in the fields of robotics, sensor technology, and swarms are being conducted within an integrated program. Mission scenarios under consideration include ground penetrating impulse radar (GPR) for detection of under-ground structures, airborne systems, and plume

  12. Particle swarm optimization for programming deep brain stimulation arrays.

    Science.gov (United States)

    Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D

    2017-02-01

    Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies

  13. Particle swarm optimization for programming deep brain stimulation arrays

    Science.gov (United States)

    Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

    2017-02-01

    Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon

  14. Steering Micro-Robotic Swarm by Dynamic Actuating Fields

    OpenAIRE

    Chao, Q.; Yu, J.; Dai, C; Xu, T.; Zhang, L.; Wang, C. C.; Jin, X.

    2016-01-01

    We present a general solution for steering microroboticswarm by dynamic actuating fields. In our approach, themotion of micro-robots is controlled by changing the actuatingdirection of a field applied to them. The time-series sequenceof actuating field’s directions can be computed automatically.Given a target position in the domain of swarm, a governingfield is first constructed to provide optimal moving directions atevery points. Following these directions, a robot can be drivento the target...

  15. Particle swarm optimization with recombination and dynamic linkage discovery.

    Science.gov (United States)

    Chen, Ying-Ping; Peng, Wen-Chih; Jian, Ming-Chung

    2007-12-01

    In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 Institute of Electrical and Electronics Engineers Congress on Evolutionary Computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.

  16. Optimized Landing of Autonomous Unmanned Aerial Vehicle Swarms

    Science.gov (United States)

    2012-06-01

    in a few hours. xvii THIS PAGE INTENTIONALLY LEFT BLANK xviii CHAPTER 1: INTRODUCTION 1.1 Background “The fiercest serpent may be overcome by a swarm... languages . Though Python has optimization-related packages and modeling languages such as Coopr and Pyomo, respectively, the lack of familiarity prevented...data structures that stay resident in the generating language , and/or using a compiled language . 32 Figure 3.12: Graphical Depiction of Scenario One

  17. Capability Driven Robotic Swarms in Reconnaissance-Based Operations

    Science.gov (United States)

    2008-05-02

    sensors is a TCRT1000 reflective optical sensor from ents. The first is a measurement of the norma 5 4 32 1 0 Scale 1:1 67 Figure 51 : Schematic of... IEEE International Conference on Robotics and Automation, pages 1464–1469, Taipei, Taiwan, Sept. 2003. [2] Barnes, L.; Alvis, W.; Fields, M...Valavanis, K.; Moreno, W., “Heterogeneous Swarm Formation Control Using Bivariate Normal Functions to Generate Potential Fields” IEEE Workshop on

  18. Synthesizing Sierpinski Antenna by Genetic Algorithm and Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2008-12-01

    Full Text Available The paper discusses the synthesis of the Sierpinski antenna operating at three prescribed frequencies: 0.9 GHz, 1.8 GHz (both GSM and 2.4 GHz (Bluetooth. In order to synthesize the antenna, a genetic algorithm and a particle swarm optimization were used. The numerical model of the antenna was developed in Zeland IE3D, optimization scripts were programmed in MATLAB. Results of both the optimization methods are compared and experimentally verified.

  19. The Information-Cost-Reward framework for understanding robot swarm foraging

    OpenAIRE

    Pitonakova, Lenka; Crowder, Richard; Bullock, Seth

    2017-01-01

    Demand for autonomous swarms, where robots can cooperate with each other without human intervention, is set to grow rapidly in the near future. Currently, one of the main challenges in swarm robotics is understanding how the behaviour of individual robots leads to an observed emergent collective performance. In this paper, a novel approach to understanding robot swarms that perform foraging is proposed in the form of the Information-Cost-Reward (ICR) framework. The framework relates the way i...

  20. Properties of a Formal Method to Model Emergence in Swarm-Based Systems

    Science.gov (United States)

    Rouff, Christopher; Vanderbilt, Amy; Truszkowski, Walt; Rash, James; Hinchey, Mike

    2004-01-01

    Future space missions will require cooperation between multiple satellites and/or rovers. Developers are proposing intelligent autonomous swarms for these missions, but swarm-based systems are difficult or impossible to test with current techniques. This viewgraph presentation examines the use of formal methods in testing swarm-based systems. The potential usefulness of formal methods in modeling the ANTS asteroid encounter mission is also examined.

  1. Mapping Ad Hoc Communications Network of a Large Number Fixed-Wing UAV Swarm

    Science.gov (United States)

    2017-03-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM by Alexis...SUBTITLE MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM 5. FUNDING NUMBERS 6. AUTHOR(S) Alexis Pospischil 7. PERFORMING... UAVs ) simultaneously as a self-organizing swarm. These vehicles were able to execute behaviors based on message notification from a single ground

  2. Particle Swarm and Ant Colony Approaches in Multiobjective Optimization

    Science.gov (United States)

    Rao, S. S.

    2010-10-01

    The social behavior of groups of birds, ants, insects and fish has been used to develop evolutionary algorithms known as swarm intelligence techniques for solving optimization problems. This work presents the development of strategies for the application of two of the popular swarm intelligence techniques, namely the particle swarm and ant colony methods, for the solution of multiobjective optimization problems. In a multiobjective optimization problem, the objectives exhibit a conflicting nature and hence no design vector can minimize all the objectives simultaneously. The concept of Pareto-optimal solution is used in finding a compromise solution. A modified cooperative game theory approach, in which each objective is associated with a different player, is used in this work. The applicability and computational efficiencies of the proposed techniques are demonstrated through several illustrative examples involving unconstrained and constrained problems with single and multiple objectives and continuous and mixed design variables. The present methodologies are expected to be useful for the solution of a variety of practical continuous and mixed optimization problems involving single or multiple objectives with or without constraints.

  3. A Solution Quality Assessment Method for Swarm Intelligence Optimization Algorithms

    Science.gov (United States)

    Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua

    2014-01-01

    Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of “value performance,” the “ordinal performance” is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and “good enough” set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method. PMID:25013845

  4. Solving Fractional Programming Problems based on Swarm Intelligence

    Science.gov (United States)

    Raouf, Osama Abdel; Hezam, Ibrahim M.

    2014-04-01

    This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint set, can be solved using the proposed approach. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using the two SI algorithms revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.

  5. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  6. A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

    Science.gov (United States)

    Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

    2005-01-01

    A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

  7. Support vector machine based on adaptive acceleration particle swarm optimization.

    Science.gov (United States)

    Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  8. Performance Evaluation of Hybrid Acoustic-Optical Underwater Swarm Networks

    Directory of Open Access Journals (Sweden)

    Samuela PERSIA

    2016-04-01

    Full Text Available The Underwater Swarm is a particular Underwater Network configuration characterized by nodes very close one to each other, with mobility capability. The structure of the network is that of a distributed network, in which the nodes, through the exchange of control information, will take decisions in collaborative manner. This type of network raises challenges for its effective design and development, for which the only use of acoustic communication as traditionally suggested in underwater communication could be not enough. A new emerging solution could be a hybrid solution that combines the use of acoustic and optical channel in order to overcome the acoustic channel limitations in underwater environment. In this work, we want to investigate how the acoustic and optical communications influence the Underwater Swarm performance by considering the Low Layers Protocols (Physical Layer, Data Link Layer and Network Layer effects over the two different propagation technologies. Performance simulations have been carried out to suggest how the new hybrid system could be designed. This study will permit to provide useful analysis for the real implementation of an Underwater Swarm based on hybrid communication technology.

