WorldWideScience

Sample records for technological forecasting technique

  1. Forecast of technological development in ore mining branches on basis of modernization of technique and technology of mining practice

    Directory of Open Access Journals (Sweden)

    Alexandr Ivanovich Tatarkin

    2012-12-01

    Full Text Available Pro forma data for exploration of mineral raw material base of some territories Ural regions are given. Perspective trajectories of development of mineral raw complex of federal subjects Russia’s are characterized. On this basis are highlighted groups of region — saving, reducing, raising the level of raw specialization or diversifying own economy. Peculiarities of forecasting technological development in ore mining branches in the period of planned economy of the USSR are illustrated. Indexes of successfully working iron-ore open casts are given. Theraise of internal Russian demand on raw is grounded, for which satisfaction are needed:corresponding tax policy for innovative production, corporate innovative policy, creating fund of supporting ore mining, commercialization of scientific products and working out rules in the sphere of scientific and technical progress. Peculiarities of technological development of ore mining branches of industry are emphasized: necessity of modernization of enterprises and exploration of deposits in regions with not enough developed infrastructure and opportunity of using new system approach by forecasting. Thestages ofeffectiveexploration of deposits and the parameters of developing ore mining enterprises arefound out. Components of forecast of technological development are analyzed. World tendencies of developing ore mining industry and basic directions of forecast of developing ore mining branches are given. New effective technologies being used in the ore mining are analyzed in detail.

  2. Forecasting for strengthening technological development

    Directory of Open Access Journals (Sweden)

    Aida Mayerly Fúquene Montañez

    2010-05-01

    Full Text Available Producing technological innovation is currently one of the key items in being more competitive. However, production sectors are facing great challenges, including analysing a large amount of available technological and market information regarding the en- vironment for strategic decision-making and being able to launch themselves onto the market with technological developments bringing the desired economic returns. Several tools for analysing information have emerged for reducing the uncertainty of tech- nological and market changes. This article provides conceptual and reflective elements so that forecasting strengthens technolo- gical development (TD. Forecasting is initially proposed as being one of the future methods of analysis having a significant im- pact on decision-making, mainly within the field of economics but which could be extrapolated to making a contribution to TD. The techniques which have been the recent instrument for collecting information for producing forecasting are described, as is work about the concept of surveillance/monitoring and the processes used for coordinating such approaches. It can thus be sta- ted that they provide an excellent basis for strengthening TD by providing platforms for new or improved developments in pro- cesses or products. Reflection about these aspects provides perspectives for implementing technological forecasting (TF in pro- duction systems so that they obtain efficient and concrete results via deterministic methods as input in decision-making in techno- logy regarding its middle- and long-term competitiveness.

  3. Persistent forecasting of disruptive technologies

    National Research Council Canada - National Science Library

    Committee on Forecasting Future Disruptive Technologies; National Research Council

    ...) and the Defense Intelligence Agency (DIA) tasked the Committee for Forecasting Future Disruptive Technologies with providing guidance and insight on how to build a persistent forecasting system to predict, analyze, and reduce the impact...

  4. Handbook of Forecasting Techniques

    Science.gov (United States)

    1975-12-01

    Functions (illustrated as plots) show the form of the relationship between the information used to make judgments ind the judgments. 177L __ - eI Level...veniently subdivided into two types. In one type, the expert. consu~lt ed_ -’ ei rlttuited because of their extensive special know’.- edge about a topic...Because values forecasts are inherently vulnerable to criticisms from any quarter, and are also favorite targets of sarcasm , they can be useful in

  5. Prediction Techniques in Operational Space Weather Forecasting

    Science.gov (United States)

    Zhukov, Andrei

    2016-07-01

    The importance of forecasting space weather conditions is steadily increasing as our society is becoming more and more dependent on advanced technologies that may be affected by disturbed space weather. Operational space weather forecasting is still a difficult task that requires the real-time availability of input data and specific prediction techniques that are reviewed in this presentation, with an emphasis on solar and interplanetary weather. Key observations that are essential for operational space weather forecasting are listed. Predictions made on the base of empirical and statistical methods, as well as physical models, are described. Their validation, accuracy, and limitations are discussed in the context of operational forecasting. Several important problems in the scientific basis of predicting space weather are described, and possible ways to overcome them are discussed, including novel space-borne observations that could be available in future.

  6. Hydrocarbon Rocket Technology Impact Forecasting

    Science.gov (United States)

    Stuber, Eric; Prasadh, Nishant; Edwards, Stephen; Mavris, Dimitri N.

    2012-01-01

    Forecasting method is a normative forecasting technique that allows the designer to quantify the effects of adding new technologies on a given design. This method can be used to assess and identify the necessary technological improvements needed to close the gap that exists between the current design and one that satisfies all constraints imposed on the design. The TIF methodology allows for more design knowledge to be brought to the earlier phases of the design process, making use of tools such as Quality Function Deployments, Morphological Matrices, Response Surface Methodology, and Monte Carlo Simulations.2 This increased knowledge allows for more informed decisions to be made earlier in the design process, resulting in shortened design cycle time. This paper will investigate applying the TIF method, which has been widely used in aircraft applications, to the conceptual design of a hydrocarbon rocket engine. In order to reinstate a manned presence in space, the U.S. must develop an affordable and sustainable launch capability. Hydrocarbon-fueled rockets have drawn interest from numerous major government and commercial entities because they offer a low-cost heavy-lift option that would allow for frequent launches1. However, the development of effective new hydrocarbon rockets would likely require new technologies in order to overcome certain design constraints. The use of advanced design methods, such as the TIF method, enables the designer to identify key areas in need of improvement, allowing one to dial in a proposed technology and assess its impact on the system. Through analyses such as this one, a conceptual design for a hydrocarbon-fueled vehicle that meets all imposed requirements can be achieved.

  7. A Delphi forecast of technology in education

    Science.gov (United States)

    Robinson, B. E.

    1973-01-01

    The results are reported of a Delphi forecast of the utilization and social impacts of large-scale educational telecommunications technology. The focus is on both forecasting methodology and educational technology. The various methods of forecasting used by futurists are analyzed from the perspective of the most appropriate method for a prognosticator of educational technology, and review and critical analysis are presented of previous forecasts and studies. Graphic responses, summarized comments, and a scenario of education in 1990 are presented.

  8. TRIZ TECHNOLOGY FORECASTING AS QFD INPUT WITHIN THE NPD ACTIVITIES

    Institute of Scientific and Technical Information of China (English)

    Coulibaly Solomani; Hua Zhongsheng; Shi Qin; Wang Wei

    2004-01-01

    As a result of the fierceness of business competition,companies,to remain competitive,have to charm their customers by anticipating their needs and being able to rapidly develop exciting new products for them.To overcome this challenge,technology forecasting is considered as a powerful tool in today's business environment,while there are as many success stories as there are failures,a good application of this method will give a good result.A methodology of integration of patterns or lines of technology evolution in TRIZ parlance is presented,which is also known as TRIZ technology forecasting,as input to the QFD process to design a new product.For this purpose,TRIZ technology forecasting,one of the TRIZ major tools,is discussed and some benefits compared to the traditional forecasting techniques are highlighted.Then a methodology to integrate TRIZ technology forecasting and QFD process is highlighted.

  9. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  10. Review of techniques for magnetic storm forecasting

    Science.gov (United States)

    Detman, Thomas R.; Vassiliadis, Dimitris

    Today a wide variety of techniques are available for nowcasting and forecasting magnetic storm activity. A brief review of linear time series prediction techniques, with examples, is used to lay a foundation for the description of newer non-linear techniques based on state-space reconstruction. We illustrate the state-space prediction technique in application to predict Dst from ISEE-3 solar wind data. Upstream solar wind data, such as from ISEE-3 or WTND close to the L1 libration point, provide a prediction lead time of 0.5-1.5 hours. To go beyond the L1 prediction lead time some information about the solar wind between the Li point and the Sun is required. Remote sensing is the measurement of something from a distance, like solar magnetograms or X-ray images. Both empirical and physically based models, driven by remote sensing data, promise a way to make forecasts a few days into the future. A combination of the statistical time series prediction techniques operating on the output of physically based models, driven by remote sensing data, may offer the first capability of predicting magnetic storms a few days in advance. We illustrate this combination of techniques using the output of a potential field model [Wang and Sheeley, 1988] as input to a linear prediction filter to forecast the planetary geomagnetic index. Finally, practical forecasting requires verification. We describe some of the standard measures of forecast performance: skill score, prediction efficiency, and correlation coefficient. The value of cross validation testing is emphasized.

  11. Study of forecasting technique of power demand

    Energy Technology Data Exchange (ETDEWEB)

    Jung, T.Y. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

    1998-04-01

    Long-term forecast of power and energy demand become an important base of investment plan of the energy supply sector, and a study based on value data is indispensable since the expansion of energy supply requires a long construction period and a lot of investment capital. Total estimated power and energy demand of the whole economy is known to have considerable relationship with macroeconomics factors. This study reviews the Kalman filter technique and abnormal time series analysis technique which is useful in analyzing energy and macroeconomics data taking the form of pre-tallied time series data. Based on these, power demand and energy demand are estimated using real data and the most reliable technique, and long-term forecast of power and energy demand is tried up to year 2015 based on the forecasted values. It should be noted that power and energy demand of Korea shows the structurally-changing behavior based on the present while the forecast based on past data involves an assumption naturally that the trend continues from the past to the present. 15 refs., 8 figs., 15 tabs.

  12. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  13. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    M S Sridhar

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  14. Multivariate postprocessing techniques for probabilistic hydrological forecasting

    Science.gov (United States)

    Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

    2016-04-01

    Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power

  15. Forecasting methods for computer technology

    Energy Technology Data Exchange (ETDEWEB)

    Worlton, W.J.

    1978-01-01

    How well the computer site manager avoids future dangers and takes advantage of future opportunities depends to a considerable degree on how much anticipatory information he has available. People who rise in management are expected with each successive promotion to concern themselves with events further in the future. It is the function of technology projection to increase this stock of information about possible future developments in order to put planning and decision making on a more rational basis. Past efforts at computer technology projections have an accuracy that declines exponentially with time. Thus, precisely defined technology projections beyond about three years should be used with considerable caution. This paper reviews both subjective and objective methods of technology projection and gives examples of each. For an integrated view of future prospects in computer technology, a framework for technology projection is proposed.

  16. Forecasting methods for computer technology

    Energy Technology Data Exchange (ETDEWEB)

    Worlton, W.J.

    1978-01-01

    How well the computer site manager avoids future dangers and takes advantage of future opportunities depends to a considerable degree on how much anticipatory information he has available. People who rise in management are expected with each successive promotion to concern themselves with events further in the future. It is the function of technology projection to increase this stock of information about possible future developments in order to put planning and decision making on a more rational basis. Past efforts at computer technology projections have an accuracy that declines exponentially with time. Thus, precisely defined technology projections beyond about three years should be used with considerable caution. This paper reviews both subjective and objective methods of technology projection and gives examples of each. For an integrated view of future prospects in computer technology, a framework for technology projection is proposed.

  17. Forecasting Consumer Adoption of Information Technology and Services--Lessons from Home Video Forecasting.

    Science.gov (United States)

    Klopfenstein, Bruce C.

    1989-01-01

    Describes research that examined the strengths and weaknesses of technological forecasting methods by analyzing forecasting studies made for home video players. The discussion covers assessments and explications of correct and incorrect forecasting assumptions, and their implications for forecasting the adoption of home information technologies…

  18. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    ... the authors see as the innovations to technology management in the last 17 years: the Internet; the greater focus on group decision-making including process management and mechanism design; and desktop software that has transformed the analytical capabilities of technology managers"--Provided by publisher.

  19. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    "The new, revised edition of this book will build on this knowledge in the context of business organizations that now place a greater emphasis on technology to stay on the cutting edge of development...

  20. A Quantitative Approach for Measuring Technological Forecasting Capability

    OpenAIRE

    Ayhan, Mustafa Batuhan; Oztemel, Ercan

    2013-01-01

    Successful technological forecasting is important to invest scarce funds to emerging technologies. A generic model to measure the success of forecasting overall technological changes is introduced in this paper, called degree of Technological Forecasting Capability. It measures the success rate of forecasts in manufacturing processes based on four important aspects of a manufacturing system; Flow Time, Quantity/Day, Scrap Ratio, and New Investment Revenue. The proposed approach has been verif...

  1. Crop Yield Forecasted Model Based on Time Series Techniques

    Institute of Scientific and Technical Information of China (English)

    Li Hong-ying; Hou Yan-lin; Zhou Yong-juan; Zhao Hui-ming

    2012-01-01

    Traditional studies on potential yield mainly referred to attainable yield: the maximum yield which could be reached by a crop in a given environment. The new concept of crop yield under average climate conditions was defined in this paper, which was affected by advancement of science and technology. Based on the new concept of crop yield, the time series techniques relying on past yield data was employed to set up a forecasting model. The model was tested by using average grain yields of Liaoning Province in China from 1949 to 2005. The testing combined dynamic n-choosing and micro tendency rectification, and an average forecasting error was 1.24%. In the trend line of yield change, and then a yield turning point might occur, in which case the inflexion model was used to solve the problem of yield turn point.

  2. Forecasting Technological Discontinuities in the ICT Industry

    DEFF Research Database (Denmark)

    Hoisl, Karin; Stelzer, Tobias; Biala, Stefanie

    2015-01-01

    Building on the existing literature on evolutionary innovation and technological change, this paper aims to identify potential signals of technological discontinuities and to obtain assessments of experts to what extent these signals help them to predict discontinuities. Furthermore, we analyze...... in the ICT industry. The conjoint approach allows for a simulation of the forecasting process and considers utility trade-offs. The results show that for both types of experts the perceived benefit of users most highly contributes to predicting technological discontinuities. Internal experts assign more...... insights to the literature on R&D and innovation management....

  3. [Forecasting medical technologies--a global overview].

    Science.gov (United States)

    Tal, Orna

    2011-02-01

    Forecasting new medical technologies is a crucial stage in the process of decision-making in health care systems on national, organizational, professional and personal levels. Knowing what is on the horizon is essential. It is a tool facilitating preparedness and planning for updating health care in the western world. The challenge is to identify new promising technologies at an early stage. This is due to the uncertainty in estimating developing trends and consequences (clinical, financial, political, legal, social and ethical). A balance must be found between the desire to adopt new emerging technologies and the necessity for accountability n basing decisions on efficient evidence. Scarce resources, pervading health systems everywhere, emphasize the need for this mechanism to justify and improve health system determinations. Planning for the future has expanded into new medical fields, thereby reinforcing the importance of national forecasting bodies. This article presents the basic terminology and principles of medical technology forecasting and reviews the agencies involved in early warning systems including Israel.

  4. Wave Forecasting Using Neuro Wavelet Technique

    Directory of Open Access Journals (Sweden)

    Pradnya Dixit

    2014-12-01

    Full Text Available In the present work a hybrid Neuro-Wavelet Technique is used for forecasting waves up to 6 hr, 12 hr, 18 hr and 24 hr in advance using hourly measured significant wave heights at an NDBC station 41004 near the east coast of USA. The NW Technique is employed by combining two methods, Discrete Wavelet Transform and Artificial Neural Networks. The hourly data of previously measured significant wave heights spanning over 2 years from 2010 and 2011 is used to calibrate and test the models. The discrete wavelet transform of NWT analyzes frequency of signal with respect to time at different scales. It decomposes time series into low (approximate and high (detail frequency components. The decomposition of approximate can be carried out up to desired multiple levels in order to provide more detail and approximate components which provides relatively smooth varying amplitude series. The neural network is trained with decorrelated approximate and detail wavelet coefficients. The outputs of networks during testing are reconstructed back using inverse DWT. The results were judged by drawing the wave plots, scatter plots and other error measures. The developed models show reasonable accuracy in prediction of significant wave heights from 6 to 24 hours. To compare the results traditional ANN models were also developed at the same location using the same data and for same time interval.

  5. Forecasting, Forecasting

    Science.gov (United States)

    Michael A. Fosberg

    1987-01-01

    Future improvements in the meteorological forecasts used in fire management will come from improvements in three areas: observational systems, forecast techniques, and postprocessing of forecasts and better integration of this information into the fire management process.

  6. Extravehicular Activity Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2011-01-01

    The goal of NASA s current EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be to reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA hardware life and limited availability of the Extravehicular Mobility Units (EMUs) will eventually become a critical issue. The current EMU has successfully served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability will be needed and the current architectures and technologies under development offer significant improvements over the current flight systems. In addition to ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an

  7. Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

    Directory of Open Access Journals (Sweden)

    Diksha Kaur

    2015-01-01

    Full Text Available The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT along with the Auto Regressive Moving Average (ARMA is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE. A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN-Ensemble Kalman Filter (EnKF hybrid technique to verify the effectiveness of the proposed hybrid method. Results of the proposed hybrid show significant improvements in the forecasting error.

  8. Potential Technologies for Assessing Risk Associated with a Mesoscale Forecast

    Science.gov (United States)

    2015-10-01

    the actual model-forecast error—the 500-hPa root-mean-square error (RMSE) height error. Future work should also consider other forecast metrics such...ARL-TN-0708 ● OCT 2015 US Army Research Laboratory Potential Technologies for Assessing Risk Associated with a Mesoscale...OCT 2015 US Army Research Laboratory Potential Technologies for Assessing Risk Associated with a Mesoscale Forecast by Patrick A

  9. Intermediate Term Forecasting Techniques for Management.

    Science.gov (United States)

    1984-06-01

    nature. They normally employ the opinicn of experts to predict events at some distance into the future. They do not attempt tc forecast specific...smoothing effect. If N is too large, however, the average will fail tc detect trends. The predicted value will simply 34 tend towards the mean of the...34 Anamolies in Relationships Between Securities | Yields and Yield-Surroqates " Joural of v- 6, pp. 103-126, Sune7gief ember 81 o * -. . - . *,., TABLE

  10. Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

    OpenAIRE

    Diksha Kaur; Tek Tjing Lie; Nirmal K. C. Nair; Brice Vallès

    2015-01-01

    The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT) along with the Auto Regressive Moving Average (ARMA) is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE). A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN)-Ensemble Kalman Filter (EnKF) hy...