  9. [Modeling of swarm formation as a consequence of autotaxis].

    Science.gov (United States)

    Senina, I N; Tiutiunov, Iu V

    2002-01-01

    The simple model of school and swarm formation is proposed within the frameworks of Eulerian space models (reaction-diffusion-advection system). Assuming that the schooling and the processes of birth-and-death act on different time scales, we have excluded the local kinetics of species (the reaction term) from the model. The spatial dynamics of animals is circumscribed by scalar field of density and vector field of velocity. The basis of animal aggregation in space is the ability of animals to move in certain direction, i.e. taxis. As an example of swarming strategy the behavior of midges is taken: we presume that individuals accelerate towards higher swarm density but change direction when the density exceeded some maximum. In other words, acceleration of movement is assumed to be proportional (with density-dependent coefficient of proportionality) to the gradient of species density. This statement poses the equation for species velocity. Thus, our model adds the differential equation for velocity of autotaxis to the standard advection-diffusion model. The linear analysis of 1D problem with zero-flux boundary conditions has showed that homogeneous nonzero equilibrium looses its stability when the movement rate of animals (coefficient of proportionality in velocity equation) overpasses some bifurcation value. The numerical experiments have confirmed analytical results, displaying stationary spatially heterogeneous solution (standing waves) for the detected supercritical value of the movement rate.

  10. Galactic Building Blocks Seen Swarming Around Andromeda

    Science.gov (United States)

    2004-02-01

    Green Bank, WV - A team of astronomers using the National Science Foundation's Robert C. Byrd Green Bank Telescope (GBT) has made the first conclusive detection of what appear to be the leftover building blocks of galaxy formation -- neutral hydrogen clouds -- swarming around the Andromeda Galaxy, the nearest large spiral galaxy to the Milky Way. This discovery may help scientists understand the structure and evolution of the Milky Way and all spiral galaxies. It also may help explain why certain young stars in mature galaxies are surprisingly bereft of the heavy elements that their contemporaries contain. Andromeda Galaxy This image depicts several long-sought galactic "building blocks" in orbit of the Andromeda Galaxy (M31). The newfound hydrogen clouds are depicted in a shade of orange (GBT), while gas that comprises the massive hydrogen disk of Andromeda is shown at high-resolution in blue (Westerbork Sythesis Radio Telescope). CREDIT: NRAO/AUI/NSF, WSRT (Click on Image for Larger Version) "Giant galaxies, like Andromeda and our own Milky Way, are thought to form through repeated mergers with smaller galaxies and through the accretion of vast numbers of even lower mass 'clouds' -- dark objects that lack stars and even are too small to call galaxies," said David A. Thilker of the Johns Hopkins University in Baltimore, Maryland. "Theoretical studies predict that this process of galactic growth continues today, but astronomers have been unable to detect the expected low mass 'building blocks' falling into nearby galaxies, until now." Thilker's research is published in the Astrophysical Journal Letters. Other contributors include: Robert Braun of the Netherlands Foundation for Research in Astronomy; Rene A.M. Walterbos of New Mexico State University; Edvige Corbelli of the Osservatorio Astrofisico di Arcetri in Italy; Felix J. Lockman and Ronald Maddalena of the National Radio Astronomy Observatory (NRAO) in Green Bank, West Virginia; and Edward Murphy of the

  11. PERFORMANCE OF PID CONTROLLER OF NONLINEAR SYSTEM USING SWARM INTELLIGENCE TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Neeraj Jain

    2016-07-01

    Full Text Available In this paper swarm intelligence based PID controller tuning is proposed for a nonlinear ball and hoop system. Particle swarm optimization (PSO, Artificial bee colony (ABC, Bacterial foraging optimization (BFO is some example of swarm intelligence techniques which are focused for PID controller tuning. These algorithms are also tested on perturbed ball and hoop model. Integral square error (ISE based performance index is used for finding the best possible value of controller parameters. Matlab software is used for designing the ball and hoop model. It is found that these swarm intelligence techniques have easy implementation & lesser settling & rise time compare to conventional methods.

  12. Improved quantum-behaved particle swarm optimization with local search strategy

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2017-03-01

    Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.

  13. The Ionospheric Bubble Index deduced from magnetic field and plasma observations onboard Swarm

    DEFF Research Database (Denmark)

    Park, Jaeheung; Noja, Max; Stolle, Claudia

    2013-01-01

    In the post-sunset tropical ionospheric F-region plasma density often exhibits depletions, which are usually called equatorial plasma bubbles (EPBs). In this paper we give an overview of the Swarm Level 2 Ionospheric Bubble Index (IBI), which is a standard scientific data of the Swarm mission....... This product called L2-IBI is generated from magnetic field and plasma observations onboard Swarm, and gives information as to whether a Swarm magnetic field observation is affected by EPBs. We validate the performance of the L2-IBI product by using magnetic field and plasma measurements from the CHAMP...

  14. Special issue “Swarm science results after 2 years in space”

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia; Floberghagen, Rune

    2016-01-01

    ) with an East-West separation of 1.4º in longitude corresponding to 155 km at the equator. The third satellite (Swarm Bravo) is in a slightly higher orbit (about 520 km altitude in September2016). Each of the three satellites carry a magnetometry package (consisting of absolute scalar magnetometer......Swarm is a three-satellite constellation mission launched by the European Space Agency (ESA) on 22 November2013. It consists of three identical spacecraft, two of which (Swarm Alpha and Swarm Charlie) are flying almost side-by-side in polar orbits at lower altitude (about 470 km in September 2016...

  15. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    Directory of Open Access Journals (Sweden)

    Huanqing Cui

    2017-03-01

    Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  16. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

    Science.gov (United States)

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-03-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  17. An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2017-01-01

    Full Text Available A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for multi-dimensional optimization problems, but also conceives a new adaptive cooperation mechanism to accomplish the information interaction among swarms and particles. Experiments are conducted on a set of benchmark functions, and the results show its better performance compared with traditional PSO algorithm in aspects of convergence, computational efficiency and avoiding premature convergence.

  18. Aftereffects of Subduction-Zone Earthquakes: Potential Tsunami Hazards along the Japan Sea Coast.

    Science.gov (United States)

    Minoura, Koji; Sugawara, Daisuke; Yamanoi, Tohru; Yamada, Tsutomu

    2015-10-01

    The 2011 Tohoku-Oki Earthquake is a typical subduction-zone earthquake and is the 4th largest earthquake after the beginning of instrumental observation of earthquakes in the 19th century. In fact, the 2011 Tohoku-Oki Earthquake displaced the northeast Japan island arc horizontally and vertically. The displacement largely changed the tectonic situation of the arc from compressive to tensile. The 9th century in Japan was a period of natural hazards caused by frequent large-scale earthquakes. The aseismic tsunamis that inflicted damage on the Japan Sea coast in the 11th century were related to the occurrence of massive earthquakes that represented the final stage of a period of high seismic activity. Anti-compressive tectonics triggered by the subduction-zone earthquakes induced gravitational instability, which resulted in the generation of tsunamis caused by slope failing at the arc-back-arc boundary. The crustal displacement after the 2011 earthquake infers an increased risk of unexpected local tsunami flooding in the Japan Sea coastal areas.

  19. An Mw = 7.7 slow earthquake in 1960 near the Aysén Fjord region, Chile

    Science.gov (United States)

    Kanamori, Hiroo; Rivera, Luis

    2017-10-01

    We re-examine the source characteristics of an Ms = 6.9 earthquake in Chile which occurred on 1960 June 6, near the Aysén Fjord region where a remarkable earthquake swarm occurred in 2007 with more than 7000 earthquakes and hundreds of landslides. The June 6 event occurred during the aftershock activity of the 1960 May 22, Mw = 9.5 great Chilean earthquake. A recently found well-calibrated strain seismogram of the June 6 event recorded at Isabella (ISA), California, is the impetus to this study. We confirm that this event is a slow earthquake caused by a source process extending at least 190 s with a seismic moment of M0 = 4.5 × 1020 Nṡm (Mw = 7.7). Although the mechanism cannot be uniquely determined, an NS trending right-lateral strike-slip mechanism is consistent with the ISA record. The depth cannot be constrained well, but the slowness of the event suggests that it may have occurred in a somewhat deeper high-temperature ductile environment caused by nearby subduction of the Chile Rise. The mechanism and the proximity of this event to the Liquiñe-Ofqui fault (LOF) which extends north-south over 1000 km along the Chilean coast suggest that the June 6 event represents a slip on this fault. The large moment of the June 6 event indicates strong interaction between the Nazca-South American plate boundary and the LOF with significant slip partitioning.

  20. Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm

    Science.gov (United States)

    Kia, Saeed; Sebt, Mohammad Hassan; Shahhosseini, Vahid

    2015-03-01

    Optimization techniques may be effective in finding the best modeling and shapes for reinforced concrete reservoirs (RCR) to improve their durability and mechanical behavior, particularly for avoiding or reducing the bending moments in these structures. RCRs are one of the major structures applied for reserving fluids to be used in drinking water networks. Usually, these structures have fixed shapes which are designed and calculated based on input discharges, the conditions of the structure's topology, and geotechnical locations with various combinations of static and dynamic loads. In this research, the elements of reservoir walls are first typed according to the performance analyzed; then the range of the membrane based on the thickness and the minimum and maximum cross sections of the bar used are determined in each element. This is done by considering the variable constraints, which are estimated by the maximum stress capacity. In the next phase, based on the reservoir analysis and using the algorithm of the PARIS connector, the related information is combined with the code for the PSO algorithm, i.e., an algorithm for a swarming search, to determine the optimum thickness of the cross sections for the reservoir membrane's elements and the optimum cross section of the bar used. Based on very complex mathematical linear models for the correct embedding and angles related to achain of peripheral strengthening membranes, which optimize the vibration of the structure, a mutual relation is selected between the modeling software and the code for a particle swarm optimization algorithm. Finally, the comparative weight of the concrete reservoir optimized by the peripheral strengthening membrane is analyzed using common methods. This analysis shows a 19% decrease in the bar's weight, a 20% decrease in the concrete's weight, and a minimum 13% saving in construction costs according to the items of a checklist for a concrete reservoir at 10,000 m3.

  1. Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Kia Saeed

    2015-03-01

    Full Text Available Optimization techniques may be effective in finding the best modeling and shapes for reinforced concrete reservoirs (RCR to improve their durability and mechanical behavior, particularly for avoiding or reducing the bending moments in these structures. RCRs are one of the major structures applied for reserving fluids to be used in drinking water networks. Usually, these structures have fixed shapes which are designed and calculated based on input discharges, the conditions of the structure's topology, and geotechnical locations with various combinations of static and dynamic loads. In this research, the elements of reservoir walls are first typed according to the performance analyzed; then the range of the membrane based on the thickness and the minimum and maximum cross sections of the bar used are determined in each element. This is done by considering the variable constraints, which are estimated by the maximum stress capacity. In the next phase, based on the reservoir analysis and using the algorithm of the PARIS connector, the related information is combined with the code for the PSO algorithm, i.e., an algorithm for a swarming search, to determine the optimum thickness of the cross sections for the reservoir membrane’s elements and the optimum cross section of the bar used. Based on very complex mathematical linear models for the correct embedding and angles related to achain of peripheral strengthening membranes, which optimize the vibration of the structure, a mutual relation is selected between the modeling software and the code for a particle swarm optimization algorithm. Finally, the comparative weight of the concrete reservoir optimized by the peripheral strengthening membrane is analyzed using common methods. This analysis shows a 19% decrease in the bar’s weight, a 20% decrease in the concrete’s weight, and a minimum 13% saving in construction costs according to the items of a checklist for a concrete reservoir at 10,000 m3.

  2. Make an Earthquake: Ground Shaking!

    Science.gov (United States)

    Savasci, Funda

    2011-01-01

    The main purposes of this activity are to help students explore possible factors affecting the extent of the damage of earthquakes and learn the ways to reduce earthquake damages. In these inquiry-based activities, students have opportunities to develop science process skills and to build an understanding of the relationship among science,…

  3. Earthquakes Threaten Many American Schools

    Science.gov (United States)

    Bailey, Nancy E.

    2010-01-01

    Millions of U.S. children attend schools that are not safe from earthquakes, even though they are in earthquake-prone zones. Several cities and states have worked to identify and repair unsafe buildings, but many others have done little or nothing to fix the problem. The reasons for ignoring the problem include political and financial ones, but…

  4. Are Earthquakes a Critical Phenomenon?

    Science.gov (United States)

    Ramos, O.

    2014-12-01

    Earthquakes, granular avalanches, superconducting vortices, solar flares, and even stock markets are known to evolve through power-law distributed events. During decades, the formalism of equilibrium phase transition has coined these phenomena as critical, which implies that they are also unpredictable. This work revises these ideas and uses earthquakes as the paradigm to demonstrate that slowly driven systems evolving through uncorrelated and power-law distributed avalanches (UPLA) are not necessarily critical systems, and therefore not necessarily unpredictable. By linking the correlation length to the pdf of the distribution, and comparing it with the one obtained at a critical point, a condition of criticality is introduced. Simulations in the classical Olami-Feder-Christensen (OFC) earthquake model confirm the findings, showing that earthquakes are not a critical phenomenon. However, one single catastrophic earthquake may show critical properties and, paradoxically, the emergence of this temporal critical behaviour may eventually carry precursory signs of catastrophic events.

  5. Testing earthquake source inversion methodologies

    KAUST Repository

    Page, Morgan T.