  11. Retrospective Analysis of Technology Forecasting: In-Scope Extension

    Science.gov (United States)

    2012-08-13

    were the means used to collect and verify forecasts, as well as the use of deep web research and broad sourcing. The study methodology is summarized in...include: • Searching the “ deep web ” to find forecast documents that are not indexed by standard search engines and therefore cannot be retrieved...used books and published reports that contain technological forecasts To search the deep web , we contracted with Bright Planet, which used proprietary

  12. Regression based peak load forecasting using a transformation technique

    Energy Technology Data Exchange (ETDEWEB)

    Haida, Takeshi; Muto, Shoichi (Tokyo Electric Power Co. (Japan). Computer and Communication Research Center)

    1994-11-01

    This paper presents a regression based daily peak load forecasting method with a transformation technique. In order to forecast the load precisely through a year, the authors should consider seasonal load change, annual load growth and the latest daily load change. To deal with these characteristics in the load forecasting, a transformation technique is presented. This technique consists of a transformation function with translation and reflection methods. The transformation function is estimated with the previous year's data points, in order that the function converts the data points into a set of new data points with preserving the shape of temperature-load relationships in the previous year. Then, the function is slightly translated so that the transformed data points will fit the shape of temperature-load relationships in the year. Finally, multivariate regression analysis with the latest daily loads and weather observations estimates the forecasting model. Large forecasting errors caused by the weather-load nonlinear characteristic in the transitional seasons such as spring and fall are reduced. Performance of the technique which is verified with simulations on actual load data of Tokyo Electric Power Company is also described.

  13. Subhourly wind forecasting techniques for wind turbine operations

    Energy Technology Data Exchange (ETDEWEB)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  14. Operational forecasting with the subgrid technique on the Elbe Estuary

    Science.gov (United States)

    Sehili, Aissa

    2017-04-01

    Modern remote sensing technologies can deliver very detailed land surface height data that should be considered for more accurate simulations. In that case, and even if some compromise is made with regard to grid resolution of an unstructured grid, simulations still will require large grids which can be computationally very demanding. The subgrid technique, first published by Casulli (2009), is based on the idea of making use of the available detailed subgrid bathymetric information while performing computations on relatively coarse grids permitting large time steps. Consequently, accuracy and efficiency are drastically enhanced if compared to the classical linear method, where the underlying bathymetry is solely discretized by the computational grid. The algorithm guarantees rigorous mass conservation and nonnegative water depths for any time step size. Computational grid-cells are permitted to be wet, partially wet or dry and no drying threshold is needed. The subgrid technique is used in an operational forecast model for water level, current velocity, salinity and temperature of the Elbe estuary in Germany. Comparison is performed with the comparatively highly resolved classical unstructured grid model UnTRIM. The daily meteorological forcing data are delivered by the German Weather Service (DWD) using the ICON-EU model. Open boundary data are delivered by the coastal model BSHcmod of the German Federal Maritime and Hydrographic Agency (BSH). Comparison of predicted water levels between classical and subgrid model shows a very good agreement. The speedup in computational performance due to the use of the subgrid technique is about a factor of 20. A typical daily forecast can be carried out within less than 10 minutes on standard PC-like hardware. The model is capable of permanently delivering highly resolved temporal and spatial information on water level, current velocity, salinity and temperature for the whole estuary. The model offers also the possibility to

  15. Forecasting and Technology Management: Statistical Theory and Methodological Issues

    DEFF Research Database (Denmark)

    Madsen, Henning

    technology. The conclusion is that widespread awareness of the growing force of technology and increasing concern over its impact means that forecasting of technological development and consequences is absolutely essential in many managerial decision situations. Examples cover e.g. identification...... of directions and targets for a R and D project, monitoring of a given area by a public agency, and evaluation of the future competitive situation for a company. This paper gives a brief introduction to the field of technological forecasting especially in relation to the strategic planning process...... as the essential phase where decisions concerning introduction of new technology are taken in companies. It includes as well a description of the problems related to the marketing area and of methods applicable in practising technological forecasting....

  16. Research and Development for Technology Evolution Potential Forecasting System

    Science.gov (United States)

    Gao, Changqing; Cao, Shukun; Wang, Yuzeng; Ai, Changsheng; Ze, Xiangbo

    Technology forecasting is a powerful weapon for many enterprises to gain an animate future. Evolutionary potential radar plot is a necessary step of some valuable methods to help the technology managers with right technical strategy. A software system for Technology Evolution Potential Forecasting (TEPF) with automatic radar plot drawing is introduced in this paper. The framework of the system and the date structure describing the concrete evolution pattern are illustrated in details. And the algorithm for radar plot drawing is researched. It is proved that the TEPF system is an effective tool during the technology strategy analyzing process with a referenced case study.

  17. Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique

    Science.gov (United States)

    Woodard, Crystal J.; Carey, L. D.; Petersen, W. A.; Roeder, W. P.

    2011-01-01

    The objective of this NASA MSFC and NOAA CSTAR funded study is to develop and test operational forecast algorithms for the prediction of lightning initiation utilizing the C-band dual-polarimetric radar, UAHuntsville's Advanced Radar for Meteorological and Operational Research (ARMOR). Although there is a rich research history of radar signatures associated with lightning initiation, few studies have utilized dual-polarimetric radar signatures (e.g., Z(sub dr) columns) and capabilities (e.g., fuzzy-logic particle identification [PID] of precipitation ice) in an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms. Improving lightning watch and warning performance will positively impact personnel safety in both work and leisure environments. Advanced warnings can provide space shuttle launch managers time to respond appropriately to secure equipment and personnel, while they can also provide appropriate warnings for spectators and players of leisure sporting events to seek safe shelter. Through the analysis of eight case dates, consisting of 35 pulse-type thunderstorms and 20 non-thunderstorm case studies, lightning initiation forecast techniques were developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce false alarms while maintaining high probability of detection and increasing lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various physically-based techniques using polarimetric variables and/or PID categories, which are strongly correlated to initial storm electrification (e.g., large precipitation ice production via drop freezing), were benchmarked against the operational reflectivity-only based approaches to find the best compromise between

  18. Enhancing COSMO-DE ensemble forecasts by inexpensive techniques

    Directory of Open Access Journals (Sweden)

    Zied Ben Bouallègue

    2013-02-01

    Full Text Available COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.

  19. Fuzzy neural network technique for system state forecasting.

    Science.gov (United States)

    Li, Dezhi; Wang, Wilson; Ismail, Fathy

    2013-10-01

    In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.

  20. Technology Reconciliation in the Remote Sensing ERA of United States Civilian Weather Forecasting: 1957 -1987.

    Science.gov (United States)

    Courain, Margaret Eileen

    This dissertation seeks to advance an understanding of the management of a major technological change in meteorology. The study examines the connection between changes in production and real-time use of data products derived from remote -sensing data collection and the evolution of U.S. civilian weather forecasting 1957-1987. The role of data collection in weather forecasting throughout history is examined, giving most attention to the 1957-1987 period. Critical to the real-time use of remote-sensing data was technology reconciliation. As defined by the author, it is the function or process by which data products and information derived from a new technology are made consistent or congruent with the existing data representations of a science in order to be used effectively. No model had been developed for a technology reconciliation process, or definition of the major role technology reconciliators played in the 30-year evolution of the science of weather forecasting. In order to assess the new remote-sensing data resource and its use in U.S. civilian weather forecasting, a Data Accountability and Review Technique (DART) was developed by the author in 1989. This technique was used to identify 16 of the technology reconciliators who developed and reconciled 25 new remote-sensing data products with the weather charts, maps and computer models of the National Weather Service. In five separate program teams, they were responsible for 15 improvements in the products--forecasts--and 18 improvement in the process of weather forecasting. A model of the technology reconciliation is proposed which can be applied to understanding the contemporary history of other sciences. The model, as well as the methods developed by the author to recognize the process of technology reconciliation has a much more general applicability beyond the sciences. Any field implementing new technology that promises to improve its whole way of working will be faced with the task of technology

  1. Technological Forecasting: Methodology Embrapa Brazilian Company

    Directory of Open Access Journals (Sweden)

    Eliane Fernandes Pietrovski

    2017-04-01

    Full Text Available Structural, economic and social changes are present in organizations. One of the strategies for decision-making, which leads to organizational policies, is the construction of feasible and doable technological scenarios that enable innovations to trigger the processes of technological change. This study to analyze the prospect of technological scenarios in the Brazilian Agricultural Research Agency a public organization of Research, Development and Innovation, based on scenario building in its operating environment. For the methodological procedures, a systemic review addressing the problem of searching for qualitative bias was developed. Taking this study’s point of view, the research is exploratory and descriptive. The sources of data collection were primary and secondary. The technical consistency of prospective scenarios for the company was highlighted in the results of this study, as this was the object of this analysis. Through the collected data it was possible to verify the inferences between literature and the applied method. [JEL Classification: O310].

  2. Application of integrated data mining techniques in stock market forecasting

    Directory of Open Access Journals (Sweden)

    Chin-Yin Huang

    2014-12-01

    Full Text Available Stock market is considered too uncertain to be predictable. Many individuals have developed methodologies or models to increase the probability of making a profit in their stock investment. The overall hit rates of these methodologies and models are generally too low to be practical for real-world application. One of the major reasons is the huge fluctuation of the market. Therefore, the current research focuses in the stock forecasting area is to improve the accuracy of stock trading forecast. This paper introduces a system that addresses the particular need. The system integrates various data mining techniques and supports the decision-making for stock trades. The proposed system embeds the top-down trading theory, artificial neural network theory, technical analysis, dynamic time series theory, and Bayesian probability theory. To experimentally examine the trading return of the presented system, two examples are studied. The first uses the Taiwan Semiconductor Manufacturing Company (TSMC data-set that covers an investment horizon of 240 trading days from 16 February 2011 to 23 January 2013. Eighty four transactions were made using the proposed approach and the investment return of the portfolio was 54% with an 80.4% hit rate during a 12-month period in which the TSMC stock price increased by 25% (from $NT 78.5 to $NT 101.5. The second example examines the stock data of Evergreen Marine Corporation, an international marine shipping company. Sixty four transactions were made and the investment return of the portfolio was 128% in 12 months. Given the remarkable investment returns in trading the example TSMC and Evergreen stocks, the proposed system demonstrates promising potentials as a viable tool for stock market forecasting.

  3. Computer technology forecast study for general aviation

    Science.gov (United States)

    Seacord, C. L.; Vaughn, D.

    1976-01-01

    A multi-year, multi-faceted program is underway to investigate and develop potential improvements in airframes, engines, and avionics for general aviation aircraft. The objective of this study was to assemble information that will allow the government to assess the trends in computer and computer/operator interface technology that may have application to general aviation in the 1980's and beyond. The current state of the art of computer hardware is assessed, technical developments in computer hardware are predicted, and nonaviation large volume users of computer hardware are identified.

  4. Operational flash flood forecasting platform based on grid technology

    Science.gov (United States)

    Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

    2009-04-01

    Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important

  5. An improved market penetration model for wind energy technology forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, P.D. [Helsinki Univ. of Technology, Espoo (Finland). Advanced Energy Systems

    1995-12-31

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  6. Forecasting display technique of human in network virtual environment

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The simulation of human in the distributed virtual environment is different from the simulation of ve hicle. Due to the human's many joints, to implement the real-time performance of the interaction between the virtual human and the environment, the quantity of information broadcasted in the network will be increased. So with the growing of the quantity of virtual human added to the network, the network burthen would augment rap idly. Therefore, for the simulation of virtual human this paper divides organically the motion parts of the body, which makes those body parts that often interact with the environment are described according to the joints while other parts are described according to the action information. Simultaneity, this paper adopts Dead Reckoning to reduce the quantity of information needed by maintaining the reality motion of virtual human. The experiment indicates that the forecasting display technique can efficiently reduce the network burthen and enhance the inter action of virtual human.

  7. Forecasting of innovative activity on the basis of application of technology of Foresight

    Directory of Open Access Journals (Sweden)

    Nazarova Natalia Leonidovna

    2011-10-01

    Full Text Available In article the basic questions of forecasting of innovative activity of economic systems are considered. Forsyte's bases are considered. Necessity, importance, success of application of technology of Forsyte for forecasting of innovative activity are proved.

  8. Analysis of Technology and Hydrological Regime Changes Induced Errors of Forecasts

    Science.gov (United States)

    Balint, G.; Rozsa, K.; Bartha, P.

    Real time hydrological forecasting results inevitable contain some errors. The source of the difference between calculated and observed values can be most diverse. In- put data of forecasting models are themselves not the true estimates of the ongoing processes U it can be followed by comparing operationally computed water levels with those checked and corrected on annual basis as they appear in hydrological year- books. Modelling errors are the most common ones and systematic or regular parts of those are often compensated by appropriate updating procedures. ARMA techniques are frequently used, but in most cases for major part of this error component can be compensated by n-step autoregressive procedure where n is a sufficiently low number. Basic statements are illustrated by the history of short term water level forecasting on the Hungarian section of the Danube. No strict calculation algorithm or defined tech- nique was used in the 1950s the forecast was the product of subjective judgement by an (usually) experienced forecaster. A simple linear regression expression was used in the 60s, early 70s often combined with results of an empirical flood routing tech- nique and/or during floods with results of graphical correlation technique used for flood crest forecasting. Most of the 70s and till mid-1980s the empirical flood routing technique developed by Szesztay remained in use, combined with flood crests fore- casting. The age of micro-computes changed the approaches in use. A flood routing model based on DLCM later combined with rainfall-runoff models (GAPI) took over as tool for daily forecasting. The graphical flood crests forecasting was replaced by a multivariate linear or polynomial regression technique. The change of techniques and more advanced technology was not followed by clear improvement represented by decreasing errors. This is mostly due to changes in hydrological regime for low flow periods often having the impact of the peak regime of hydro power

  9. Recalibration of CFS seasonal precipitation forecasts using statistical techniques for bias correction

    Science.gov (United States)

    Bliefernicht, Jan; Laux, Patrick; Siegmund, Jonatan; Kunstmann, Harald

    2013-04-01

    The development and application of statistical techniques with a special focus on a recalibration of meteorological or hydrological forecasts to eliminate the bias between forecasts and observations has received a great deal of attention in recent years. One reason is that retrospective forecasts are nowadays available which allows for a proper training and validation of this kind of techniques. The objective of this presentation is to propose several statistical techniques with different degree of complexity and to evaluate and compare their performance for a recalibration of seasonal ensemble forecasts of monthly precipitation. The techniques selected in this study range from straightforward normal score and quantile-quantile transformation, local scaling, to more sophisticated and novel statistical techniques such as Copula-based methodology recently proposed by Laux et al. (2011). The seasonal forecasts are derived from the Climate Forecast System Version 2. This version is the current coupled ocean-atmosphere general circulation model of the U.S. National Centers for Environmental Prediction used to provide forecasts up to nine months. The CFS precipitation forecasts are compared to monthly precipitation observations from the Global Precipitation Climatology Centre. The statistical techniques are tested for semi-arid regions in West Africa and the Indian subcontinent focusing on large-scale river basins such as the Ganges and the Volta basin. In both regions seasonal precipitation forecasts are a crucial source of information for the prediction of hydro-meteorological extremes, in particular for droughts. The evaluation is done using retrospective CFS ensemble forecast from 1982 to 2009. The training of the statistical techniques is done in a cross-validation mode. The outcome of this investigation illustrates large systematic differences between forecasts and observations, in particular for the Volta basin in West Africa. The selection of straightforward

  10. Forecasting and Technology Management: Statistical Theory and Methodological Issues

    DEFF Research Database (Denmark)

    Madsen, Henning

    The degree of development in the technical capability of many new devices and materials over their predecessors often is in multiples of improvement. These gains in performance are so great that they abruptly and drastically alter the means, effects, time, or costs of doing things. Thus, they dis......The degree of development in the technical capability of many new devices and materials over their predecessors often is in multiples of improvement. These gains in performance are so great that they abruptly and drastically alter the means, effects, time, or costs of doing things. Thus...... technology. The conclusion is that widespread awareness of the growing force of technology and increasing concern over its impact means that forecasting of technological development and consequences is absolutely essential in many managerial decision situations. Examples cover e.g. identification...

  11. An Analysis of the Performance of Artificial Neural Network Technique for Stock Market Forecasting

    Directory of Open Access Journals (Sweden)

    Dr. Ashutosh Kumar Bhatt

    2010-09-01

    Full Text Available In this paper, we showed a method to forecast the daily stock price using neural networks and the result of the Neural Network forecast is compared with the Statistical forecasting result. Stock price prediction is one of the emerging field in neural network forecastingarea. This paper also presents the Neural Networks ability to forecast the daily Stock Market Prices. Stock market prediction is very difficult since it depends on several known and unknown factors while the Artificial Neural Network is a popular technique for the stock market Forecasting. The Neural Network is based on the conceptof ‘Learn by Example’. In this paper, Neural Networks and Statistical techniques are employed to model and forecast the daily stock market prices and then the results of these two models are compared. The forecasting ability of these two models is accessed using MAPE, MSE and RMSE. The results show that Neural Networks, when trained with sufficient data, proper inputs and with proper architecture, can predict the stock market prices very well. Statistical technique though well built but their forecasting ability is reduced as the series become complex. Therefore, Neural Networks can be used as an better alternative technique for forecasting the daily stock market prices.