    2011-01-01

    Source Inversion Validation Workshop; Palm Springs, California, 11-12 September 2010; Nowadays earthquake source inversions are routinely performed after large earthquakes and represent a key connection between recorded seismic and geodetic data and the complex rupture process at depth. The resulting earthquake source models quantify the spatiotemporal evolution of ruptures. They are also used to provide a rapid assessment of the severity of an earthquake and to estimate losses. However, because of uncertainties in the data, assumed fault geometry and velocity structure, and chosen rupture parameterization, it is not clear which features of these source models are robust. Improved understanding of the uncertainty and reliability of earthquake source inversions will allow the scientific community to use the robust features of kinematic inversions to more thoroughly investigate the complexity of the rupture process and to better constrain other earthquakerelated computations, such as ground motion simulations and static stress change calculations.

  6. Early Earthquakes of the Americas

    Science.gov (United States)

    Ni, James

    2004-11-01

    Robert Kovach's second book looks at the interplay of earthquake and volcanic events, archeology, and history in the Americas. Throughout history, major earthquakes have caused the deaths of millions of people and have damaged countless cities. Earthquakes undoubtedly damaged prehistoric cities in the Americas, and evidence of these events could be preserved in archeological records. Kovach asks, Did indigenous native cultures-Indians of the Pacific Northwest, Aztecs, Mayas, and Incas-document their natural history? Some events have been explicitly documented, for example, in Mayan codices, but many may have been recorded as myth and legend. Kovach's discussions of how early cultures dealt with fearful events such as earthquakes and volcanic eruptions are colorful, informative, and entertaining, and include, for example, a depiction of how the Maya would talk to maize plants in their fields during earthquakes to reassure them.

  7. Slip Distribution of Two Recent Large Earthquakes in the Guerrero Segment of the Mexican Subduction Zone, and Their Relation to Previous Earthquakes, Silent Slip Events and Seismic Gaps

    Science.gov (United States)

    Hjorleifsdottir, V.; Ji, C.; Iglesias, A.; Cruz-Atienza, V. M.; Singh, S. K.

    2016-12-01

    In 2012 and 2014 mega-thrust earthquakes occurred approximately 300 km apart, in the state of Guerrero, Mexico. The westernmost half of the segment between them has not had a large earthquake in at least 100 years and most of the easternmost half last broke in 1957. However, down dip of both earthquakes, silent slip events have been reported, as well as in the gap between them (Kostoglodov et al 2003, Graham 2014). There are indications that the westernmost half has different frictional properties than the areas surrounds it. However, the two events at the edges of the zone also seem to behave in different manners, indicating a broad range of frictional properties in this area, with changes occurring over short distances. The 2012/03/20, M7.5 earthquake occurred near the Guerrero-Oaxaca border, between the towns of Ometepec (Gro.) and Pinotepa Nacional (Oax.). This earthquake is noteworthy for breaking the same asperities as two previously recorded earthquakes, the M7.2 1937 and M6.9 1982(a) earthquakes, in very large "repeating earthquakes". Furthermore, the density of repeating smaller events is larger in this zone than in other parts of the subduction zone (Dominguez et al, submitted) and this earthquake has had very many aftershocks for its size (UNAM Seis. group, 2013). The 2012 event may have broken two asperities (UNAM Seis. group, 2013). How the two asperities relate to the previous relatively smaller "large events", to the repeating earthquakes, the high number of aftershocks and to the slow slip event is not clear. The 2014/04/18 M 7.2 earthquake broke a patch on the edge of the Guerrero gap, that previously broke in the 1979 M7.4 earthquake as well as the 1943 M 7.4 earthquake. This earthquake, despite being smaller, had a much larger duration, few aftershocks and clearly ruptured two separate patches (UNAM Seis. group 2015). In this work we estimate the slip distributions for the 2012 and 2014 earthquakes, by combining the data used separately in

  8. The CATDAT damaging earthquakes database

    Directory of Open Access Journals (Sweden)

    J. E. Daniell

    2011-08-01

    Full Text Available The global CATDAT damaging earthquakes and secondary effects (tsunami, fire, landslides, liquefaction and fault rupture database was developed to validate, remove discrepancies, and expand greatly upon existing global databases; and to better understand the trends in vulnerability, exposure, and possible future impacts of such historic earthquakes.

    Lack of consistency and errors in other earthquake loss databases frequently cited and used in analyses was a major shortcoming in the view of the authors which needed to be improved upon.

    Over 17 000 sources of information have been utilised, primarily in the last few years, to present data from over 12 200 damaging earthquakes historically, with over 7000 earthquakes since 1900 examined and validated before insertion into the database. Each validated earthquake includes seismological information, building damage, ranges of social losses to account for varying sources (deaths, injuries, homeless, and affected, and economic losses (direct, indirect, aid, and insured.

    Globally, a slightly increasing trend in economic damage due to earthquakes is not consistent with the greatly increasing exposure. The 1923 Great Kanto ($214 billion USD damage; 2011 HNDECI-adjusted dollars compared to the 2011 Tohoku (>$300 billion USD at time of writing, 2008 Sichuan and 1995 Kobe earthquakes show the increasing concern for economic loss in urban areas as the trend should be expected to increase. Many economic and social loss values not reported in existing databases have been collected. Historical GDP (Gross Domestic Product, exchange rate, wage information, population, HDI (Human Development Index, and insurance information have been collected globally to form comparisons.

    This catalogue is the largest known cross-checked global historic damaging earthquake database and should have far-reaching consequences for earthquake loss estimation, socio-economic analysis, and the global

  9. Review Article: On the relation between the seismic activity and the Hurst exponent of the geomagnetic field at the time of the 2000 Izu swarm

    Directory of Open Access Journals (Sweden)

    F. Masci

    2013-09-01

    Full Text Available Many papers document the observation of earthquake-related precursory signatures in geomagnetic field data. However, the significance of these findings is ambiguous because the authors did not adequately take into account that these signals could have been generated by other sources, and the seismogenic origin of these signals have not been validated by comparison with independent datasets. Thus, they are not reliable examples of magnetic disturbances induced by the seismic activity. Hayakawa et al. (2004 claim that at the time of the 2000 Izu swarm the Hurst exponent of the Ultra-Low-Frequency (ULF: 0.001–10 Hz band of the geomagnetic field varied in accord with the energy released by the seismicity. The present paper demonstrates that the behaviour of the Hurst exponent was insufficiently investigated and also misinterpreted by the authors. We clearly show that during the Izu swarm the changes of the Hurst exponent were strongly related to the level of global geomagnetic activity and not to the increase of the local seismic activity.

  10. Tracking of Thermal Infrared Anomaly before One Strong Earthquake-In the Case of Ms6.2 Earthquake in Zadoi, Qinghai on October 17th, 2016

    Science.gov (United States)

    Zhang, Xuan; Zhang, Yuansheng; Tian, Xiufeng; Zhang, Qiaoli; Tian, Jie

    2017-10-01

    The detection and tracking process of thermal infrared anomaly before Ms6.2 earthquake in Zadio, Qinghai on October 17th, 2016, are reviewed and analyzed; then the different characteristics of thermal infrared brightness temperature data before this earthquake is described in details. According to these characteristics, the tracking process of thermal anomaly is divided into four stages, respectively identification stage, pre-judgment stage, tracking and approaching stage and verification stage. The anomaly forms and turning signals focused in each stage can provide clear indication information for earthquake pre-judgment; finally, the prediction efficiency and technical issues of this method are illustrated and discussed.

  11. The 2015 Gorkha Nepal Earthquake: Insights from Earthquake Damage Survey

    Directory of Open Access Journals (Sweden)

    Katsuichiro eGoda

    2015-06-01

    Full Text Available The 2015 Gorkha Nepal earthquake caused tremendous damage and loss. To gain valuable lessons from this tragic event, an earthquake damage investigation team was dispatched to Nepal from 1 May 2015 to 7 May 2015. A unique aspect of the earthquake damage investigation is that first-hand earthquake damage data were obtained 6 to 11 days after the mainshock. To gain deeper understanding of the observed earthquake damage in Nepal, the paper reviews the seismotectonic setting and regional seismicity in Nepal and analyzes available aftershock data and ground motion data. The earthquake damage observations indicate that the majority of the damaged buildings were stone/brick masonry structures with no seismic detailing, whereas the most of RC buildings were undamaged. This indicates that adequate structural design is the key to reduce the earthquake risk in Nepal. To share the gathered damage data widely, the collected damage data (geo-tagged photos and observation comments are organized using Google Earth and the kmz file is made publicly available.

  12. Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses

    Directory of Open Access Journals (Sweden)

    Bingbing Zhang

    2017-03-01

    Full Text Available Swarm is a European Space Agency (ESA project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1–25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD of 10−2 mm/s in radial (R, along-track (T and cross-track (N directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD. During high ionospheric activity, the mean Root Mean Square (RMS of Swarm GPS phase residuals is at 9–11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2–4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2–4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery.

  13. Discovery of Transition Rules for Cellular Automata Using Artificial Bee Colony and Particle Swarm Optimization Algorithms in Urban Growth Modeling

    Directory of Open Access Journals (Sweden)

    Fereydoun Naghibi

    2016-12-01

    Full Text Available This paper presents an advanced method in urban growth modeling to discover transition rules of cellular automata (CA using the artificial bee colony (ABC optimization algorithm. Also, comparisons between the simulation results of CA models optimized by the ABC algorithm and the particle swarm optimization algorithms (PSO as intelligent approaches were performed to evaluate the potential of the proposed methods. According to previous studies, swarm intelligence algorithms for solving optimization problems such as discovering transition rules of CA in land use change/urban growth modeling can produce reasonable results. Modeling of urban growth as a dynamic process is not straightforward because of the existence of nonlinearity and heterogeneity among effective involved variables which can cause a number of challenges for traditional CA. ABC algorithm, the new powerful swarm based optimization algorithms, can be used to capture optimized transition rules of CA. This paper has proposed a methodology based on remote sensing data for modeling urban growth with CA calibrated by the ABC algorithm. The performance of ABC-CA, PSO-CA, and CA-logistic models in land use change detection is tested for the city of Urmia, Iran, between 2004 and 2014. Validations of the models based on statistical measures such as overall accuracy, figure of merit, and total operating characteristic were made. We showed that the overall accuracy of the ABC-CA model was 89%, which was 1.5% and 6.2% higher than those of the PSO-CA and CA-logistic model, respectively. Moreover, the allocation disagreement (simulation error of the simulation results for the ABC-CA, PSO-CA, and CA-logistic models are 11%, 12.5%, and 17.2%, respectively. Finally, for all evaluation indices including running time, convergence capability, flexibility, statistical measurements, and the produced spatial patterns, the ABC-CA model performance showed relative improvement and therefore its superiority was

  14. ElarmS Earthquake Early Warning System Updates and Performance

    Science.gov (United States)

    Chung, A. I.; Allen, R. M.; Hellweg, M.; Henson, I. H.; Neuhauser, D. S.

    2015-12-01

    The ElarmS earthquake early warning algorithm has been detecting earthquakes throughout California since 2007. It is one of the algorithms that contributes to CISN's ShakeAlert, a prototype earthquake early warning system being developed for California. Overall, ElarmS performance has been excellent. Over the past year (July 1, 2014 - July 1, 2015), ElarmS successfully detected all but three of the significant earthquakes (M4+) that occurred within California. Of the 24 events that were detected, the most notable was the M6.0 South Napa earthquake that occurred on August 24, 2014. The first alert for this event was sent in 5.1 seconds with an initial magnitude estimate of M5.7. This alert provided approximately 8 seconds of warning of the impending S-wave arrival to the city of San Francisco. The magnitude estimate increased to the final value of M6.0 within 15 seconds of the initial alert. One of the two events that were not detected by ElarmS occurred within 30 seconds of the M6.0 Napa mainshock. The two other missed events occurred offshore in a region with sparse station coverage in the Eureka area. Since its inception, ElarmS has evolved and adapted to meet new challenges. On May 30, 2015, an extraordinarily deep (678km) M7.8 teleseism in Japan generated 5 false event detections for earthquakes greater than M4 within a minute due to the simultaneous arrival of the P-waves at stations throughout California. In order to improve the speed and accuracy of the ElarmS detections, we are currently exploring new methodologies to quickly evaluate incoming triggers from individual stations. Rapidly determining whether or not a trigger at a given station is due to a local earthquake or some other source (such as a distant teleseism) could dramatically increase the confidence in individual triggers and reduce false alerts.

  15. Earthquake Hazard and the Environmental Seismic Intensity (ESI) Scale

    Science.gov (United States)

    Serva, Leonello; Vittori, Eutizio; Comerci, Valerio; Esposito, Eliana; Guerrieri, Luca; Michetti, Alessandro Maria; Mohammadioun, Bagher; Mohammadioun, Georgianna C.; Porfido, Sabina; Tatevossian, Ruben E.

    2016-05-01

    The main objective of this paper was to introduce the Environmental Seismic Intensity scale (ESI), a new scale developed and tested by an interdisciplinary group of scientists (geologists, geophysicists and seismologists) in the frame of the International Union for Quaternary Research (INQUA) activities, to the widest community of earth scientists and engineers dealing with seismic hazard assessment. This scale defines earthquake intensity by taking into consideration the occurrence, size and areal distribution of earthquake environmental effects (EEE), including surface faulting, tectonic uplift and subsidence, landslides, rock falls, liquefaction, ground collapse and tsunami waves. Indeed, EEEs can significantly improve the evaluation of seismic intensity, which still remains a critical parameter for a realistic seismic hazard assessment, allowing to compare historical and modern earthquakes. Moreover, as shown by recent moderate to large earthquakes, geological effects often cause severe damage"; therefore, their consideration in the earthquake risk scenario is crucial for all stakeholders, especially urban planners, geotechnical and structural engineers, hazard analysts, civil protection agencies and insurance companies. The paper describes background and construction principles of the scale and presents some case studies in different continents and tectonic settings to illustrate its relevant benefits. ESI is normally used together with traditional intensity scales, which, unfortunately, tend to saturate in the highest degrees. In this case and in unpopulated areas, ESI offers a unique way for assessing a reliable earthquake intensity. Finally, yet importantly, the ESI scale also provides a very convenient guideline for the survey of EEEs in earthquake-stricken areas, ensuring they are catalogued in a complete and homogeneous manner.