  12. Extravehicular Activity (EVA) Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2010-01-01

    Beginning in Fiscal Year (FY) 2011, Extravehicular activity (EVA) technology development became a technology foundational domain under a new program Enabling Technology Development and Demonstration. The goal of the EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA technology life and limited availability of the EMUs will become a critical issue eventually. The current Extravehicular Mobility Unit (EMU) has vastly served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability could be an option for the future mission applications building off of the technology development over the last several years. Besides ISS, potential mission applications include EVAs for

  13. A New Weather Forecasting Technique using Back Propagation Neural Network with Modified Levenberg-Marquardt Algorithm for Learning

    Directory of Open Access Journals (Sweden)

    I.Kadar Shereef

    2011-11-01

    Full Text Available Temperature warnings are essential forecasts since they are utilized to guard life and property. Temperature forecasting is the kind of science and technology to approximate the temperature for a future time and for a given place. Temperature forecasts are performed by means of gathering quantitative data regarding the in progress state of the atmosphere. The author in this paper utilized a neural network-based technique for determining the temperature in future. The Neural Networks package consists of various kinds of training or learning techniques. One such technique is Back Propagation Neural Network (BPN technique. The main advantage of the Back Propagation Neural Network technique is that it can reasonably estimated a large class of functions. This technique is more efficient than numerical differentiation. The simple meaning of this term is that the proposed technique has ability to confine the complex relationships among several factors that contribute to assured temperature. The proposed idea is tested using the real time dataset. In order to further improve the prediction accuracy, this paper uses Modified Levenberg-Marquardt (LM Algorithm for Neural Network learning. In modified LM, the learning parameters are modified. The proposed algorithm has good convergence and also it reduces the amount of oscillation in learning procedure. The proposed technique is compare with the usage of BPN and the practical working of meteorological department. The experimental result shows that the proposed technique results in better accuracy of prediction when compared to the conventional technique of weather prediction.

  14. Case studies on forecasting for innovative technologies: frequent revisions improve accuracy.

    Science.gov (United States)

    Lerner, Jeffrey C; Robertson, Diane C; Goldstein, Sara M

    2015-02-01

    Health technology forecasting is designed to provide reliable predictions about costs, utilization, diffusion, and other market realities before the technologies enter routine clinical use. In this article we address three questions central to forecasting's usefulness: Are early forecasts sufficiently accurate to help providers acquire the most promising technology and payers to set effective coverage policies? What variables contribute to inaccurate forecasts? How can forecasters manage the variables to improve accuracy? We analyzed forecasts published between 2007 and 2010 by the ECRI Institute on four technologies: single-room proton beam radiation therapy for various cancers; digital breast tomosynthesis imaging technology for breast cancer screening; transcatheter aortic valve replacement for serious heart valve disease; and minimally invasive robot-assisted surgery for various cancers. We then examined revised ECRI forecasts published in 2013 (digital breast tomosynthesis) and 2014 (the other three topics) to identify inaccuracies in the earlier forecasts and explore why they occurred. We found that five of twenty early predictions were inaccurate when compared with the updated forecasts. The inaccuracies pertained to two technologies that had more time-sensitive variables to consider. The case studies suggest that frequent revision of forecasts could improve accuracy, especially for complex technologies whose eventual use is governed by multiple interactive factors. Project HOPE—The People-to-People Health Foundation, Inc.

  15. Data-Driven Techniques for Regional Groundwater Level Forecasts

    Science.gov (United States)

    Chang, F. J.; Chang, L. C.; Tsai, F. H.; Shen, H. Y.

    2015-12-01

    Data-Driven Techniques for Regional Groundwater Level Forecasts Fi-John Changa, Li-Chiu Changb, Fong He Tsaia, Hung-Yu Shenba Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan, ROC. b Department of Water Resources and Environmental Engineering, Tamkang University, New Taipei City 25137, Taiwan, ROC..Correspondence to: Fi-John Chang (email: changfj@ntu.edu.tw)The alluvial fan of the Zhuoshui River in Taiwan is a good natural recharge area of groundwater. However, the over extraction of groundwater occurs in the coastland results in serious land subsidence. Groundwater systems are heterogeneous with diverse temporal-spatial patterns, and it is very difficult to quantify their complex processes. Data-driven methods can effectively capture the spatial-temporal characteristics of input-output patterns at different scales for accurately imitating dynamic complex systems with less computational requirements. In this study, we implement various data-driven methods to suitably predict the regional groundwater level variations for making countermeasures in response to the land subsidence issue in the study area. We first establish the relationship between regional rainfall, streamflow as well as groundwater levels and then construct intelligent groundwater level prediction models for the basin based on the long-term (2000-2013) regional monthly data sets collected from the Zhuoshui River basin. We analyze the interaction between hydrological factors and groundwater level variations; apply the self-organizing map (SOM) to obtain the clustering results of the spatial-temporal groundwater level variations; and then apply the recurrent configuration of nonlinear autoregressive with exogenous inputs (R-NARX) to predicting the monthly groundwater levels. As a consequence, a regional intelligent groundwater level prediction model can be constructed based on the adaptive results of the SOM. Results demonstrate that the development

  16. Comparison of Artificial Intelligence Techniques for river flow forecasting

    Directory of Open Access Journals (Sweden)

    M. Firat

    2008-01-01

    Full Text Available The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS and Artificial Neural Network (ANN methods, Generalized Regression Neural Networks (GRNN and Feed Forward Neural Networks (FFNN, and Auto-Regressive (AR models for forecasting of daily river flow is investigated and Seyhan River and Cine River was chosen as case study area. For the Seyhan River, the forecasting models are established using combinations of antecedent daily river flow records. On the other hand, for the Cine River, daily river flow and rainfall records are used in input layer. For both stations, the data sets are divided into three subsets, training, testing and verification data set. The river flow forecasting models having various input structures are trained and tested to investigate the applicability of ANFIS and ANN and AR methods. The results of all models for both training and testing are evaluated and the best fit input structures and methods for both stations are determined according to criteria of performance evaluation. Moreover the best fit forecasting models are also verified by verification set which was not used in training and testing processes and compared according to criteria. The results demonstrate that ANFIS model is superior to the GRNN and FFNN forecasting models, and ANFIS can be successfully applied and provide high accuracy and reliability for daily river flow forecasting.

  17. Fusion of Hurricane Models and Observations: Developing the Technology to Improve the Forecasts Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop the technology to provide the fusion of observations and operational model simulations to help improve the understanding and forecasting of hurricane...

  18. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  19. Forecasting the impact of virtual environment technology on maintenance training

    Science.gov (United States)

    Schlager, Mark S.; Boman, Duane; Piantanida, Tom; Stephenson, Robert

    1993-01-01

    To assist NASA and the Air Force in determining how and when to invest in virtual environment (VE) technology for maintenance training, we identified possible roles for VE technology in such training, assessed its cost-effectiveness relative to existing technologies, and formulated recommendations for a research agenda that would address instructional and system development issues involved in fielding a VE training system. In the first phase of the study, we surveyed VE developers to forecast capabilities, maturity, and estimated costs for VE component technologies. We then identified maintenance tasks and their training costs through interviews with maintenance technicians, instructors, and training developers. Ten candidate tasks were selected from two classes of maintenance tasks (seven aircraft maintenance and three space maintenance) using five criteria developed to identify types of tasks most likely to benefit from VE training. Three tasks were used as specific cases for cost-benefit analysis. In formulating research recommendations, we considered three aspects of feasibility: technological considerations, cost-effectiveness, and anticipated R&D efforts. In this paper, we describe the major findings in each of these areas and suggest research efforts that we believe will help achieve the goal of a cost-effective VE maintenance training system by the next decade.

  20. Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

    Science.gov (United States)

    Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

    2016-04-01

    Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

  1. Forecasting and observability: critical technologies for system operations with high PV penetration

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    Forecasting and monitoring technologies for photovoltaics are required on different spatial and temporal scales by multiple actors, from the owners of PV systems to transmission system operators. In this paper the Grid integration working group of the European Technology and Innovation Platform...... – Photovoltaics (ETIP PV) reviews the different use cases for these technologies, their current status, and the need for future developments. Power system operations require a real-time view of PV production for managing power reserves and for feeding shortterm forecasts. They also require forecasts on all...... for a cost/benefit analysis since the forecasting error can be linked to the prices charged for energy imbalance...

  2. An assessment of the value of seasonal forecasting technology for Western Australian farmers

    OpenAIRE

    Petersen, Elizabeth H.; Fraser, Rob W.

    2001-01-01

    Of the number of seasonal forecasting systems that have been developed of late, none are of practical benefit to Western Australian farmers. This study aims to improve the methodology for assessing the value of forecasting technology ex ante to its development, using the Merredin agricultural region of Western Australia as an illustration. Results suggest that a seasonal forecasting technology that provides a 30 per cent decrease in seasonal uncertainty increases annual profits by approximate...

  3. Ionospheric scintillation forecasting model based on NN-PSO technique

    Science.gov (United States)

    Sridhar, M.; Venkata Ratnam, D.; Padma Raju, K.; Sai Praharsha, D.; Saathvika, K.

    2017-09-01

    The forecasting and modeling of ionospheric scintillation effects are crucial for precise satellite positioning and navigation applications. In this paper, a Neural Network model, trained using Particle Swarm Optimization (PSO) algorithm, has been implemented for the prediction of amplitude scintillation index (S4) observations. The Global Positioning System (GPS) and Ionosonde data available at Darwin, Australia (12.4634° S, 130.8456° E) during 2013 has been considered. The correlation analysis between GPS S4 and Ionosonde drift velocities (hmf2 and fof2) data has been conducted for forecasting the S4 values. The results indicate that forecasted S4 values closely follow the measured S4 values for both the quiet and disturbed conditions. The outcome of this work will be useful for understanding the ionospheric scintillation phenomena over low latitude regions.

  4. Forecasting and observability: critical technologies for system operations with high PV penetration

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    Forecasting and monitoring technologies for photovoltaics are required on different spatial and temporal scales by multiple actors, from the owners of PV systems to transmission system operators. In this paper the Grid integration working group of the European Technology and Innovation Platform –...... for a cost/benefit analysis since the forecasting error can be linked to the prices charged for energy imbalance......Forecasting and monitoring technologies for photovoltaics are required on different spatial and temporal scales by multiple actors, from the owners of PV systems to transmission system operators. In this paper the Grid integration working group of the European Technology and Innovation Platform...... – Photovoltaics (ETIP PV) reviews the different use cases for these technologies, their current status, and the need for future developments. Power system operations require a real-time view of PV production for managing power reserves and for feeding shortterm forecasts. They also require forecasts on all...

  5. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  6. Comparison between genetic programming and an ensemble Kalman filter as data assimilation techniques for probabilistic flood forecasting

    Science.gov (United States)

    Mediero, L.; Garrote, L.; Requena, A.; Chávez, A.

    2012-04-01

    Flood events are among the natural disasters that cause most economic and social damages in Europe. Information and Communication Technology (ICT) developments in last years have enabled hydrometeorological observations available in real-time. High performance computing promises the improvement of real-time flood forecasting systems and makes the use of post processing techniques easier. This is the case of data assimilation techniques, which are used to develop an adaptive forecast model. In this paper, a real-time framework for probabilistic flood forecasting is presented and two data assimilation techniques are compared. The first data assimilation technique uses genetic programming to adapt the model to the observations as new information is available, updating the estimation of the probability distribution of the model parameters. The second data assimilation technique uses an ensemble Kalman filter to quantify errors in both hydrologic model and observations, updating estimates of system states. Both forecast models take the result of the hydrologic model calibration as a starting point and adapts the individuals of this first population to the new observations in each operation time step. Data assimilation techniques have great potential when are used in hydrological distributed models. The distributed RIBS (Real-time Interactive Basin Simulator) rainfall-runoff model was selected to simulate the hydrological process in the basin. The RIBS model is deterministic, but it is run in a probabilistic way through Monte Carlo simulations over the probability distribution functions that best characterise the most relevant model parameters, which were identified by a probabilistic multi-objective calibration developed in a previous work. The Manzanares River basin was selected as a case study. Data assimilation processes are computationally intensive. Therefore, they are well suited to test the applicability of the potential of the Grid technology to

  7. Application of nonlinear forecasting techniques for meteorological modeling

    Directory of Open Access Journals (Sweden)

    V. Pérez-Muñuzuri

    Full Text Available A nonlinear forecasting method was used to predict the behavior of a cloud coverage time series several hours in advance. The method is based on the reconstruction of a chaotic strange attractor using four years of cloud absorption data obtained from half-hourly Meteosat infrared images from Northwestern Spain. An exhaustive nonlinear analysis of the time series was carried out to reconstruct the phase space of the underlying chaotic attractor. The forecast values are used by a non-hydrostatic meteorological model ARPS for daily weather prediction and their results compared with surface temperature measurements from a meteorological station and a vertical sounding. The effect of noise in the time series is analyzed in terms of the prediction results.

    Key words: Meterology and atmospheric dynamics (mesoscale meteorology; general – General (new fields

  8. A formulation of multidimensional growth models for the assessment and forecast of technology attributes

    Science.gov (United States)

    Danner, Travis W.

    modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and

  9. Forecasting daily and monthly exchange rates with machine learning techniques

    OpenAIRE

    Papadimitriou, Theophilos; Gogas, Periklis; Plakandaras, Vasilios

    2013-01-01

    We combine signal processing to machine learning methodologies by introducing a hybrid Ensemble Empirical Mode Decomposition (EEMD), Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) model in order to forecast the monthly and daily Euro (EUR)/United States Dollar (USD), USD/Japanese Yen (JPY), Australian Dollar (AUD)/Norwegian Krone (NOK), New Zealand Dollar (NZD)/Brazilian Real (BRL) and South African Rand (ZAR)/Philippine Peso (PHP) exchange rates. After th...

  10. Review of methods for forecasting the market penetration of new technologies

    Energy Technology Data Exchange (ETDEWEB)

    Gilshannon, S.T.; Brown, D.R.

    1996-12-01

    In 1993 the DOE Office of Energy Efficiency and Renewable Energy (EE) initiated a program called Quality Metrics. Quality Metrics was developed to measure the costs and benefits of technologies being developed by EE R&D programs. The impact of any new technology is directly related to its adoption by the market. The techniques employed to project market adoption are critical to measuring a new technology`s impact. Our purpose was to review current market penetration theories and models and develop a recommended approach for evaluating the market penetration of DOE technologies. The following commonly cited innovation diffusion theories were reviewed to identify analytical approaches relevant to new energy technologies: (1) the normal noncumulative adopter distribution method, (2) the Bass Model, (3) the Mansfield-Blackman Model, (4) the Fisher-Pry Model, (5) a meta-analysis of innovation diffusion studies. Of the theories reviewed, the Bass and Mansfield-Blackman models were found most applicable to forecasting the market penetration of electricity supply technologies. Their algorithms require input estimates which characterize the technology adoption behavior of the electricity supply industry. But, inadequate work has been done to quantify the technology adoption characteristics of this industry. The following energy technology market penetration models were also reviewed: (1) DOE`s Renewable Energy Penetration (REP) Model, (2) DOE`s Electricity Capacity Planning Submodule of the National Energy Modeling System (NEMS), (3) the Assessment of Energy Technologies (ASSET) model by Regional Economic Research, Inc., (4) the Market TREK model by the Electric Power Research Institute (EPRI). The two DOE models were developed for electricity generation technologies whereas the Regional Economic Research and EPRI models were designed for demand- side energy technology markets. Therefore, the review and evaluation focused on the DOE models.

  11. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    OpenAIRE

    Shipra Banik; Khodadad Khan, A. F. M.; Mohammad Anwer

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsigh...

  12. Wind Power Forecasting techniques in complex terrain: ANN vs. ANN-CFD hybrid approach

    Science.gov (United States)

    Castellani, Francesco; Astolfi, Davide; Mana, Matteo; Burlando, Massimiliano; Meißner, Cathérine; Piccioni, Emanuele

    2016-09-01

    Due to technology developments, renewable energies are becoming competitive against fossil sources and the number of wind farms is growing, which have to be integrated into power grids. Therefore, accurate power forecast is needed and often operators are charged with penalties in case of imbalance. Yet, wind is a stochastic and very local phenomenon, and therefore hard to predict. It has a high variability in space and time and wind power forecast is challenging. Statistical methods, as Artificial Neural Networks (ANN), are often employed for power forecasting, but they have some shortcomings: they require data sets over several years and are not able to capture tails of wind power distributions. In this work a pure ANN power forecast is compared against a hybrid method, based on the combination of ANN and a physical method using computational fluid dynamics (CFD). The validation case is a wind farm sited in southern Italy in a very complex terrain, with a wide spread turbine layout.

  13. Application of forecasting structural cracks technique of 3DMove in Chengdao buried hill

    Institute of Scientific and Technical Information of China (English)

    WU Shiguo; WANG Xiuling; JI Yuxin; LIU Yuzhen; HAN Wengong

    2005-01-01

    3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

  14. COMPUTER MODELING AS ONE OF CONTEMPORARY METHODS OF FORECASTING IN PHARMACEUTICAL TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    S. O. Losenkova

    2014-01-01

    Full Text Available The work presents researches devoted to the forecasting of compatibility of additive and drug substances with a method of computer modeling for its use in composition elaboration and technology of transdermal therapeutic systems.

  15. The Modeling and Forecasting of the Technological and Innovation Development of a Transition-Economy Country

    OpenAIRE

    Kononenko, Igor; Repin, Anton

    2006-01-01

    The rule of GDP change influence on the investment inflows into the country’s economy for transition-economy countries has been found. The method for forecasting the innovational and scientific-technological development of a country, based on consequent use of simulation model of innovational and scientific-technological development of a country and of the method of forecasting the investment inflows into economy has been developed. The method was tested on the Ukrainian statistical data for ...

  16. Computer-Aided Analysis of Patents for Product Technology Maturity Forecasting

    Science.gov (United States)

    Liang, Yanhong; Gan, Dequan; Guo, Yingchun; Zhang, Peng

    Product technology maturity foresting is vital for any enterprises to hold the chance for innovation and keep competitive for a long term. The Theory of Invention Problem Solving (TRIZ) is acknowledged both as a systematic methodology for innovation and a powerful tool for technology forecasting. Based on TRIZ, the state -of-the-art on the technology maturity of product and the limits of application are discussed. With the application of text mining and patent analysis technologies, this paper proposes a computer-aided approach for product technology maturity forecasting. It can overcome the shortcomings of the current methods.