  16. Determination of Design Basis Earthquake ground motion

    Energy Technology Data Exchange (ETDEWEB)

    Kato, Muneaki [Japan Atomic Power Co., Tokyo (Japan)

    1997-03-01

    This paper describes principle of determining of Design Basis Earthquake following the Examination Guide, some examples on actual sites including earthquake sources to be considered, earthquake response spectrum and simulated seismic waves. In sppendix of this paper, furthermore, seismic safety review for N.P.P designed before publication of the Examination Guide was summarized with Check Basis Earthquake. (J.P.N.)

  17. Earthquake Emergency Education in Dushanbe, Tajikistan

    Science.gov (United States)

    Mohadjer, Solmaz; Bendick, Rebecca; Halvorson, Sarah J.; Saydullaev, Umed; Hojiboev, Orifjon; Stickler, Christine; Adam, Zachary R.

    2010-01-01

    We developed a middle school earthquake science and hazards curriculum to promote earthquake awareness to students in the Central Asian country of Tajikistan. These materials include pre- and post-assessment activities, six science activities describing physical processes related to earthquakes, five activities on earthquake hazards and mitigation…

  18. Estimation of the magnetic field gradient tensor using the Swarm constellation

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Finlay, Chris; Olsen, Nils

    2014-01-01

    For the first time, part of the magnetic field gradient tensor is estimated in space by the Swarm mission. We investigate the possibility of a more complete estimation of the gradient tensor exploiting the Swarm constellation. The East-West gradients can be approximated by observations from...

  19. The impact of quorum sensing and swarming motility on Pseudomonas aeruginosa biofilm formation is nutritionally conditional

    DEFF Research Database (Denmark)

    Shrout, J.D.; Chopp, D.L.; Just, C.L.

    2006-01-01

    nutritionally conditional control of biofilm development through regulation of swarming motility. Examination of pilA and fliM mutant strains further supported the role of swarming motility in biofilm formation. These data led to a model proposing that the prevailing nutritional conditions dictate...

  20. Westward tilt of low-latitude plasma blobs as observed by the Swarm constellation

    DEFF Research Database (Denmark)

    Park, Jaeheung; Luehr, Hermann; Michaelis, Ingo

    2015-01-01

    In this study we investigate the three-dimensional structure of low-latitude plasma blobs using multi-instrument and multisatellite observations of the Swarm constellation. During the early commissioning phase the Swarm satellites were flying at the same altitude with zonal separation of about 0......., which are similar to the shell structure of equatorial plasma bubbles suggested by previous studies....

  1. Use of the Comprehensive Inversion method for Swarm satellite data analysis

    DEFF Research Database (Denmark)

    Sabaka, T. J.; Tøffner-Clausen, Lars; Olsen, Nils

    2013-01-01

    An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agen...

  2. An intelligent scheduling method based on improved particle swarm optimization algorithm for drainage pipe network

    Science.gov (United States)

    Luo, Yaqi; Zeng, Bi

    2017-08-01

    This paper researches the drainage routing problem in drainage pipe network, and propose an intelligent scheduling method. The method relates to the design of improved particle swarm optimization algorithm, the establishment of the corresponding model from the pipe network, and the process by using the algorithm based on improved particle swarm optimization to find the optimum drainage route in the current environment.

  3. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

    Science.gov (United States)

    Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614

  4. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

    Directory of Open Access Journals (Sweden)

    Miguel Duarte

    Full Text Available Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

  5. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

    Science.gov (United States)

    Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

  6. Emergent Runaway into an Avoidance Area in a Swarm of Soldier Crabs: e97870

    National Research Council Canada - National Science Library

    Hisashi Murakami; Takenori Tomaru; Yuta Nishiyama; Toru Moriyama; Takayuki Niizato; Yukio-Pegio Gunji

    2014-01-01

    ... on mass effects are rare. In this study, we show that a swarm of soldier crabs could spontaneously enter a water pool, which are usually avoided, by forming densely populated part of a swarm at the edge of the water pool...

  7. An iron detection system determines bacterial swarming initiation and biofilm formation

    NARCIS (Netherlands)

    Lin, Chuan-Sheng; Tsai, Yu-Huan; Chang, Chih-Jung; Tseng, Shun-Fu; Wu, Tsung-Ru; Lu, Chia-Chen; Wu, Ting-Shu; Lu, Jang-Jih; Horng, Jim-Tong; Martel, Jan; Ojcius, David M.; Lai, Hsin-Chih; Young, John D.; Andrews, S. C.; Robinson, A. K.; Rodriguez-Quinones, F.; Touati, D.; Yeom, J.; Imlay, J. A.; Park, W.; Marx, J. J.; Braun, V.; Hantke, K.; Cornelis, P.; Wei, Q.; Vinckx, T.; Troxell, B.; Hassan, H. M.; Verstraeten, N.; Lewis, K.; Hall-Stoodley, L.; Costerton, J. W.; Stoodley, P.; Kearns, D. B.; Losick, R.; Butler, M. T.; Wang, Q.; Harshey, R. M.; Lai, S.; Tremblay, J.; Deziel, E.; Overhage, J.; Bains, M.; Brazas, M. D.; Hancock, R. E.; Partridge, J. D.; Kim, W.; Surette, M. G.; Givskov, M.; Rather, P. N.; Houdt, R. Van; Michiels, C. W.; Mukherjee, S.; Inoue, T.; Frye, J. G.; McClelland, M.; McCarter, L.; Silverman, M.; Matilla, M. A.; Wu, Y.; Outten, F. W.; Singh, P. K.; Parsek, M. R.; Greenberg, E. P.; Welsh, M. J.; Banin, E.; Vasil, M. L.; Wosten, M. M.; Kox, L. F.; Chamnongpol, S.; Soncini, F. C.; Groisman, E. A.; Laub, M. T.; Goulian, M.; Krell, T.; Lai, H. C.; Lin, C. S.; Soo, P. C.; Tsai, Y. H.; Wei, J. R.; Wyckoff, E. E.; Mey, A. R.; Leimbach, A.; Fisher, C. F.; Payne, S. M.; Livak, K. J.; Schmittgen, T. D.; Clarke, M. B.; Hughes, D. T.; Zhu, C.; Boedeker, E. C.; Sperandio, V.; Stintzi, A.; Clarke-Pearson, M. F.; Brady, S. F.; Drake, E. J.; Gulick, A. M.; Qaisar, U.; Rowland, M. A.; Deeds, E. J.; Garcia, C. A.; Alcaraz, E. S.; Franco, M. A.; Rossi, B. N. Passerini de; Mehi, O.; Skaar, E. P.; Visaggio, D.; Nishino, K.; Dietz, P.; Gerlach, G.; Beier, D.; Bustin, S. A.; Schwyn, B.; Neilands, J. B.

    2016-01-01

    Iron availability affects swarming and biofilm formation in various bacterial species. However, how bacteria sense iron and coordinate swarming and biofilm formation remains unclear. Using Serratia marcescens as a model organism, we identify here a stage-specific iron-regulatory machinery comprising

  8. Bare bones particle swarm optimization with scale matrix adaptation.

    Science.gov (United States)

    Campos, Mauro; Krohling, Renato A; Enriquez, Ivan

    2014-09-01

    Bare bones particle swarm optimization (BBPSO) is a swarm algorithm that has shown potential for solving single-objective unconstrained optimization problems over continuous search spaces. However, it suffers of the premature convergence problem that means it may get trapped into a local optimum when solving multimodal problems. In order to address this drawback and improve the performance of the BBPSO, we propose a variant of this algorithm, named by us as BBPSO with scale matrix adaptation (SMA), SMA-BBPSO for short reference. In the SMA-BBPSO, the position of a particle is selected from a multivariate t-distribution with a rule for adaptation of its scale matrix. We use the multivariate t-distribution in its hierarchical form, as a scale mixtures of normal distributions. The t -distribution has heavier tails than those of the normal distribution, which increases the ability of the particles to escape from a local optimum. In addition, our approach includes the normal distribution as a particular case. As a consequence, the t -distribution can be applied during the optimization process by maintaining the proper balance between exploration and exploitation. We also propose a simple update rule to adapt the scale matrix associated with a particle. Our strategy consists of adapting the scale matrix of a particle such that the best position found by any particle in its neighborhood is sampled with maximum likelihood in the next iteration. A theoretical analysis was developed to explain how the SMA-BBPSO works, and an empirical study was carried out to evaluate the performance of the proposed algorithm. The experimental results show the suitability of the proposed approach in terms of effectiveness to find good solutions for all benchmark problems investigated. Nonparametric statistical tests indicate that SMA-BBPSO shows a statistically significant improvement compared with other swarm algorithms.

  9. New evidence of mating swarms of the malaria vector, Anopheles arabiensis in Tanzania.

    Science.gov (United States)

    Kaindoa, Emmanuel W; Ngowo, Halfan S; Limwagu, Alex; Mkandawile, Gustav; Kihonda, Japhet; Masalu, John Paliga; Bwanary, Hamis; Diabate, Abdoulaye; Okumu, Fredros O

    2017-01-01

    Background: Malaria mosquitoes form mating swarms around sunset, often at the same locations for months or years. Unfortunately, studies of Anopheles swarms are rare in East Africa, the last recorded field observations in Tanzania having been in 1983. Methods: Mosquito swarms were surveyed by trained volunteers between August-2016 and June-2017 in Ulanga district, Tanzania. Identified Anopheles swarms were sampled using sweep nets, and collected mosquitoes killed by refrigeration then identified by sex and taxa. Sub-samples were further identified by PCR, and spermatheca of females examined for mating status. Mosquito ages were estimated by observing female ovarian tracheoles and rotation of male genitalia. GPS locations, types of swarm markers, start/end times of swarming, heights above ground, mosquito counts/swarm, and copulation events were recorded. Results: A total of 216 Anopheles swarms were identified, characterized and mapped, from which 7,142 Anopheles gambiae s.l and 13 Anopheles funestus were sampled. The An. gambiae s.l were 99.6% males and 0.4% females, while the An. funestus were all males. Of all An. gambiae s.l analyzed by PCR, 86.7% were An. arabiensis, while 13.3% returned non-amplified DNA. Mean height (±SD) of swarms was 2.74±0.64m, and median duration was 20 (IQR; 15-25) minutes. Confirmed swarm markers included rice fields (25.5%), burned grounds (17.2%), banana trees (13%), brick piles (8.8%), garbage heaps (7.9%) and ant-hills (7.4%). Visual estimates of swarm sizes by the volunteers was strongly correlated to actual sizes by sweep nets (R=0.94; P=maturity. Conclusions: This is the first report of Anopheles swarms in Tanzania in more than three decades. The study demonstrates that the swarms can be identified and characterized by trained community-based volunteers, and highlights potential new interventions, for example targeted aerosol spraying of the swarms to improve malaria control.

  10. An evaluation of coordination relationships during earthquake emergency rescue using entropy theory

    Directory of Open Access Journals (Sweden)

    Huang Rong

    2015-05-01

    Full Text Available Emergency rescue after an earthquake is complex work which requires the participation of relief and social organizations. Studying earthquake emergency coordination efficiency can not only help rescue organizations to define their own rescue missions, but also strengthens inter-organizational communication and collaboration tasks, improves the efficiency of emergency rescue, and reduces loss. In this paper, collaborative entropy is introduced to study earthquake emergency rescue operations. To study the emergency rescue coordination relationship, collaborative matrices and collaborative entropy functions are established between emergency relief work and relief organizations, and the collaborative efficiency of the emergency rescue elements is determined based on this entropy function. Finally, the Lushan earthquake is used as an example to evaluate earthquake emergency rescue coordination efficiency.

  11. What is a surprise earthquake? The example of the 2002, San Giuliano (Italy event

    Directory of Open Access Journals (Sweden)

    M. Mucciarelli

    2005-06-01

    Full Text Available Both in scientific literature and in the mass media, some earthquakes are defined as «surprise earthquakes». Based on his own judgment, probably any geologist, seismologist or engineer may have his own list of past «surprise earthquakes». This paper tries to quantify the underlying individual perception that may lead a scientist to apply such a definition to a seismic event. The meaning is different, depending on the disciplinary approach. For geologists, the Italian database of seismogenic sources is still too incomplete to allow for a quantitative estimate of the subjective degree of belief. For seismologists, quantification is possible defining the distance between an earthquake and its closest previous neighbor. Finally, for engineers, the San Giuliano quake could not be considered a surprise, since probabilistic site hazard estimates reveal that the change before and after the earthquake is just 4%.

  12. The April 16th 2016 Pedernales Earthquake and Instituto Geofisico efforts for improving seismic monitoring in Ecuador

    Science.gov (United States)

    Ruiz, M. C.; Alvarado, A. P.; Hernandez, S.; Singaucho, J. C.; Gabriela, P.; Landeureau, A.; Perrault, M.; Acero, W.; Viracucha, C.; Plain, M.; Yepes, H. A.; Palacios, P.; Aguilar, J.; Mothes, P. A.; Segovia, M.; Pacheco, D. A.; Vaca, S.

    2016-12-01

    On April 16th, 2016, Ecuador's coastal provinces were struck by a devastating earthquake with 7.8 Mw magnitude. This event caused the earthquake-related largest dead toll in Ecuador (663 fatalities) since 1987 inland event. It provoked also a widespread destruction of houses, hotels, hospitals, affecting economic activities. Damaged was very worthy in the city of Pedernales, one of the nearest localities to the epicenter. Rupture area extended about a 100 km from the southern limit marked by the aftershock area of the 1998, 7.1 Mw earthquake to its northern limit controlled by the Punta Galera-Mompiche seismic zone, which is one of the several elongated swarms oriented perpendicular to the trench that occurred since 2007. Historical accounts of the Ecuador Colombia subduction zone have few mentions of felt earthquakes in the XVIII and XIX century likely related to poor communication and urban settlements in this area. A cycle of noticeable earthquakes began in 1896, including the 1906 8.8 Mw event and three earthquakes with magnitudes larger than 7.7 in the period 1942-1979, that preceded the 2016 earthquake. The Instituto Geofiísico of the Escuela Politécnica Nacional (IGEPN) has been monitoring the coastal area through the National Seismic Network (RENSIG) since 30 years back and recently enhanced through SENASCYT and SENPLADES supported projects. International collaboration from Japanese JICA and French IRD also contributed to expand the network and implement research projects in the area. Nowadays, the RENSIG has 135 seismic stations including 105 broadband and 5 strong motion velocimeters. Processing performed by Seiscomp3 software allows an automatic distribution of seismic parameters. A joint cooperation between IGEPN, the Navy Oceanographic Institute and the National Department for Risk Management is in charge of tsunami monitoring.