  17. Past speculations of future health technologies: a description of technologies predicted in 15 forecasting studies published between 1986 and 2010.

    Science.gov (United States)

    Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

    2017-07-31

    To describe and classify health technologies predicted in forecasting studies. A portrait describing health technologies predicted in 15 forecasting studies published between 1986 and 2010 that were identified in a previous systematic review. Health technologies are classified according to their type, purpose and clinical use; relating these to the original purpose and timing of the forecasting studies. All health-related technologies predicted in 15 forecasting studies identified in a previously published systematic review. Outcomes related to (1) each forecasting study including country, year, intention and forecasting methods used and (2) the predicted technologies including technology type, purpose, targeted clinical area and forecast timeframe. Of the 896 identified health-related technologies, 685 (76.5%) were health technologies with an explicit or implied health application and included in our study. Of these, 19.1% were diagnostic or imaging tests, 14.3% devices or biomaterials, 12.6% information technology systems, eHealth or mHealth and 12% drugs. The majority of the technologies were intended to treat or manage disease (38.1%) or diagnose or monitor disease (26.1%). The most frequent targeted clinical areas were infectious diseases followed by cancer, circulatory and nervous system disorders. The most frequent technology types were for: infectious diseases-prophylactic vaccines (45.8%), cancer-drugs (40%), circulatory disease-devices and biomaterials (26.3%), and diseases of the nervous system-equally devices and biomaterials (25%) and regenerative medicine (25%). The mean timeframe for forecasting was 11.6 years (range 0-33 years, median=10, SD=6.6). The forecasting timeframe significantly differed by technology type (p=0.002), the intent of the forecasting group (p<0.001) and the methods used (p<001). While description and classification of predicted health-related technologies is crucial in preparing healthcare systems for adopting new innovations

  18. Assessing public forecasts to encourage accountability: The case of MIT's Technology Review.

    Science.gov (United States)

    Funk, Jeffrey

    2017-01-01

    Although high degrees of reliability have been found for many types of forecasts purportedly due to the existence of accountability, public forecasts of technology are rarely assessed and continue to have a poor reputation. This paper's analysis of forecasts made by MIT's Technology Review provides a rare assessment and thus a means to encourage accountability. It first shows that few of the predicted "breakthrough technologies" currently have large markets. Only four have sales greater than $10 billion while eight technologies not predicted by Technology Review have sales greater than $10 billion including three with greater than $100 billion and one other with greater than $50 billion. Second, possible reasons for these poor forecasts are then discussed including an over emphasis on the science-based process of technology change, sometimes called the linear model of innovation. Third, this paper describes a different model of technology change, one that is widely used by private companies and that explains the emergence of those technologies that have greater than $10 billion in sales. Fourth, technology change and forecasts are discussed in terms of cognitive biases and mental models.

  19. Research on Forecast Technology of Mine Gas Emission Based on Fuzzy Data Mining(FDM)

    Institute of Scientific and Technical Information of China (English)

    XU Chang-kai; WANG Yao-cai; WANG Jun-wei

    2004-01-01

    The safe production of coalmine can be further improved by forecasting the quantity of gas emission based on the real-time data and historical data which the gas monitoring system has saved. By making use of the advantages of data warehouse and data mining technology for processing large quantity of redundancy data, the method and its application of forecasting mine gas emission quantity based on FDM were studied. The constructing fuzzy resembling relation and clustering analysis were proposed, which the potential relationship inside the gas emission data may be found. The mode finds model and forecast model were presented, and the detailed approach to realize this forecast was also proposed, which have been applied to forecast the gas emission quantity efficiently.

  20. Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study

    CERN Document Server

    Join, Cédric; Fliess, Michel; Muselli, Marc; Nivet, Marie Laure; Paoli, Christophe; Chaxel, Frédéric

    2014-01-01

    This communication is devoted to solar irradiance and irradiation short-term forecasts, which are useful for electricity production. Several different time series approaches are employed. Our results and the corresponding numerical simulations show that techniques which do not need a large amount of historical data behave better than those which need them, especially when those data are quite noisy.

  1. A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting

    OpenAIRE

    Francisco Martínez-Álvarez; Alicia Troncoso; Gualberto Asencio-Cortés; Riquelme, José C

    2015-01-01

    Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely used. In particular, this work explores the application of these techniques to time series forecasting. Although classical statistical-based methods provides reasonably good results, the result of the application of data mining outperforms those of ...

  2. Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    problem. To this end we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, well known to time series econometricians, and the Marginal Bridge Estimator, better known to statisticians and microeconometricians.The performance of these three model...... selectors is compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series of the G7 countries and the four Scandinavian ones, and focus on forecasting......In this work we consider forecasting macroeconomic variables during an economic crisis. The focus is on a speci…c class of models, the so-called single hidden-layer feedforward autoregressive neural network models. What makes these models interesting in the present context is that they form a class...

  3. A Hybrid Model for the Mid-Long Term Runoff Forecasting by Evolutionary Computaion Techniques

    Institute of Scientific and Technical Information of China (English)

    Zou Xiu-fen; Kang Li-shan; Cae Hong-qing; Wu Zhi-jian

    2003-01-01

    The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology fore casting ones. The observed data is divided into two parts: the slow "smooth and steady" data, and the fast "coarse and fluctuation" data. Under the divide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in tbe northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM).

  4. New Technology Trends in Education: Seven Years of Forecasts and Convergence

    Science.gov (United States)

    Martin, Sergio; Diaz, Gabriel; Sancristobal, Elio; Gil, Rosario; Castro, Manuel; Peire, Juan

    2011-01-01

    Each year since 2004, a new Horizon Report has been released. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the mid-term (the next 2 years) and the long term (the next 4 years). This paper analyzes the evolution of technology trends…

  5. PATTERNS OF SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENT AND THEIR USE IN FORECASTING

    Directory of Open Access Journals (Sweden)

    N. I. Komkov

    2010-01-01

    Full Text Available In article laws of scientifically-technological development are considered. Their number concern traditional, base and new, formed. Possibilities and ways of the account of the listed laws are shown at forecasting of prospects of scientifically-technological development.

  6. Forecasting the innovation and technology based economic development as a component of the choice of anti-crisis strategy

    OpenAIRE

    L. Fedulova

    2009-01-01

    The author reveals the role of the technology factor in crisis situations and justifies the significance of the mechanisms of technological forecasting in the choice of strategic guidelines of a country's development. She proposes a conceptual model of the system of scientifico-technological forecasting and shows its place in the innovation based renewal of economic activities.

  7. Forecasting the innovation and technology based economic development as a component of the choice of anti-crisis strategy

    OpenAIRE

    L. Fedulova

    2009-01-01

    The author reveals the role of the technology factor in crisis situations and justifies the significance of the mechanisms of technological forecasting in the choice of strategic guidelines of a country's development. She proposes a conceptual model of the system of scientifico-technological forecasting and shows its place in the innovation based renewal of economic activities.

  8. A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Francisco Martínez-Álvarez

    2015-11-01

    Full Text Available Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely used. In particular, this work explores the application of these techniques to time series forecasting. Although classical statistical-based methods provides reasonably good results, the result of the application of data mining outperforms those of classical ones. Hence, this work faces two main challenges: (i to provide a compact mathematical formulation of the mainly used techniques; (ii to review the latest works of time series forecasting and, as case study, those related to electricity price and demand markets.

  9. Image Science Technology Forecasting on offset printing:A Patent Analysis Approach

    Institute of Scientific and Technical Information of China (English)

    Liu Yaojen

    2004-01-01

    Technology forecasting is a important approach which can help researcher to point out what will be of technology in the future. There are many well-developed approaches and methodologies can do technology forecasting well, for example S-curve analysis. Patent analysis is another way to analyze technology development trend. Patent is a kind of intellectual property right can help researcher avoid to infringe patent owned by competitor. Patent analysis can help researcher and corporate find out what are major technology trends and point out what field has low patent infringement risk.It will describe what patent analysis is briefly and how to process, and use patent analysis to analysis image reproduction technology trend. Offset printing technology is the main field discussed. When running analysis will follow the international patent classification (IPC) category and use USPTO patent database.

  10. Multimodel SuperEnsemble technique for quantitative precipitation forecasts in Piemonte region

    Directory of Open Access Journals (Sweden)

    D. Cane

    2010-02-01

    Full Text Available The Multimodel SuperEnsemble technique is a powerful post-processing method for the estimation of weather forecast parameters reducing direct model output errors. It has been applied to real time NWP, TRMM-SSM/I based multi-analysis, Seasonal Climate Forecasts and Hurricane Forecasts. The novelty of this approach lies in the methodology, which differs from ensemble analysis techniques used elsewhere.

    Several model outputs are put together with adequate weights to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure, the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts, involving a new accurate statistical method for bias correction and a wide spectrum of results over Piemonte very dense non-GTS weather station network.

  11. MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

    Science.gov (United States)

    Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

    2014-01-01

    MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free-magnetic-energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the "Present MAG4" technique and each of three alternative techniques, called "McIntosh Active-Region Class," "Total Magnetic Flux," and "Next MAG4." We do this by using (1) the MAG4 database of magnetograms and major-flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique-performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4).

  12. Nonlinear techniques for forecasting solar activity directly from its time series

    Science.gov (United States)

    Ashrafi, S.; Roszman, L.; Cooley, J.

    1993-01-01

    This paper presents numerical techniques for constructing nonlinear predictive models to forecast solar flux directly from its time series. This approach makes it possible to extract dynamical in variants of our system without reference to any underlying solar physics. We consider the dynamical evolution of solar activity in a reconstructed phase space that captures the attractor (strange), give a procedure for constructing a predictor of future solar activity, and discuss extraction of dynamical invariants such as Lyapunov exponents and attractor dimension.

  13. Fuzzy Time Series Forecasting Model Based on Automatic Clustering Techniques and Generalized Fuzzy Logical Relationship

    Directory of Open Access Journals (Sweden)

    Wangren Qiu

    2015-01-01

    Full Text Available In view of techniques for constructing high-order fuzzy time series models, there are three types which are based on advanced algorithms, computational method, and grouping the fuzzy logical relationships. The last type of models is easy to be understood by the decision maker who does not know anything about fuzzy set theory or advanced algorithms. To deal with forecasting problems, this paper presented novel high-order fuzz time series models denoted as GTS (M, N based on generalized fuzzy logical relationships and automatic clustering. This paper issued the concept of generalized fuzzy logical relationship and an operation for combining the generalized relationships. Then, the procedure of the proposed model was implemented on forecasting enrollment data at the University of Alabama. To show the considerable outperforming results, the proposed approach was also applied to forecasting the Shanghai Stock Exchange Composite Index. Finally, the effects of parameters M and N, the number of order, and concerned principal fuzzy logical relationships, on the forecasting results were also discussed.

  14. Improved Satellite Techniques for Monitoring and Forecasting the Transition of Hurricanes to Extratropical Storms

    Science.gov (United States)

    Folmer, Michael; Halverson, Jeffrey; Berndt, Emily; Dunion, Jason; Goodman, Steve; Goldberg, Mitch

    2014-01-01

    The Geostationary Operational Environmental Satellites R-Series (GOES-R) and Joint Polar Satellite System (JPSS) Satellite Proving Grounds have introduced multiple proxy and operational products into operations over the last few years. Some of these products have proven to be useful in current operations at various National Weather Service (NWS) offices and national centers as a first look at future satellite capabilities. Forecasters at the National Hurricane Center (NHC), Ocean Prediction Center (OPC), NESDIS Satellite Analysis Branch (SAB) and the NASA Hurricane and Severe Storms Sentinel (HS3) field campaign have had access to a few of these products to assist in monitoring extratropical transitions of hurricanes. The red, green, blue (RGB) Air Mass product provides forecasters with an enhanced view of various air masses in one complete image to help differentiate between possible stratospheric/tropospheric interactions, moist tropical air masses, and cool, continental/maritime air masses. As a compliment to this product, a new Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) Ozone product was introduced in the past year to assist in diagnosing the dry air intrusions seen in the RGB Air Mass product. Finally, a lightning density product was introduced to forecasters as a precursor to the new Geostationary Lightning Mapper (GLM) that will be housed on GOES-R, to monitor the most active regions of convection, which might indicate a disruption in the tropical environment and even signal the onset of extratropical transition. This presentation will focus on a few case studies that exhibit extratropical transition and point out the usefulness of these new satellite techniques in aiding forecasters forecast these challenging events.

  15. Impact of Sophisticated Stationary Forecast Techniques on the Bullwhip Effect in a Supply Chain

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The bullwhip effect in a multistage supply chain was analyzed using sophisticated stationary forecasts (third order moving average and third order exponential smoothing forecasts ). The third order exponential smoothing and third order moving average forecasts sometimes have a variance reducing effect on the supply chain.In a supply chain with positively correlated or independent and identically distributed (i. i. d) demands, the order variance based on simple moving average forecast (or simple exponential smoothing forecast) is larger than the order variance based on second order moving average forecast (or second order exponential smoothing forecast) ,and the order variance based on second order moving average forecast ( or second order exponential smoothing forecast) is larger than the order variance based on third order moving average forecast( or third order exponential smoothing forecast). In addition, for i.i.d demands, third order exponential smoothing forecast leads to a larger variation than third order moving average forecast.

  16. INVESTIGATION OF AN APPROPRIATE TECHNOLOGY FORECASTING PROCESS FOR SASOL FOR THE NEW ENERGY ERA

    Directory of Open Access Journals (Sweden)

    L. Ma

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Sasol is predominantly an energy-based company. The energy industry is undergoing a fundamental transformation that may have a profound impact on Sasol’s overall business. This study has been carried out to investigate the need to establish an appropriate technology forecasting process for the new energy era. Although there exist some evidence of technology forecasting within Sasol, they are scattered and unsophisticated. Technology forecasting as a tool enables managers to make better decisions and encourages networking and knowledge sharing within the organization, an important trait of a ‘Learning Organization’. A theoretical framework of technology forecasting for Sasol is thereby formulated.

    AFRIKAANSE OPSOMMING: Sasol is hoofsaaklik 'n energie-gebaseerde maatskappy. Die energie-industrie ondergaan tans 'n diepgaande transformasie wat 'n wesenlike impak kan hê op Sasol se totale besigheid. Hierdie studie is uitgevoer om die behoefte vir 'n toepaslike tegnologie-vooruitskattingsproses vir die nuwe energie-era te bepaal. Alhoewel daar bewyse bestaan vir tegnologie-vooruitskatting binne Sasol, is dit verspreid en ongesofistikeerd. Tegnologie-vooruitskatting is 'n gereedskapstuk wat bestuurders in staat stel om beter besluite te neem en bevorder die gebruik van netwerke en kennis-uitruiling binne die organisasie, 'n belangrike eienskap van 'n 'Lerende Organisasie'. 'n Teoretiese raamwerk vir tegnologie-vooruitskatting vir Sasol word sodoende geformuleer.

  17. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    Science.gov (United States)

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  18. Forecasting performances of three automated modelling techniques during the economic crisis 2007-2009

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    2014-01-01

    into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians....... The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four......In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact...

  19. New Techniques for Real-Time Stage Forecasting for Tributaries in the Nashville Area

    Science.gov (United States)

    Charley, W.; Moran, B.; LaRosa, J.

    2011-12-01

    On Saturday, May 1, 2010, heavy rain began falling in the Cumberland River Valley, Tennessee, and continued through the following day. 13.5 inches was measured at Nashville, an unprecedented amount that doubled the previous 2-day record, and exceeded the May monthly total record of 11 inches. Elsewhere in the valley, amounts of over 19 inches were measured. This intensity of rainfall quickly overwhelmed tributaries to the Cumberland in the Nashville area, causing wide-spread and serious flooding. Tractor-trailers and houses were seen floating down Mill Creek, a primary tributary in the south eastern area of Nashville. Twenty-six people died and over 2 billion dollars in damage occurred as a result of the flood. Since that time, several other significant rainfall events have occurred in the area. As a result of the flood, agencies in the Nashville area want better capabilities to forecast stages for the local tributaries. Better stage forecasting will help local agencies close roads, evacuate homes and businesses and similar actions. An interagency group, consisting of Metro Nashville Water Services and Office of Emergency Management, the National Weather Service, the US Geological Survey and the US Army Corps of Engineers, has been established to seek ways to better forecast short-term events in the region. It should be noted that the National Weather Service has the official responsibility of forecasting stages. This paper examines techniques and algorithms that are being developed to meet this need and the practical aspects of integrating them into a usable product that can quickly and accurately forecast stages in the short-time frame of the tributaries. This includes not only the forecasting procedure, but also the procedure to acquire the latest precipitation and stage data to make the forecasts. These procedures are integrated into the program HEC-RTS, the US Army Corps of Engineers Real-Time Simulation program. HEC-RTS is a Java-based integration tool that

  20. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  1. The Status of Budget Forecasting

    Directory of Open Access Journals (Sweden)

    Daniel W. Williams

    2016-11-01

    Full Text Available This article examines the breadth of the current forecast literature as it relates to public budget making. It serves to provide summary information to decision-makers who otherwise do not have the resources to learn more than a small amount focused on much more narrowly defined areas of forecasting (such as the politics of forecast bias. Next, it serves those who perform forecasting related to budgeting by reviewing the current methods and practices commonly used in this domain. It also provides a ground level for future public budget forecasting research. Finally, this article identifies several areas in which the public forecasting literature needs additional development. Several of these areas, such as the effectiveness of nonregression-based forecasting techniques, are quite important to the majority of governments in the United States and other subnational jurisdictions, where budget offices are limited and resource investments in technology are scarce.

  2. Modeling Growth Trend and Forecasting Techniques for Vehicular Population in India

    Directory of Open Access Journals (Sweden)

    Kartikeya Jha

    2013-06-01

    Full Text Available Forecasting and estimation of growth in vehicular population is a sine qua non of any major transportation engineering development, requires capturing the past trend and using it to predict the future trend based on qualified assumptions, simulations and models created using explanatory variables. This work attempts to review the in vogue approaches and investigate a more contemporary approach, the Time Series (TS Analysis. Three fundamentally different methods were explored and results from each of these analyses were collated to check for respective levels of accuracy in predicting vehicular population for the same target year. Within the scope of this study and estimation, results obtained from TS Analysis were found to be considerably more accurate than those from Trend Line Analysis and observably better than those from Econometric Analysis. To reinforce these observations and inferences drawn, a second set of analysis was done on more recent input by using AADT data from PeMS, California. Inter alia this was carried out to contrast any statistical improvement observed when doing TS analysis with rich and accurate data. With all the data sets used and locations analyzed for forecasting, the Time Series analysis technique was invariably found to be a potent tool for forecasting.

  3. Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

    KAUST Repository

    Fernandes, José Antonio

    2015-01-01

    The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

  4. Superhydrophobic Materials Technology-PVC Bonding Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Hunter, Scott R. [Oak Ridge National Laboratory; Efird, Marty [VeloxFlow, LLC

    2013-05-03

    The purpose of the technology maturation project was to develop an enhanced application technique for applying diatomaceous earth with pinned polysiloxane oil to PVC pipes and materials. The oil infiltration technique is applied as a spray of diluted oil in a solvent onto the superhydrophobic diatomaceous earth substrate. This makes the surface take on the following characteristics: wet-cleanable; anti-biofouling; waterproof; and anti-corrosion. The project involved obtaining input and supplies from VeloxFlow and the development of successful techniques that would quickly result in a commercial license agreement with VeloxFlow and other companies that use PVC materials in a variety of other fields of use.

  5. Wood Technology: Techniques, Processes, and Products

    Science.gov (United States)

    Oatman, Olan

    1975-01-01

    Seven areas of wood technology illustrates applicable techniques, processes, and products for an industrial arts woodworking curriculum. They are: wood lamination; PEG (polyethylene glycol) diffusion processes; wood flour and/or particle molding; production product of industry; WPC (wood-plastic-composition) process; residential construction; and…

  6. Forecasting the Development of Different Solar Cell Technologies

    Directory of Open Access Journals (Sweden)

    Arturo Morales-Acevedo

    2013-01-01

    Full Text Available Solar cells are made of several materials and device structures with the main goal of having maximum efficiency at low cost. Some types of solar cells have shown a rapid efficiency progress whereas others seem to remain constant as a consequence of different factors such as the technological and economic ones. Using information published by the National Renewable Energy Laboratory (NREL about the increase of solar cells record efficiency, we apply a simple mathematical model to estimate the evolution in the near future for the different cell technologies. Here, as an example, we use data for solar cells made with representative materials and structures of each of the three “PV generations.”

  7. Improving the Army’s Next Effort in Technology Forecasting

    Science.gov (United States)

    2010-09-01

    Cortisol Effects on Body Mass, Blood Pressure, and Cholesterol in the General Population,” Hypertension, 33 (1999), 1364–1368. 13 V. Technological...of HPA (hypothalamus-pituitary-adrenal) axis stress response hormones, notably cortisol and b-endorphin.62 These authors suggest that high hardy...stressors. In short, hardy individuals are more likely to remain emotionally stable during stressful situations. In support of this interpretation is

  8. Socioeconomic Impact Assessment: Communications Industry. Phase III. Technology Forecast.

    Science.gov (United States)

    1979-02-02

    follows: stagflation, balanced growth, rapid growth. That is, it requires less time to move from ideation to market introduction under a rapid growth...consider the relative relationship among the socio-economic scenarios. The assertions of import include: 1. The period between ideation and market ... introduction for a technology is influenced by the socio-economic scenario. It is likely that the time requirement, i.e. innovation lag, will be ordered as

  9. Survey of Long-Term Technology Forecasting Methodologies

    Science.gov (United States)

    2002-11-01

    betting scores at horse races (Ref. 11). The RAND research was directed at improving the use of expert predictions in policy - making. Procedures were... policy formulation, but we have no way of knowing whether it did. Much of the thinking was heavily oriented toward then-current problems, such as the...asked to put themselves into a future time frame in which some technology is assumed to be commonplace. Then, the group is asked to “ backcast ” to

  10. Forecasting the Development of Different Solar Cell Technologies

    OpenAIRE

    Arturo Morales-Acevedo; Gaspar Casados-Cruz

    2013-01-01

    Solar cells are made of several materials and device structures with the main goal of having maximum efficiency at low cost. Some types of solar cells have shown a rapid efficiency progress whereas others seem to remain constant as a consequence of different factors such as the technological and economic ones. Using information published by the National Renewable Energy Laboratory (NREL) about the increase of solar cells record efficiency, we apply a simple mathematical model to estimate the ...

  11. Skill Assessment of An Hybrid Technique To Estimate Quantitative Precipitation Forecast For Galicia (nw Spain)

    Science.gov (United States)

    Lage, A.; Taboada, J. J.

    Precipitation is the most obvious of the weather elements in its effects on normal life. Numerical weather prediction (NWP) is generally used to produce quantitative precip- itation forecast (QPF) beyond the 1-3 h time frame. These models often fail to predict small-scale variations of rain because of spin-up problems and their coarse spatial and temporal resolution (Antolik, 2000). Moreover, there are some uncertainties about the behaviour of the NWP models in extreme situations (de Bruijn and Brandsma, 2000). Hybrid techniques, combining the benefits of NWP and statistical approaches in a flexible way, are very useful to achieve a good QPF. In this work, a new technique of QPF for Galicia (NW of Spain) is presented. This region has a percentage of rainy days per year greater than 50% with quantities that may cause floods, with human and economical damages. The technique is composed of a NWP model (ARPS) and a statistical downscaling process based on an automated classification scheme of at- mospheric circulation patterns for the Iberian Peninsula (J. Ribalaygua and R. Boren, 1995). Results show that QPF for Galicia is improved using this hybrid technique. [1] Antolik, M.S. 2000 "An Overview of the National Weather Service's centralized statistical quantitative precipitation forecasts". Journal of Hydrology, 239, pp:306- 337. [2] de Bruijn, E.I.F and T. Brandsma "Rainfall prediction for a flooding event in Ireland caused by the remnants of Hurricane Charley". Journal of Hydrology, 239, pp:148-161. [3] Ribalaygua, J. and Boren R. "Clasificación de patrones espaciales de precipitación diaria sobre la España Peninsular". Informes N 3 y 4 del Servicio de Análisis e Investigación del Clima. Instituto Nacional de Meteorología. Madrid. 53 pp.

  12. Developing and testing solar irradiance forecasting techniques in the Hawaiian Islands region

    Science.gov (United States)

    Matthews, D. K.; Souza, J. M.; Stein, K.

    2014-12-01

    Irradiance variability, primarily driven by cloud formation and advection, can be problematic in the state of Hawaíi, because of the high penetration of distributed solar and the small scale of the island electrical grids. The Hawaíi Natural Energy Institute (HNEI) is developing an operational system in order to research and test new techniques to generate solar forecasts for the Hawaiian Islands. The operational system comprises the following three components.(i) A ground-observation-based advection model, using sky imagers and a ceilometer located at the University of Hawaíi at Mānoa. Every 10 minutes (during daylight hours), this component generates a high-resolution 1 hour Global Horizontal Irradiance (GHI) prediction for a region that is within ~15 km of the instrumentation. (ii) A satellite-image-based advection model, using Geostationary Operational Environmental Satellite (GOES) imagery and the Heliosat-II method. Every 30 minutes (during daylight hours), this component generates a 1 km resolution, 6 hour GHI prediction for the entire Hawaiian Archipelago. (iii) A coupled ocean-atmosphere model, using the Regional Ocean Modeling System (ROMS) model and the Weather Research and Forecasting (WRF) model, including newly available microphysics, shallow convection parameterization, and radiative transfer model options. Nightly, this component generates 48 hour GHI, Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI) predictions for (a) a 10 km resolution domain covering the full Hawaiian Archipelago and (b) a nested 2 km resolution domain covering the islands of Maui, Óahu, and Hawaíi. We discuss the development and validation of the system, and the scales of forecasting accuracy for each component. We also examine the impact of the coupled model on the simulations of surface flux processeses and ocean-atmosphere feedbacks, both of which influence the prediction of regional cloud properties.

  13. Granulation techniques and technologies: recent progresses.

    Science.gov (United States)

    Shanmugam, Srinivasan

    2015-01-01

    Granulation, the process of particle enlargement by agglomeration technique, is one of the most significant unit operations in the production of pharmaceutical dosage forms, mostly tablets and capsules. Granulation process transforms fine powders into free-flowing, dust-free granules that are easy to compress. Nevertheless, granulation poses numerous challenges due to high quality requirement of the formed granules in terms of content uniformity and physicochemical properties such as granule size, bulk density, porosity, hardness, moisture, compressibility, etc. together with physical and chemical stability of the drug. Granulation process can be divided into two types: wet granulation that utilize a liquid in the process and dry granulation that requires no liquid. The type of process selection requires thorough knowledge of physicochemical properties of the drug, excipients, required flow and release properties, to name a few. Among currently available technologies, spray drying, roller compaction, high shear mixing, and fluid bed granulation are worth of note. Like any other scientific field, pharmaceutical granulation technology also continues to change, and arrival of novel and innovative technologies are inevitable. This review focuses on the recent progress in the granulation techniques and technologies such as pneumatic dry granulation, reverse wet granulation, steam granulation, moisture-activated dry granulation, thermal adhesion granulation, freeze granulation, and foamed binder or foam granulation. This review gives an overview of these with a short description about each development along with its significance and limitations.

  14. Analysed potential of big data and supervised machine learning techniques in effectively forecasting travel times from fused data

    Directory of Open Access Journals (Sweden)

    Ivana Šemanjski

    2015-12-01

    Full Text Available Travel time forecasting is an interesting topic for many ITS services. Increased availability of data collection sensors increases the availability of the predictor variables but also highlights the high processing issues related to this big data availability. In this paper we aimed to analyse the potential of big data and supervised machine learning techniques in effectively forecasting travel times. For this purpose we used fused data from three data sources (Global Positioning System vehicles tracks, road network infrastructure data and meteorological data and four machine learning techniques (k-nearest neighbours, support vector machines, boosting trees and random forest. To evaluate the forecasting results we compared them in-between different road classes in the context of absolute values, measured in minutes, and the mean squared percentage error. For the road classes with the high average speed and long road segments, machine learning techniques forecasted travel times with small relative error, while for the road classes with the small average speeds and segment lengths this was a more demanding task. All three data sources were proven itself to have a high impact on the travel time forecast accuracy and the best results (taking into account all road classes were achieved for the k-nearest neighbours and random forest techniques.

  15. The Technology to Train Techniques in Sports

    Directory of Open Access Journals (Sweden)

    Vladimir E. Afonshin

    2016-03-01

    Full Text Available The training session of technical techniques is proposed to conduct on the playing ground where computer-controlled light emitters create allowed and unallowed light dynamic zones. Each athlete is to be placed in one of the allowed zones and to execute with an implement some techniques directed with his breast on the light guide mark created outside the allowed zone. The athlete holding an implement is not allowed to go out of the permitted area. In the course of the training session unpredictably for an athlete the position, the shape and the area of the permitted and unallowed zones is changed. The athlete’s going into the unallowed zone or performing techniques in the position not-oriented on the guide mark is considered to be an error. If the errors are none, the allowed zone area is reduced and the intensity of the session is increased until the athlete commits an error. By the minimum square of the allowed zone, the maximum speed of its movement that the athlete performing the exercise does not commit any errors, they evaluate the athlete’s technical skill. The proposed technology facilitates in faster mastering the play technique, unlocking the individual technical features and enhancing them at any stage of the professional career. The technology can be used for the technical training of athletes of different professional profiles specializing in football, hockey, handball, basketball and other sports that require implement handling.

  16. Tide-surge adjoint modeling: A new technique to understand forecast uncertainty

    Science.gov (United States)

    Wilson, Chris; Horsburgh, Kevin J.; Williams, Jane; Flowerdew, Jonathan; Zanna, Laure

    2013-10-01

    For a simple dynamical system, such as a pendulum, it is easy to deduce where and when applied forcing might produce a particular response. However, for a complex nonlinear dynamical system such as the ocean or atmosphere, this is not as obvious. Knowing when or where the system is most sensitive, to observational uncertainty or otherwise, is key to understanding the physical processes, improving and providing reliable forecasts. We describe the application of adjoint modeling to determine the sensitivity of sea level at a UK coastal location, Sheerness, to perturbations in wind stress preceding an extreme North Sea storm surge event on 9 November 2007. Sea level at Sheerness is one of the most important factors used to decide whether to close the Thames Flood Barrier, which protects London. Adjoint modeling has been used by meteorologists since the 1990s, but is a relatively new technique for ocean modeling. It may be used to determine system sensitivity beyond the scope of ensemble modeling and in a computationally efficient way. Using estimates of wind stress error from Met Office forecasts, we find that for this event total sea level at Sheerness is most sensitive in the 3 h preceding the time of its unperturbed maximum level and over a radius of approximately 300 km. We also find that the pattern of sensitivity follows a simple sequence when considered in the reverse-time direction.

  17. Improvement of machining accuracy in precision micro-boring system by forecasting compensatory control technique

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Presents the design of a micro-boring servo system. A piezoelectric actuator is employed to compensate the deflection errors of the cutter in the radial direction to reduce the force-induced errors in the workpiece. In order to bore small and deep holes, the boring bar is designed with a new structure consisting of two concentric bars, one being used for error measuring and the other for error compensation. As a result, the size of the micro-boring bar is not af fected even after the piezoelectric actuator and strain gauges have been incorporated. The outer diameter of the boring bar used is 16 mm and the length to diameter ratio is greater than 9. A Forecasting Compensatory Control (FCC) technique is adopted in this system for error prediction and error compensation. The off-line forecasting compensatory control simulation and on-line cutting results have verified that the roundness form errors in the workpiece can be re duced up to 60 percent with the developed micro-boring servo system.

  18. Forecasting stock price using grey-fuzzy technique and portfolio optimization by invasive weed optimization algorithm

    Directory of Open Access Journals (Sweden)

    A. Hajnoori

    2013-07-01

    Full Text Available Portfolio optimization problem follows the calculation of investment income per share, based on return and risk criteria. Since stock risk is achieved by calculating its return, which is itself computed based on stock price, it is essential to forecast the stock price, efficiently. In this paper, in order to predict the stock price, grey fuzzy technique with high efficiency is employed. The proposed study of this paper calculates the return and risk of each asset and portfolio optimization model is developed based on cardinality constraint and investment income per share. To solve the resulted model, Invasive Weed Optimization (IWO algorithm is applied. In an example this algorithm is compared with other metaheuristic algorithms such as Imperialist Competitive Algorithm (ICA, Genetic Algorithm (GA and Particle Swarm Optimization (PSO. The results show that the applied algorithm performs significantly better than other algorithms.

  19. Innovative activity of high-technology companies as assessment and forecasting object

    Directory of Open Access Journals (Sweden)

    A. E. Sklyarov

    2016-01-01

    Full Text Available Innovation activities, as well as innovations, are closely related meanings, and like many others economical definitions, have a broad range of meanings. Main characteristics and attributes of innovation involves new or significantly improved product, that’s being used, or in other words, found its application, and innovative activities – activities focused on realization of innovations. In this article, innovations are mainly considered in terms of high-technology production, evidence from Russian space industry. There are 5 basic stages of lifecycle of innovative project in considered industry: initiation, development, realization, expansion, consumption. Practically, third or fourth, or even both of these stages, often missing because there is no need of them. R&D activities, or even further serial production, based on previous developments, is an innovation activity, because these activities are stages of innovative projects lifecycle itself. Then it seems legit, to draw a conclusion, that in terms of high-technology production, company’s primary activity equals innovative activity. Basic characteristics of innovative activity of high-technology companies as assessment and forecasting object involves high level of uncertainty at every stage of projects lifecycle, high dependency on funding level of this activity, and high level and erratic structure of risk. All the above mentioned, means that assessment and forecasting of innovative activity of high-technology companies, needs development of its own methodological tools for each industry.

  20. Role of hybrid forecasting techniques for transportation planning of broiler meat under uncertain demand in thailand

    Directory of Open Access Journals (Sweden)

    Thoranin Sujjaviriyasup

    2014-12-01

    Full Text Available One of numerous problems experiencing in supply chain management is the demand. Most demands are appeared in terms of uncertainty. The broiler meat industry is inevitably encountering the same problem. In this research, hybrid forecasting model of ARIMA and Support Vector Machine (SVMs are developed to forecast broiler meat export. In addition, ARIMA, SVMs, and Moving Average (MA are chosen for comparing the forecasting efficiency. All the forecasting models are tested and validated using the data of Brazil’s export, Canada’s export, and Thailand’s export. The hybrid model provides accuracy of the forecasted values that are 98.71%, 97.50%, and 93.01%, respectively. In addition, the hybrid model presents the least error of all MAE, RMSE, and MAPE comparing with other forecasting models. As forecasted data are applied to transportation planning, the mean absolute percentage error (MAPE of optimal value of forecasted value and actual value is 14.53%. The hybrid forecasting model shows an ability to reduce risk of total cost of transportation when broiler meat export is forecasted by using MA(2, MA(3, ARIMA, and SVM are 50.59%, 60.18%, 68.01%, and 46.55%, respectively. The results indicate that the developed forecasting model is recommended to broiler meat industries’ supply chain decision.