  13. The 1448 earthquake in Catalonia. Some effects and local reactions

    Directory of Open Access Journals (Sweden)

    R. Salicrù i Lluch

    1995-06-01

    Full Text Available The May 1448 earthquake. the last destructive one that took place in Catalonia in the Middle Ages, was known chiefly from several chronistic and narrative medieval sources. To these sources I add new previously unknown data proceeding Eroin documentary archival sources in Barcelona, and other data that up to now have been wrongly considered as a consequence of the weak quake recorded in September 1450. They allow us to locate the epicentre in the Vall&s Oriental, around Llinars, to deny the existence of two almost simultaneous earthquakes, and to extend the range of the earthquake damage. to pinpoint them better and to suppose that the effects of the 1448 earthquake were more important than we had previously thought. All this information leads to several reflections on compulsory critical analysis of historical seismic documentary sources in order for them to be useful to historical seismicity. Finally. by the opposition of the three lands of documentary sources that refer to the damage caused by the earthquake in the township of Mataro. I show how natural catastrophes could be manipulated, and the skill of a society in exploiting them to deal with an adverse situation.

  14. DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

    Energy Technology Data Exchange (ETDEWEB)

    Maiden, Wendy M. [Washington State Univ., Pullman, WA (United States)

    2010-05-01

    Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.

  15. Pseudomonad Swarming Motility Is Restricted to a Narrow Range of High Matric Water Potentials

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Smets, Barth F.

    2012-01-01

    significances. Our results indicate that swarming motility is restricted to a narrow range of high matric water potentials in the three pseudomonads tested (Pseudomonas sp. DSS73, Pseudomonas syringae B728a, and Pseudomonas aeruginosa PA14). The threshold below which no swarming was observed was about –0.45 k......Using a novel experimental system that allows control of the matric potential of an agar slab, we explored the hydration conditions under which swarming motility is possible. If there is recognition that this physical parameter is a key determinant of swarming, it is usually neither controlled nor......Pa for the first and about –0.1 kPa for the latter two. Above the threshold, the expansion rate of DSS73 swarms increased exponentially with the matric potential. Mutants deficient in surfactant production were totally or partially unable to expand rapidly on the surface of the agar slab. Our results thus suggest...

  16. Ionospheric phenomena before strong earthquakes

    Directory of Open Access Journals (Sweden)

    A. S. Silina

    2001-01-01

    Full Text Available A statistical analysis of several ionospheric parameters before earthquakes with magnitude M > 5.5 located less than 500 km from an ionospheric vertical sounding station is performed. Ionospheric effects preceding "deep" (depth h > 33 km and "crust" (h 33 km earthquakes were analysed separately. Data of nighttime measurements of the critical frequencies foF2 and foEs, the frequency fbEs and Es-spread at the middle latitude station Dushanbe were used. The frequencies foF2 and fbEs are proportional to the square root of the ionization density at heights of 300 km and 100 km, respectively. It is shown that two days before the earthquakes the values of foF2 averaged over the morning hours (00:00 LT–06:00 LT and of fbEs averaged over the nighttime hours (18:00 LT–06:00 LT decrease; the effect is stronger for the "deep" earthquakes. Analysing the coefficient of semitransparency which characterizes the degree of small-scale turbulence, it was shown that this value increases 1–4 days before "crust" earthquakes, and it does not change before "deep" earthquakes. Studying Es-spread which manifests itself as diffuse Es track on ionograms and characterizes the degree of large-scale turbulence, it was found that the number of Es-spread observations increases 1–3 days before the earthquakes; for "deep" earthquakes the effect is more intensive. Thus it may be concluded that different mechanisms of energy transfer from the region of earthquake preparation to the ionosphere occur for "deep" and "crust" events.

  17. Fracking, wastewater disposal, and earthquakes

    Science.gov (United States)

    McGarr, Arthur

    2016-03-01

    In the modern oil and gas industry, fracking of low-permeability reservoirs has resulted in a considerable increase in the production of oil and natural gas, but these fluid-injection activities also can induce earthquakes. Earthquakes induced by fracking are an inevitable consequence of the injection of fluid at high pressure, where the intent is to enhance permeability by creating a system of cracks and fissures that allow hydrocarbons to flow to the borehole. The micro-earthquakes induced during these highly-controlled procedures are generally much too small to be felt at the surface; indeed, the creation or reactivation of a large fault would be contrary to the goal of enhancing permeability evenly throughout the formation. Accordingly, the few case histories for which fracking has resulted in felt earthquakes have been due to unintended fault reactivation. Of greater consequence for inducing earthquakes, modern techniques for producing hydrocarbons, including fracking, have resulted in considerable quantities of coproduced wastewater, primarily formation brines. This wastewater is commonly disposed by injection into deep aquifers having high permeability and porosity. As reported in many case histories, pore pressure increases due to wastewater injection were channeled from the target aquifers into fault zones that were, in effect, lubricated, resulting in earthquake slip. These fault zones are often located in the brittle crystalline rocks in the basement. Magnitudes of earthquakes induced by wastewater disposal often exceed 4, the threshold for structural damage. Even though only a small fraction of disposal wells induce earthquakes large enough to be of concern to the public, there are so many of these wells that this source of seismicity contributes significantly to the seismic hazard in the United States, especially east of the Rocky Mountains where standards of building construction are generally not designed to resist shaking from large earthquakes.

  18. Particle Swarm Optimization for HW/SW Partitioning

    OpenAIRE

    Abdelhalim, M. B.; Habib, S. E. &#;D.

    2009-01-01

    In this chapter, the recent introduction of the Particle Swarm Optimization technique to solve the HW/SW partitioning problem is reviewed, along with its “re-exited PSO” modification. The re-exited PSO algorithm is a recently-introduced restarting technique for PSO. The Re-exited PSO proved to be highly effective for solving the HW/SW partitioning problem. Efficient cost function formulation is of a paramount importance for an efficient optimization algorithm. Each component in the design...

  19. OPTIMIZATION OF GRID RESOURCE SCHEDULING USING PARTICLE SWARM OPTIMIZATION ALGORITHM

    Directory of Open Access Journals (Sweden)

    S. Selvakrishnan

    2010-10-01

    Full Text Available Job allocation process is one of the big issues in grid environment and it is one of the research areas in Grid Computing. Hence a new area of research is developed to design optimal methods. It focuses on new heuristic techniques that provide an optimal or near optimal solution for large grids. By learning grid resource scheduling and PSO (Particle Swarm Optimization algorithm, this proposed scheduler allocates an application to a host from a pool of available hosts and applications by selecting the best match. PSO-based algorithm is more effective in grid resources scheduling with the favor of reducing the executing time and completing time.

  20. PID control for chaotic synchronization using particle swarm optimization

    Energy Technology Data Exchange (ETDEWEB)

    Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: wdchang@mail.stu.edu.tw

    2009-01-30

    In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.