  1. A patent survey case: how could technological forecasting help cosmetic chemists with product innovation?

    Science.gov (United States)

    Domicio Da Silva Souza, Ivan; Juliana Pinheiro, Bárbara; Passarini Takahashi, Vania

    2012-01-01

    Patents represent a free and open source of data for studying innovation and forecasting technological trends. Thus, we suggest that new discussions about the role of patent information are needed. To illustrate the relevance of this issue, we performed a survey of patents involving skin care products, which were granted by the United States Patent and Trademark Office (USPTO) between 2006 and 2010, to identify opportunities for innovation and technological trends. We quantified the use of technologies in 333 patents. We plotted a life cycle of technologies related to natural ingredients. We also determined the cross impact of the technologies identified. We observed technologies related to processes applied to cosmetics (2.2%), functional packaging and applicators (2.9%), excipients and active compounds (21.5%), and cosmetic preparations (73.5%). Further, 21.6% of the patents were related to the use of natural ingredients. Several opportunities for innovation were discussed throughout this paper, for example, the use of peptides as active compounds or intracellular carriers (only 3.9% of the technologies in cosmetic preparations). We also observed technological cross impacts that suggested a trend toward multifunctional cosmetics, among others. Patent surveys may help researchers with product innovation because they allow us to identify available and unexplored technologies and turn them into whole new concepts.

  2. Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

    Science.gov (United States)

    Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

    2017-08-01

    The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

  3. Comparison of Artificial Neural Network And M5 Model Tree Technique In Water Level Forecasting of Solo River

    Science.gov (United States)

    Lasminto, Umboro; Hery Mularta, Listya

    2010-05-01

    Flood events along the Solo River flow at the end of December 2007 has caused lose of properties and lives. Floods occurred in the city of Ngawi, Madiun, Bojonegoro, Babat and surrounding areas. To reduce future losses, one of the important efforts that will occur during a flood is to get information about the magnitude and time will be floods, so that people can make an effort to reduce its impact. Flood forecasting model can provide information of water level in the river some time before the incident. This paper will compare the flood forecasting model at Bojonegoro City was built using the technique of Artificial Neural Network (ANN) and M5 Model Tree (M5MT). The model will forecast the water level of 1, 3 and 6 hours ahead at the point of water level recorders in the City of Bojonegoro using input from the water level at some point water level recorders in the upstream such as Karangnongko, Sekayu, Jurug and Wonogiri. The same data set of hourly water level records are used to build the model of ANN and M5MT technique. The selection of parameters and setup of ANN and M5MT technique is done to obtain the best result. The results of the model are evaluated by calculating the Root Mean Square Error (RMSE) between the predictions and observations. RMSE produced by the water level forecasting model 1, 3 and 6 hours ahead with M5MT technique are 0.2723, 0.6279 and 0.7176 meters. While the ANN technique are 0.1829, 0.3192 and 0517 meters. ANN technique has a better ability in predicting low flow, whereas M5 Model Tree technique has a better ability in predicting high flow. Keywords : Water level forecasting, Solo River, M5 Model Tree, Artificial Neural Network

  4. A statistical technique for defining rainfall forecast probabilities in southern Africa

    Science.gov (United States)

    Husak, G. J.; Magadzire, T.

    2010-12-01

    Probabilistic forecasts are currently produced by many climate centers and by just as many processes. These models use a number of inputs to generate the probability of rainfall falling in the lower/middle/upper tercile (frequently termed “below-normal”/”normal”/”above-normal”) of the historical rainfall distribution. Generation of forecasts for a season may be the result of a dynamic climate model, a statistical model, a consensus of a panel of experts, or a combination of some of the afore-mentioned techniques, among others. This last method is one most commonly accepted in Southern Africa, resulting from the Southern Africa Regional Climate Outlook Forum (SARCOF). While it has been noted that there is a reasonable chance of polygons having a dominant tercile of 60% probability or more, this has seldom been the case. Indeed, over the last four years, the SARCOF process has not produced any polygons with such a likelihood. In fact, the terciles in all of the SARCOFs since 2007 have been some combination of 40%, 35% and 25%. Discussions with SARCOF scientists suggests that the SARCOF process is currently using the probabilistic format to define relatively qualitative, rank-ordered outcomes in the format “most-likely”, “second-most likely” and “least likely” terciles. While this rank-ordered classification has its merits, it limits the sort of downstream quantitative statistical analysis that could potentially be of assistance to various decision makers. In this study we build a simple statistical model to analyze the probabilistic outcomes for the coming rainfall season, and analyze their resulting probabilities. The prediction model takes a similar approach to that already used in the SARCOF process: namely, using available historic rainfall data and SST information to create a linear regression between rainfall and SSTs, define a likely rainfall outcome, and analyze the cross-validation errors over the most recent 30 years. The cross

  5. Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications.

    Directory of Open Access Journals (Sweden)

    Paul Thottakkara

    Full Text Available To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury.Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010.50,318 adult patients undergoing major surgery.We evaluated the performance of logistic regression, generalized additive models, naïve Bayes and support vector machines for forecasting postoperative sepsis and acute kidney injury. We assessed the impact of feature reduction techniques on predictive performance. Model performance was determined using the area under the receiver operating characteristic curve, accuracy, and positive predicted value. The results were reported based on a 70/30 cross validation procedure where the data were randomly split into 70% used for training the model and the 30% for validation.The areas under the receiver operating characteristic curve for different models ranged between 0.797 and 0.858 for acute kidney injury and between 0.757 and 0.909 for severe sepsis. Logistic regression, generalized additive model, and support vector machines had better performance compared to Naïve Bayes model. Generalized additive models additionally accounted for non-linearity of continuous clinical variables as depicted in their risk patterns plots. Reducing the input feature space with LASSO had minimal effect on prediction performance, while feature extraction using principal component analysis improved performance of the models.Generalized additive models and support vector machines had good performance as risk prediction model for postoperative sepsis and AKI. Feature extraction using principal component analysis improved the predictive performance of all models.

  6. Peak load forecasting using multiple years data with trend data processing techniques; Tanendo data no trend shori ni motozuita saidai denryoku yosoku

    Energy Technology Data Exchange (ETDEWEB)

    Haida, T.; Muto, S.; Takahashi, Y.; Ishii, Y. [Tokyo Electric Power Co. Inc., Tokyo (Japan)

    1997-07-20

    This paper presents a regression based daily peak load forecasting method using multiple years data with trend cancellation and trend estimation techniques. Daily peak load heavily depends on temperature in daytime and is influenced by the other weather factors such as humidity. Since a characteristic of the load is varying, peak loads just before a forecasting day are more significant for the forecasting. The regression model can represent relationships between these weather factors and peak loads. However, the forecasting model is sometime not adequate for precise load forecasting. The regression model is well matched with the late data, but the model causes large forecasting errors in transitional seasons because of seasonal change of load characteristics. In order to forecast precisely through a year, a method of using seasonal or whole year data in past years is proposed. In this paper, two kinds of trend data processing techniques are described. The first is trend cancellation. The second is trend estimation. The trend cancellation technique removes annual load growth by means of division or subtraction processes with morning load on the forecasting day. The trend estimation technique estimates the trend between the forecasting year`s load and the past year`s load by using the variable transformation techniques. Performance of the both techniques verified with simulations on actual load data- is also described. 12 refs., 8 figs.

  7. Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    In this paper we consider the forecasting performance of a well-defined class of flexible models, the so-called single hidden-layer feedforward neural network models. A major aim of our study is to find out whether they, due to their flexibility, are as useful tools in economic forecasting as some...... previous studies have indicated. When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. In fact, their parameters are not even globally...... on the linearisation idea: the Marginal Bridge Estimator and Autometrics. Second, one must decide whether forecasting should be carried out recursively or directly. Comparisons of these two methodss exist for linear models and here these comparisons are extended to neural networks. Finally, a nonlinear model...

  8. Innovation Forecasting

    Science.gov (United States)

    1997-11-01

    relating to “ injectors ”) to develop a map of the related technologies [33.] Another approach is to develop a “tree” showing a system branching into its...additional terms such as “trend,” “forecast,” “ delphi ,” “assessment,” and so forth may call up other forecasts and assessments relating to the topic...present and future engine technologies. A preliminary search (Step 1, Table 5) located prior forecasts, in particular, a Delphi study [36]. The Delphi

  9. Artificial Intelligence as a Business Forecasting and Error Handling Tool

    Directory of Open Access Journals (Sweden)

    Md. Tabrez Quasim

    2015-10-01

    Full Text Available  Any business enterprise must rely a lot on how well it can predict the future happenings. To cope up with the modern global customer demand, technological challenges, market competitions etc., any organization is compelled to foresee the future having maximum impact and least chances of errors. The traditional forecasting approaches have some limitations. That is why the business world is adopting the modern Artificial Intelligence based forecasting techniques. This paper has tried to present different types of forecasting and AI techniques that are useful in business forecasting. At the later stage we have also discussed the forecasting errors and the steps involved in planning the AI support system.

  10. Machine learning techniques in disease forecasting: a case study on rice blast prediction

    Directory of Open Access Journals (Sweden)

    Kapoor Amar S

    2006-11-01

    Full Text Available Abstract Background Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases. Results Six significant weather variables were selected as predictor variables. Two series of models (cross-location and cross-year were developed and validated using a five-fold cross validation procedure. For cross-year models, the conventional multiple regression (REG approach achieved an average correlation coefficient (r of 0.50, which increased to 0.60 and percent mean absolute error (%MAE decreased from 65.42 to 52.24 when back-propagation neural network (BPNN was used. With generalized regression neural network (GRNN, the r increased to 0.70 and %MAE also improved to 46.30, which further increased to r = 0.77 and %MAE = 36.66 when support vector machine (SVM based method was used. Similarly, cross-location validation achieved r = 0.48, 0.56 and 0.66 using REG, BPNN and GRNN respectively, with their corresponding %MAE as 77.54, 66.11 and 58.26. The SVM-based method outperformed all the three approaches by further increasing r to 0.74 with improvement in %MAE to 44.12. Overall, this SVM-based prediction approach will open new vistas in the area of forecasting plant diseases of various crops. Conclusion Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also

  11. Short-Term Forecasting Models for Photovoltaic Plants: Analytical versus Soft-Computing Techniques

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2013-01-01

    Full Text Available We present and compare two short-term statistical forecasting models for hourly average electric power production forecasts of photovoltaic (PV plants: the analytical PV power forecasting model (APVF and the multiplayer perceptron PV forecasting model (MPVF. Both models use forecasts from numerical weather prediction (NWP tools at the location of the PV plant as well as the past recorded values of PV hourly electric power production. The APVF model consists of an original modeling for adjusting irradiation data of clear sky by an irradiation attenuation index, combined with a PV power production attenuation index. The MPVF model consists of an artificial neural network based model (selected among a large set of ANN optimized with genetic algorithms, GAs. The two models use forecasts from the same NWP tool as inputs. The APVF and MPVF models have been applied to a real-life case study of a grid-connected PV plant using the same data. Despite the fact that both models are quite different, they achieve very similar results, with forecast horizons covering all the daylight hours of the following day, which give a good perspective of their applicability for PV electric production sale bids to electricity markets.

  12. Forecasting macroeconomic variables using neural network models and three automated model selection techniques

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    2016-01-01

    When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. To alleviate the problem, White (2006) presented a solution (Quick......Net) that converts the specification and nonlinear estimation problem into a linear model selection and estimation problem. We shall compare its performance to that of two other procedures building on the linearization idea: the Marginal Bridge Estimator and Autometrics. Second, one must decide whether forecasting...

  13. Track etching technique in membrane technology

    Energy Technology Data Exchange (ETDEWEB)

    Apel, P. E-mail: apel@lnr.jinr.ru

    2001-06-01

    Track membrane (TM) technology is an example of industrial application of track etching technique. Track-etch membranes offer distinct advantages over conventional membranes due to their precisely determined structure. Their pore size, shape and density can be varied in a controllable manner so that a membrane with the required transport and retention characteristics can be produced. The use of heavy ion accelerators made it possible to vary LET of track-forming particles, angle distribution of pore channels and pore lengths. So far the track formation and etching process has been studied in much detail for several polymeric materials. Today we understand determining factors and have numerous empirical data enabling us to manufacture any particular product based on polyethylene terephthalate (PET) or polycarbonate (PC) films. Pore shape can be made cylindrical, conical, funnel-like, or cigar-like at will. A number of modification methods has been developed for creating TMs with special properties and functions. Applications of 'conventional' track membranes can be categorized into three groups: process filtration, cell culture, and laboratory filtration. The use in biology stands out among other areas. Nuclear track pores find diverse applications as model systems and as templates for the synthesis of micro- and nanostructures.

  14. Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

    Science.gov (United States)

    Funaro, Gregory V.; Alexander, Reginald A.

    2015-01-01

    The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision­-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of

  15. Developing and testing solar irradiance forecasting techniques in the Hawaiian Islands region

    Science.gov (United States)

    Matthews, D. K.

    2015-12-01

    The Hawaíi Natural Energy Institute (HNEI) is developing an operational solar forecasting for the Hawaiian Islands. The system comprises the following three components, covering forecasting horizons from seconds to days ahead. (i) A ground-observation driven advection model, using sky imagery and cloud height data. (ii) A satellite-image based advection model, primarily driven by Geostationary Operational Environmental Satellite (GOES) imagery. (iii) A coupled ocean-atmosphere model, using the Regional Ocean Modeling System (ROMS) model and the Weather Research and Forecasting (WRF) model, including newly available microphysics, shallow convection parameterization, and radiative transfer physics options. The satellite and NWP components provide coverage for the entire island chain, however, lack the resolution in time and space, to accurately forecast ramp events (large changes in irradiance that occur over a short period of time). Knowledge of the magnitude, duration and timing of ramp events are particularly important in Hawaíi due to the small size of the electric grids. Currently, HNEI employs a sky imager and ceilometer installed on the University of Hawaíi campus for high resolution forecasting, however, instrument design and cost limit widespread deployment. We discuss the development and preliminary validation of a new forecasting system based on inexpensive, panoramic (large FOV), off-the-shelf cameras with a cloud base height retrieval algorithm that does not require additional instrumentation.

  16. STAR 21, Technology Forecast Assessments. Strategic Technologies for the Army of the Twenty-First Century

    Science.gov (United States)

    1993-01-01

    technology, power conditioning includes prime power from homopolar generators, compulsators , and alternators combined with capacitors, batteries, and pulse...positions where they cease to make design contributions. Working relationships with suppliers are changing from strictly buyer /seller to partnerships

  17. Forecasting the Market for New Communication Technology: The Home Video Player Experience.

    Science.gov (United States)

    Klopfenstein, Bruce C.

    This paper describes a critical study of the available forecasts and forecasting studies for the home video player market over a 15-year period which was undertaken to discover why so many forecasts were wrong about consumer adoption of home videocassette players and videodisk players, the reasons for these errors, and ways in which this knowledge…

  18. Considerations in forecasting the demand for carbon sequestration and biotic storage technologies

    Energy Technology Data Exchange (ETDEWEB)

    Trexler, M.C. [Trexler and Associates, Inc., Portland, OR (United States)

    1997-12-31

    The Intergovernmental Panel on Climate Change (IPCC) has identified forestry and other land-use based mitigation measures as possible sources and sinks of greenhouse gases. An overview of sequestration and biotic storage is presented, and the potential impacts of the use of carbon sequestration as a mitigation technology are briefly noted. Carbon sequestration is also compare to other mitigation technologies. Biotic mitigation technologies are concluded to be a legitimate and potentially important part of greenhouse gas mitigation due to their relatively low costs, ancillary benefits, and climate impact. However, not all biotic mitigation techniques perfectly match the idealized definition of a mitigation measure, and policies are becoming increasingly biased against biotic technologies.

  19. Using Information Processing Techniques to Forecast, Schedule, and Deliver Sustainable Energy to Electric Vehicles

    Science.gov (United States)

    Pulusani, Praneeth R.

    As the number of electric vehicles on the road increases, current power grid infrastructure will not be able to handle the additional load. Some approaches in the area of Smart Grid research attempt to mitigate this, but those approaches alone will not be sufficient. Those approaches and traditional solution of increased power production can result in an insufficient and imbalanced power grid. It can lead to transformer blowouts, blackouts and blown fuses, etc. The proposed solution will supplement the ``Smart Grid'' to create a more sustainable power grid. To solve or mitigate the magnitude of the problem, measures can be taken that depend on weather forecast models. For instance, wind and solar forecasts can be used to create first order Markov chain models that will help predict the availability of additional power at certain times. These models will be used in conjunction with the information processing layer and bidirectional signal processing components of electric vehicle charging systems, to schedule the amount of energy transferred per time interval at various times. The research was divided into three distinct components: (1) Renewable Energy Supply Forecast Model, (2) Energy Demand Forecast from PEVs, and (3) Renewable Energy Resource Estimation. For the first component, power data from a local wind turbine, and weather forecast data from NOAA were used to develop a wind energy forecast model, using a first order Markov chain model as the foundation. In the second component, additional macro energy demand from PEVs in the Greater Rochester Area was forecasted by simulating concurrent driving routes. In the third component, historical data from renewable energy sources was analyzed to estimate the renewable resources needed to offset the energy demand from PEVs. The results from these models and components can be used in the smart grid applications for scheduling and delivering energy. Several solutions are discussed to mitigate the problem of overloading

  20. The impact of earth resources exploration from space. [technology assessment/LANDSAT satellites -technological forecasting

    Science.gov (United States)

    Nordberg, W.

    1975-01-01

    The use of Earth Resources Technology Satellites in solving global problems is examined. Topics discussed are: (1) management of food, water, and fiber resources; (2) exploration and management of energy and mineral resources; (3) protection of the environment; (4) protection of life and property; and (5) improvements in shipping and navigation.

  1. River flow forecasting. Part 2. Algebraic development of linear modelling techniques

    Science.gov (United States)

    Kachroo, R. K.; Liang, G. C.

    1992-04-01

    The role of linear input-output models in hydrological forecasting is discussed. The algebraic analysis of linear systems with single or multiple input and single output is presented in outline. The least squares method of system identification is discussed in the context of recursive and off-line estimation, with and without volumetric and shape constraints. An alternative means of imposing shape constraints, via parametric modelling, is also discussed. A procedure for 'updating' is presented for models used in real-time forecasting.

  2. Application of the LEPS technique for Quantitative Precipitation Forecasting (QPF in Southern Italy: a preliminary study

    Directory of Open Access Journals (Sweden)

    S. Federico

    2006-01-01

    Full Text Available This paper reports preliminary results for a Limited area model Ensemble Prediction System (LEPS, based on RAMS (Regional Atmospheric Modelling System, for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time in an operational implementation of LEPS, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that form the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12-km horizontal resolution. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecasts, LEPS forecasts are compared to a full Brute Force (BF ensemble. This ensemble is based on RAMS, has 36 km horizontal resolution and is generated by 51 members, nested in each ECMWF-EPS member. LEPS and BF results are compared subjectively and by objective scores. Subjective analysis is based on precipitation and probability maps of case studies whereas objective analysis is made by deterministic and probabilistic scores. Scores and maps are calculated by comparing ensemble precipitation forecasts against reports from the Calabria regional raingauge network. Results show that LEPS provided better rainfall predictions than BF for all case studies selected. This strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria for these cases. To further explore the impact of local physiographic features on QPF (Quantitative Precipitation Forecasting, LEPS results are also compared with a 6-km horizontal resolution deterministic forecast. Due

  3. Hybrid models for hydrological forecasting: integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following top

  4. Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following top

  5. Hybrid models for hydrological forecasting: integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following

  6. Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following

  7. Technology assessment of applied techniques for exploitation of geothermal energy

    Energy Technology Data Exchange (ETDEWEB)

    1977-04-01

    Studies were made to elucidate the effects of technological development of natural steam and hot water on the general social and industrial environments. These were followed by studies of enhanced methods for the forecasting of these impacts. The studies included assessments of actual conditions and the preparation of regional models, ranging from rural to urban-fringe situations. The economic implications of geothermal development in various regional situations are discussed, and the models developed provide for the integration of new data and their extrapolation to as yet uncertain situations.

  8. Techniques to Pass on: Technology and Euthanasia

    Science.gov (United States)

    Martin, Brian

    2010-01-01

    Proponents and opponents of euthanasia have argued passionately about whether it should be legalized. In Australia in the mid-1990s, following the world's first legal euthanasia deaths, Dr. Philip Nitschke initiated a different approach: a search for do-it-yourself technological means of dying with dignity. The Australian government has opposed…

  9. Techniques to Pass on: Technology and Euthanasia

    Science.gov (United States)

    Martin, Brian

    2010-01-01

    Proponents and opponents of euthanasia have argued passionately about whether it should be legalized. In Australia in the mid-1990s, following the world's first legal euthanasia deaths, Dr. Philip Nitschke initiated a different approach: a search for do-it-yourself technological means of dying with dignity. The Australian government has opposed…

  10. Sensitivity analysis of a data assimilation technique for hindcasting and forecasting hydrodynamics of a complex coastal water body

    Science.gov (United States)

    Ren, Lei; Hartnett, Michael

    2017-02-01

    Accurate forecasting of coastal surface currents is of great economic importance due to marine activities such as marine renewable energy and fish farms in coastal regions in recent twenty years. Advanced oceanographic observation systems such as satellites and radars can provide many parameters of interest, such as surface currents and waves, with fine spatial resolution in near real time. To enhance modelling capability, data assimilation (DA) techniques which combine the available measurements with the hydrodynamic models have been used since the 1990s in oceanography. Assimilating measurements into hydrodynamic models makes the original model background states follow the observation trajectory, then uses it to provide more accurate forecasting information. Galway Bay is an open, wind dominated water body on which two coastal radars are deployed. An efficient and easy to implement sequential DA algorithm named Optimal Interpolation (OI) was used to blend radar surface current data into a three-dimensional Environmental Fluid Dynamics Code (EFDC) model. Two empirical parameters, horizontal correlation length and DA cycle length (CL), are inherent within OI. No guidance has previously been published regarding selection of appropriate values of these parameters or how sensitive OI DA is to variations in their values. Detailed sensitivity analysis has been performed on both of these parameters and results presented. Appropriate value of DA CL was examined and determined on producing the minimum Root-Mean-Square-Error (RMSE) between radar data and model background states. Analysis was performed to evaluate assimilation index (AI) of using an OI DA algorithm in the model. AI of the half-day forecasting mean vectors' directions was over 50% in the best assimilation model. The ability of using OI to improve model forecasts was also assessed and is reported upon.

  11. Evaluation of NCAR Icing/SLD Forecasts, Tools and Techniques Used During The 1998 NASA SLD Flight Season

    Science.gov (United States)

    Bernstein, Ben C.

    2001-01-01

    Supercooled Large Droplet (SLD) icing conditions were implicated in at least one recent aircraft crash, and have been associated with other aircraft incidents. Inflight encounters with SLD can result in ice accreting on unprotected areas of the wing where it can not be removed. Because this ice can adversely affect flight characteristics of some aircraft, there has been concern about flight safety in these conditions. The FAA held a conference on in-flight icing in 1996 where the state of knowledge concerning SLD was explored. One outcome of these meetings was an identified need to acquire SLD flight research data, particularly in the Great Lakes Region. The flight research data was needed by the FAA to develop a better understanding of the meteorological characteristics associated with SLD and facilitate an assessment of existing aircraft icing certification regulations with respect to SLD. In response to this need, NASA, the Federal Aviation Administration (FAA), and the National Center for Atmospheric Research (NCAR) conducted a cooperative icing flight research program to acquire SLD flight research data. The NASA Glenn Research Center's Twin Otter icing research aircraft was flown throughout the Great Lakes region during the winters of 1996-97 and 1997-98 to acquire SLD icing and meteorological data. The NASA Twin Otter was instrumented to measure cloud microphysical properties (particle size, LWC (Liquid Water Content), temperature, etc.), capture images of wing and tail ice accretion, and then record the resultant effect on aircraft performance due to the ice accretion. A satellite telephone link enabled the researchers onboard the Twin Otter to communicate with NCAR meteorologists. who provided real-time guidance into SLD icing conditions. NCAR meteorologists also provided preflight SLD weather forecasts that were used to plan the research flights, and served as on-board researchers. This document contains an evaluation of the tools and techniques NCAR

  12. Exchange Rate Forecasting Techniques, Survey Data, and Implications for the Foreign Exchange Market

    OpenAIRE

    Frankel, Jeffrey A.; Kenneth Froot

    1990-01-01

    The paper presents new empirical results that elucidate the dynamics of the foreign exchange market. The first half of the paper is an updated study of the exchange rate expectations held by market participants, as reflected in responses to surveys, and contains the following conclusions. First, the bias observed in the forward discount as a predictor of the future spot rate is not attributable to an exchange risk premium, as is conventionally believed. Second, at short horizons forecasters t...

  13. Using a cross correlation technique to refine the accuracy of the Failure Forecast Method: Application to Soufrière Hills volcano, Montserrat

    Science.gov (United States)

    Salvage, R. O.; Neuberg, J. W.

    2016-09-01

    Prior to many volcanic eruptions, an acceleration in seismicity has been observed, suggesting the potential for this as a forecasting tool. The Failure Forecast Method (FFM) relates an accelerating precursor to the timing of failure by an empirical power law, with failure being defined in this context as the onset of an eruption. Previous applications of the FFM have used a wide variety of accelerating time series, often generating questionable forecasts with large misfits between data and the forecast, as well as the generation of a number of different forecasts from the same data series. Here, we show an alternative approach applying the FFM in combination with a cross correlation technique which identifies seismicity from a single active source mechanism and location at depth. Isolating a single system at depth avoids additional uncertainties introduced by averaging data over a number of different accelerating phenomena, and consequently reduces the misfit between the data and the forecast. Similar seismic waveforms were identified in the precursory accelerating seismicity to dome collapses at Soufrière Hills volcano, Montserrat in June 1997, July 2003 and February 2010. These events were specifically chosen since they represent a spectrum of collapse scenarios at this volcano. The cross correlation technique generates a five-fold increase in the number of seismic events which could be identified from continuous seismic data rather than using triggered data, thus providing a more holistic understanding of the ongoing seismicity at the time. The use of similar seismicity as a forecasting tool for collapses in 1997 and 2003 greatly improved the forecasted timing of the dome collapse, as well as improving the confidence in the forecast, thereby outperforming the classical application of the FFM. We suggest that focusing on a single active seismic system at depth allows a more accurate forecast of some of the major dome collapses from the ongoing eruption at Soufri

  14. Current and Potential Use of Technology Forecasting Tools in the Federal Government

    Science.gov (United States)

    2016-03-01

    seeks to “develop and test methods for generating accurate forecasts for significant [S&T] milestones, by combining the judgements of many experts.”2 To...a primarily respondent-driven sampling method was used to identify and facilitate contact with appropriate individuals. An initial list of...Forecasting ............................................15 1. Agencies that Use Automated Methods ......................................................15 2

  15. A neutral network based technique for short-term forecasting of anomalous load periods

    Energy Technology Data Exchange (ETDEWEB)

    Sforna, M. [ENEL, s.p.a, Italian Power Company (Italy); Lamedica, R.; Prudenzi, A. [Rome Univ. `La Sapienza`, Rome (Italy); Caciotta, M.; Orsolini Cencelli, V. [Rome Univ. III, Rome (Italy)

    1995-01-01

    The paper illustrates a part of the research activity conducted by authors in the field of electric Short Term Load Forecasting (STLF) based on Artificial Neural Network (ANN) architectures. Previous experiences with basic ANN architectures have shown that, even though these architecture provide results comparable with those obtained by human operators for most normal days, they evidence some accuracy deficiencies when applied to `anomalous` load conditions occurring during holidays and long weekends. For these periods a specific procedure based upon a combined (unsupervised/supervised) approach has been proposed. The unsupervised stage provides a preventive classification of the historical load data by means of a Kohonen`s Self Organizing Map (SOM). The supervised stage, performing the proper forecasting activity, is obtained by using a multi-layer percept ron with a back propagation learning algorithm similar to the ones above mentioned. The unconventional use of information deriving from the classification stage permits the proposed procedure to obtain a relevant enhancement of the forecast accuracy for anomalous load situations.

  16. Techniques and technologies to maximize mucosal exposure

    NARCIS (Netherlands)

    Moons, L.M.; Gralnek, I.M.; Siersema, P.D.

    2015-01-01

    Performing high-quality colonoscopy is one of the important goals of gastroenterology practices and requires achieving a high level of bowel cleansing, performing good and safe polypectomy, and detecting all polyps present in the colon. This article summarizes currently available techniques and tech

  17. Granulation techniques and technologies: recent progresses

    OpenAIRE

    Srinivasan Shanmugam

    2015-01-01

    Granulation, the process of particle enlargement by agglomeration technique, is one of the most significant unit operations in the production of pharmaceutical dosage forms, mostly tablets and capsules. Granulation process transforms fine powders into free-flowing, dust-free granules that are easy to compress. Nevertheless, granulation poses numerous challenges due to high quality requirement of the formed granules in terms of content uniformity and physicochemical proper...

  18. Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques.

    Science.gov (United States)

    Chen, Shyi-Ming; Manalu, Gandhi Maruli Tua; Pan, Jeng-Shyang; Liu, Hsiang-Chuan

    2013-06-01

    In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization (PSO) techniques. First, we fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors second-order fuzzy logical relationships. Then, we group the two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, we obtain the optimal weighting vector for each fuzzy-trend logical relationship group by using PSO techniques to perform the forecasting. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index and the NTD/USD exchange rates. The experimental results show that the proposed method gets better forecasting performance than the existing methods.

  19. Real-time flood forecasting coupling different postprocessing techniques of precipitation forecast ensembles with a distributed hydrological model. The case study of may 2008 flood in western Piemonte, Italy

    Directory of Open Access Journals (Sweden)

    D. Cane

    2013-02-01

    Full Text Available In this work, we compare the performance of an hydrological model when driven by probabilistic rain forecast derived from two different post-processing techniques. The region of interest is Piemonte, northwestern Italy, a complex orography area close to the Mediterranean Sea where the forecast are often a challenge for weather models. The May 2008 flood is here used as a case study, and the very dense weather station network allows us for a very good description of the event and initialization of the hydrological model. The ensemble probabilistic forecasts of the rainfall fields are obtained with the Bayesian model averaging, with the classical poor man ensemble approach and with a new technique, the Multimodel SuperEnsemble Dressing. In this case study, the meteo-hydrological chain initialized with the Multimodel SuperEnsemble Dressing is able to provide more valuable discharge ranges with respect to the one initialized with Bayesian model averaging multi-model.

  20. The application of LEPS technique for Quantitative Precipitation Forecast (QPF in Southern Italy

    Directory of Open Access Journals (Sweden)

    S. Federico

    2006-01-01

    Full Text Available This paper reports preliminary results of a Limited area model Ensemble Prediction System (LEPS, based on RAMS, for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time, in order to implement LEPS operational, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that forms the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12 km horizontal resolution. Hereafter this ensemble will be referred also as LEPS_12L30. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecast, LEPS_12L30 forecasts are compared to a lower resolution ensemble, based on RAMS that has 50 km horizontal resolution and 51 members, nested in each ECMWF-EPS member. Hereafter this ensemble will be also referred as LEPS_50L30. LEPS_12L30 and LEPS_50L30 results were compared subjectively for all case studies but, for brevity, results are reported for two "representative" cases only. Subjective analysis is based on ensemble-mean precipitation and probability maps. Moreover, a short summary of objective scores. Maps and scores are evaluated against reports of Calabria regional raingauges network. Results show better LEPS_12L30 performance compared to LEPS_50L30. This is obtained for all case studies selected and strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria, at least for set-ups and case studies selected in this work.

  1. Shortrange Forecasting through Extrapolation of Satellite Imagery Patterns. Part II. Testing Motion Vector Techniques.

    Science.gov (United States)

    1979-12-10

    and/ur ,, LL Unclassified SICURITY CLASSIFICATION OP THIS PA6r(gIm 000. ,i,;P .-41 -_ _ _ __, _ __ _ Contents 1. INTRODUCTION 5 2. PLANS FOR SECOND...SRI fFt Cross- Binary Cross- 1971 1977 Covariance Covariance +8.3 ±6.0 ±4.9 ±0.3 ± 3.9 ± 3.7 ± 3.8 ±1.5 Vector ± 59% ± 49% * 42% 100 Error 2. PLANS ...correct forecast of their non-o( turrunce tarea A in Figure 4). In Figure 6. the overall level of percent ,orrect drops almost monotonically as the

  2. Innovation in surgical technology and techniques: Challenges and ethical issues.

    Science.gov (United States)

    Geiger, James D; Hirschl, Ronald B

    2015-06-01

    The pace of medical innovation continues to increase. The deployment of new technologies in surgery creates many ethical challenges including how to determine safety of the technology, what is the timing and process for deployment of a new technology, how are patients informed before undergoing a new technology or technique, how are the outcomes of a new technology evaluated and how are the responsibilities of individual patients and society at large balanced. Ethical considerations relevant to the implementation of ECMO and robotic surgery are explored to further discussion of how we can optimize the delicate balance between innovation and regulation.

  3. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  4. 光伏功率预测技术%An Overview of Photovoltaic Energy System Output Forecasting Technology

    Institute of Scientific and Technical Information of China (English)

    龚莺飞; 鲁宗相; 乔颖; 王强

    2016-01-01

    Forecast of photovoltaic energy system output is a crucial technology to improve the performance of photovoltaic energy stations,and plays a fundamental role in the secure and stable operation of power grid with high penetration of photovoltaic generation.Since photovoltaic energy system forecasting is still at very early stage,it is critical to understand its technical roadmap and key problems.This paper gives a comprehensive review of the basic technical principles and key problems in the photovoltaic energy forecasting.Firstly,the basic principle and methods of photovoltaic energy forecasting are introduced.Then the key technical points of ultra-short term and short term forecasting are summarized,specially focusing on the forecasting accuracy.Finally,the key issues of photovoltaic energy forecasting are summarized from the prospective of Chinese market.%光伏功率预测是提高光伏电站控制、调度性能,保障高比率光伏发电接入的电网安全稳定运行的基础性关键技术。国内光伏功率预测技术研究和工程应用尚处于起步阶段,理清其技术脉络和关键问题尤其迫切。文中对光伏功率预测基本技术原理和关键问题进行了全面综述,首先介绍其基本原理和预测模式,然后总结了超短期和短期预测的主要技术要点,并着重对提升预测精度的相关研究进行评述,最后结合中国光伏功率预测发展现状,提出了值得研究和关注的光伏功率预测关键问题。

  5. 基于专利分析的技术预测概念模型%Conceptual Model of Technology Forecast Based on Patent Analysis

    Institute of Scientific and Technical Information of China (English)

    张韵君; 柳飞红

    2014-01-01

    国内外研究者对技术预测给予了不同的阐释。专利分析作为技术预测的一种有效工具,可以为技术创新提供有力的决策支持。针对特定技术领域的预测,是基于“专利三性”隐含的技术发展方向、技术发展水平和技术发展潜力的特征所作出的判断。因此,可以建立一个基于专利分析的技术预测概念模型。概念模型在纵向层次上分为总预测层、预测综合层、预测分析层和预测信息层。在此基础上,选择和运用相应的专利分析指标和方法,形成一个技术预测的专利分析方法框架,以指导实际的技术预测活动。技术预测的效用可以用技术的发展方向、发展水平和发展潜力这三个变量予以描述。但专利分析也存在局限性,需要与其它方法配合使用。%There are different definitions for technology forecast domestically and abroad. Being an effective tool for technology forecast, patent analysis is very helpful to technological innovation decision-making. Because the forecast in specific technology fields is based on features of technology development direction, level and potential implicated in the “three natures of patent”, so a conceptual model of technology forecast can be built on the basis of patent analysis. The proposed model consists four layers of overall forecast, forecast con-solidated, predictive analysis and forecast information from a longitudinal level. Based on this, corresponding indicators and methods of patent analysis can be chosen and used to build a patent analysis frame for technology forecast to guide the actual activities of technology forecast. The effectiveness of technology forecast can be described with the three variables of development direction, level and potential of technology. And it is suggested that other methods be used together with patent analysis because of its limitations.

  6. North Florida Dairy Farmer Perceptions Toward the Use of Seasonal Climate Forecast Technology

    Energy Technology Data Exchange (ETDEWEB)

    Cabrera, V.E.; Breuer, N.E. [Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Gainesville, 256 Frazier Rogers Hall, PO Box 110570, FL 32611, Florida (United States); Hildebrand, P.E. [Food and Resource Economic Department, University of Florida, Gainesville, Gainesville, 1172 McCarty Hall, PO Box 110240, 32611-0240, Florida (United States)

    2006-10-15

    Evidence of increasing nitrogen levels in the Suwannee River Basin in North Florida demands a collaborative effort to find creative ways to reduce N pollution. This study explores the perspectives, perceptions, and attitudes of dairy farmers regarding adoption of climate forecasts as a potential way to mitigate the problem. These farmers are heavily scrutinized because of their nitrogen emissions. By contrasting scientists' pre-conceived attitudes about the usefulness of ENSO-based (El Nino/Southern Oscillation) forecasts with dairy farmers' perceptions, gathered in a participatory and consensual manner, valuable lessons were learned. A deeper understanding of the day to day realities of dairy farming systems help researchers pinpoint management adaptations that are not only useful, but feasible, in light of improved seasonal climate forecasts. Furthermore, dairy farmers' perceptions regarding the use of seasonal climate information to mitigate the nitrate problem are critical for designing future dairy systems.

  7. Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

    Science.gov (United States)

    Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

    2014-05-01

    Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

  8. One-step ahead prediction of foF2 using time series forecasting techniques

    Directory of Open Access Journals (Sweden)

    A. Belehaki

    2005-11-01

    Full Text Available In this paper the problem of one-step ahead prediction of the critical frequency (foF2 of the middle-latitude ionosphere, using time series forecasting methods, is considered. The whole study is based on a sample of about 58000 observations of foF2 with 15-min time resolution, derived from the Athens digisonde ionograms taken from the Digisonde Portable Sounder (DPS4 located at Palaia Penteli (38° N, 23.5° E, for the period from October 2002 to May 2004. First, the embedding dimension of the dynamical system that generates the above sample is estimated using the false nearest neighbor method. This information is then utilized for the training of the predictors employed in this study, which are the linear predictor, the neural network predictor, the persistence predictor and the k-nearest neighbor predictor. The results obtained by the above predictors suggest that, as far as the mean square error is considered as performance criterion, the first two predictors are significantly better than the latter two predictors. In addition, the results obtained by the linear and the neural network predictors are not significantly different from each other. This may be taken as an indication that a linear model suffices for one step ahead prediction of foF2.

  9. Forecasting- where computational intelligence meets the stock market

    Institute of Scientific and Technical Information of China (English)

    Edward TSANG

    2009-01-01

    Forecasting is an important activity in finance.Traditionally, forecasting has been done with in-depth knowledge in finance and the market. Advances in computational intelligence have created opportunities that were never there before. Computational finance techniques, machine learning in particular, can dramatically enhance our ability to forecast. They can help us to forecast ahead of our competitors and pick out scarce opportunities. This paper explains some of the opportunities offered by computational intelligence and some of the achievements so far. It also explains the underlying technologies and explores the research horizon.

  10. Structural equation modelling based data fusion for technology forecasting: A generic framework

    CSIR Research Space (South Africa)

    Staphorst, L

    2013-07-01

    Full Text Available makers. Technology indicators are those sources of technology related data that allow for the direct characterisation and evaluation of technologies over their whole life cycle. Future-oriented Technology Analysis (FTA), which is a forward...

  11. Report on the Evaluation of Demand Forecasting Techniques for the Subsistence Commodity. Volume 1,

    Science.gov (United States)

    1985-10-01

    Advanced Technology , Inc. Mr. Greg Logan, Defense Technical Information Center Mr. Don Stewart, Defense Technical Information Center Mr. Larry Jenkins...and Eggs 8915 Fruits and Vegetables 8920 Bakery and Cereal Products 8925 Sugar, Confectionary and Nuts I 8930 Jams, Jellies and Preserves 8935 Soups

  12. Cognitive Heterogeneous Reconfigurable Optical Networks (CHRON): Enabling Technologies and Techniques

    DEFF Research Database (Denmark)

    Tafur Monroy, Idelfonso; Zibar, Darko; Guerrero Gonzalez, Neil;

    2011-01-01

    We present the approach of cognition applied to heterogeneous optical networks developed in the framework of the EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network. We introduce and discuss in particular the technologies and techniques that will enable a cognitive optical ne...

  13. Application of Data Collection Techniques by Human Performance Technology Practitioners

    Science.gov (United States)

    Duan, Minjing

    2011-01-01

    By content-analyzing 22 published cases from a variety of professional and academic books and journals, this study examines the status quo of human performance technology (HPT) practitioners' application of five major data collection techniques in their everyday work: questionnaire, interview, focus group, observation, and document collection. The…

  14. Multi-Model Combination techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

    Energy Technology Data Exchange (ETDEWEB)

    Ajami, N K; Duan, Q; Gao, X; Sorooshian, S

    2005-04-11

    This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.

  15. Multi-Model Combination Techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

    Energy Technology Data Exchange (ETDEWEB)

    Ajami, N; Duan, Q; Gao, X; Sorooshian, S

    2006-05-08

    This paper examines several multi-model combination techniques: the Simple Multimodel Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.

  16. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  17. Forecasting the direction of stock market index movement using three data mining techniques: the case of Tehran Stock Exchange

    Directory of Open Access Journals (Sweden)

    Sadegh Bafandeh Imandoust

    2014-06-01

    Full Text Available Prediction of stock price return is a highly complicated and very difficult task because there are many factors such that may influence stock prices. An accurate prediction of movement direction of stock index is crucial for investors to make effective market trading strategies. However, because of the high nonlinearity of the stock market, it is difficult to reveal the inside law by the traditional forecast methods. In response to such difficulty, data mining techniques have been introduced and applied for this financial prediction. This study attempted to develop three models and compared their performances in predicting the direction of movement in daily Tehran Stock Exchange (TSE index. The models are based on three classification techniques, Decision Tree, Random Forest and Naïve Bayesian Classifier. Ten microeconomic variables and three macroeconomic variables were chosen as inputs of the proposed models. Experimental results show that performance of Decision Tree model (80.08% was found better than Random Forest (78.81% and Naïve Bayesian Classifier (73.84%.

  18. Supply shortage forecast in Ontario: The significance of demand-side management (DSM); its tools and techniques

    Energy Technology Data Exchange (ETDEWEB)

    Saini, S.

    2004-06-01

    Aspects of the recent report by the Ontario Electricity Conservation and Supply Task Force and Independent Market Operator which forecasts acute power supply shortages in Ontario, are discussed. Immediate action is recommended to avert the problem. The principal recommendation concerns the adoption of Demand Side Management as a tool to reduce the widening gap between supply and demand, citing supply shortage, imports, high prices, deregulated market and environmental concerns as the driving forces which push for the adoption of DSM. It is claimed that DSM, through its tools such as Demand/Load Response Programs and Time-of-Use rates has the capacity to create the necessary balance between supply and demand more efficiently, and in a more timely fashion than supply side management. The demand for adoption of DSM is justified on the basis of a careful examination of the magnitude and significance of each of the driving forces affecting the electricity supply in Ontario, as well as the benefits and techniques of DSM designed to manage power shortages. Energy Conservation and Efficiency and Demand/Load Response Programs are discussed as the principal DSM techniques, while Dynamic/Real Time Pricing, Time-of-Use Rates, Automated /Smart Metering, Web-based/Communication Systems, Reliability-based Programs, Market/Price-based programs, and Types of Load Control are described as the principal tools used by DSM. DSM program approaches and strategies are also reviewed, along with a brief list of successful examples of DSM applications. 3 figs.

  19. Arts and technology - Mosaic new techniques and procedures

    Science.gov (United States)

    Papiu, G. A.; Suciu, N.

    2017-05-01

    The relationship between art and technique has been along the time one that is inseparable and systematic, artists appealing to various technologies, tools and practices that help them stimulate their imagination. Today there is a new category of artists, coming from a technical or scientific field, that are being 'trapped’ in this ‘game of art”. The mosaic, even if it is an old technique, responded to the social requirements and it evolved over time, being constantly related to aesthetic and artistic thinking, discoveries of science, assimilating permanent new techniques and technologies, diversifying its artistic forms of expression and methods of transposition. Not being bound any more to a religious institution, which was its birth place, today, she migrated to all public spaces. Works of art in public space have become today an active factor in reshaping the urban aesthetic landscape.

  20. On the Influence of Weather Forecast Errors in Short-Term Load Forecasting Models

    OpenAIRE

    Fay, D; Ringwood, John; Condon, M.

    2004-01-01

    Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...

  1. Adaptive Opportunistic Cooperative Control Mechanism Based on Combination Forecasting and Multilevel Sensing Technology of Sensors for Mobile Internet of Things

    Directory of Open Access Journals (Sweden)

    Yong Jin

    2014-01-01

    Full Text Available In mobile Internet of Things, there are many challenges, including sensing technology of sensors, how and when to join cooperative transmission, and how to select the cooperative sensors. To address these problems, we studied the combination forecasting based on the multilevel sensing technology of sensors, building upon which we proposed the adaptive opportunistic cooperative control mechanism based on the threshold values such as activity probability, distance, transmitting power, and number of relay sensors, in consideration of signal to noise ratio and outage probability. More importantly, the relay sensors would do self-test real time in order to judge whether to join the cooperative transmission, for maintaining the optimal cooperative transmission state with high performance. The mathematical analyses results show that the proposed adaptive opportunistic cooperative control approach could perform better in terms of throughput ratio, packet error rate and delay, and energy efficiency, compared with the direct transmission and opportunistic cooperative approaches.

  2. Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

    Science.gov (United States)

    Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

    2014-12-01

    Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of

  3. Applying machine learning techniques for forecasting flexibility of virtual power plants

    DEFF Research Database (Denmark)

    MacDougall, Pamela; Kosek, Anna Magdalena; Bindner, Henrik W.

    2016-01-01

    hidden layer artificial neural network (ANN). Both techniques are used to model a relationship between the aggregator portfolio state and requested ramp power to the longevity of the delivered flexibility. Using validated individual household models, a smart controlled aggregated virtual power plant...... is simulated. A hierarchical market-based supply-demand matching control mechanism is used to steer the heating devices in the virtual power plant. For both the training and validation set of clusters, a random number of households, between 200 and 2000, is generated with day ahead profile scaled accordingly...

  4. Updating prediction models by dynamical relaxation - An examination of the technique. [for numerical weather forecasting

    Science.gov (United States)

    Davies, H. C.; Turner, R. E.

    1977-01-01

    A dynamical relaxation technique for updating prediction models is analyzed with the help of the linear and nonlinear barotropic primitive equations. It is assumed that a complete four-dimensional time history of some prescribed subset of the meteorological variables is known. The rate of adaptation of the flow variables toward the true state is determined for a linearized f-model, and for mid-latitude and equatorial beta-plane models. The results of the analysis are corroborated by numerical experiments with the nonlinear shallow-water equations.

  5. Applications of soft computing in time series forecasting simulation and modeling techniques

    CERN Document Server

    Singh, Pritpal

    2016-01-01

    This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and governmen...

  6. Practical Applications of Evolutionary Computation to Financial Engineering Robust Techniques for Forecasting, Trading and Hedging

    CERN Document Server

    Iba, Hitoshi

    2012-01-01

    “Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutio...

  7. NEEMO 21: Tools, Techniques, Technologies & Training for Science Exploration EVA

    Science.gov (United States)

    Graff, Trevor

    2016-01-01

    The 21st mission of the NASA Extreme Environment Mission Operations (NEEMO) was a highly integrated operational test and evaluation of tools, techniques, technologies, and training for science driven exploration during Extravehicular Activity (EVA).The 16-day mission was conducted from the Aquarius habitat, an underwater laboratory, off the coast of Key Largo, FL. The unique facility, authentic science objectives, and diverse skill-sets of the crew/team facilitate the planning and design for future space exploration.

  8. Spray drying technique: II. Current applications in pharmaceutical technology.

    Science.gov (United States)

    Sollohub, Krzysztof; Cal, Krzysztof

    2010-02-01

    This review presents current applications of spray drying in pharmaceutical technology. The topics discussed include the obtention of excipients and cospray dried composites, methods for increasing the aqueous solubility and bioavailability of active substances, and modified release profiles from spray-dried particles. This review also describes the use of the spray drying technique in the context of biological therapies, such as the spray drying of proteins, inhalable powders, and viable organisms, and the modification of the physical properties of dry plant extracts.

  9. Advanced computer modeling techniques expand belt conveyor technology

    Energy Technology Data Exchange (ETDEWEB)

    Alspaugh, M.

    1998-07-01

    Increased mining production is continuing to challenge engineers and manufacturers to keep up. The pressure to produce larger and more versatile equipment is increasing. This paper will show some recent major projects in the belt conveyor industry that have pushed the limits of design and engineering technology. Also, it will discuss the systems engineering discipline and advanced computer modeling tools that have helped make these achievements possible. Several examples of technologically advanced designs will be reviewed. However, new technology can sometimes produce increased problems with equipment availability and reliability if not carefully developed. Computer modeling techniques that help one design larger equipment can also compound operational headaches if engineering processes and algorithms are not carefully analyzed every step of the way.

  10. The intersections between TRIZ and forecasting methodology

    Directory of Open Access Journals (Sweden)

    Georgeta BARBULESCU

    2010-12-01

    Full Text Available The authors’ intention is to correlate the basic knowledge in using the TRIZ methodology (Theory of Inventive Problem Solving or in Russian: Teoriya Resheniya Izobretatelskikh Zadatch as a problem solving tools meant to help the decision makers to perform more significant forecasting exercises. The idea is to identify the TRIZ features and instruments (40 inventive principles, i.e. for putting in evidence the noise and signal problem, for trend identification (qualitative and quantitative tendencies and support tools in technological forecasting, to make the decision-makers able to refine and to increase the level of confidence in the forecasting results. The interest in connecting TRIZ to forecasting methodology, nowadays, relates to the massive application of TRIZ methods and techniques for engineering system development world-wide and in growing application of TRIZ’s concepts and paradigms for improvements of non-engineering systems (including the business and economic applications.

  11. A Curriculum for Teaching Information Technology Investigative Techniques for Auditors

    Directory of Open Access Journals (Sweden)

    Grover S. Kearns

    2006-12-01

    Full Text Available Recent prosecutions of highly publicized white-collar crimes combined with public outrage have resulted in heightened regulation of financial reporting and greater emphasis on systems of internal control. Because both white-collar and cybercrimes are usually perpetrated through computers, internal and external auditors’ knowledge of information technology (IT is now more vital than ever. However, preserving digital evidence and investigative techniques, which can be essential to fraud examinations, are not skills frequently taught in accounting programs and instruction in the use of computer assisted auditing tools and techniques – applications that might uncover fraudulent activity – is limited. Only a few university-level accounting classes provide instruction in IT investigative techniques. This paper explains why such a course would be beneficial to the program, the college, and the student. Additionally, it presents a proposed curriculum and suggests useful resources for the instructor and student.

  12. Artificial neural networks in forecasting tourists’ flow, an intelligent technique to help the economic development of tourism in Albania.

    Directory of Open Access Journals (Sweden)

    Dezdemona Gjylapi

    2014-07-01

    The aim of this paper is to present the neural network usage in the tourists’ number forecasting and to determine the trends of the future tourist inflow, thus helping tourism management agencies in making scientific based financial decisions.

  13. A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

    Science.gov (United States)

    Zack, J. W.

    2015-12-01

    Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

  14. Solar system exploration - Some thoughts on techniques and technologies

    Science.gov (United States)

    Bekey, Ivan

    1990-01-01

    Some techniques and technologies for proposed interplanetary missions are described. Methods for reducing the effect of zero gravity on humans during missions to Mars and the moon, and the need for launch vehicles with increased lift capability are discussed. The use of nuclear power, liquid oxygen from the moon, and helium 3 as propellants for spacecraft is examined. The development and capabilities of the Shuttle Z vehicle are considered. Attention is given to the Space Station Freedom and Energia. A launch vehicle concept which utilizes the Shuttle Z for a mission to Mars is presented.

  15. Landmine Detection Technologies to TraceExplosive Vapour Detection Techniques

    Directory of Open Access Journals (Sweden)

    J. C. Kapoor

    2007-11-01

    Full Text Available Large quantity of explosive is manufactured worldwide for use in various types of ammunition,arms, and mines, and used in armed conflicts. During manufacturing and usage of the explosiveequipment, some of the explosive residues are released into the environment in the form ofcontaminated effluents, unburnt explosives fumes and vapours. Limited but uncontrolledcontinuous release of trace vapours also takes place when explosive-laden landmines are deployedin the field. One of the major technological challenges in post-war scenario worldwide is thedetection of landmines using these trace vapour signatures and neutralising them safely.  Differenttypes of explosives are utilised as the main charge in antipersonnel and antitank landmines. Inthis paper, an effort has been made to review the techniques so far available based on explosivevapour detection especially to detect the landmines. A comprehensive compilation of relevantinformation on the techniques is presented, and their maturity levels, shortcomings, and difficultiesfaced are highlighted.

  16. Technology development of fabrication techniques for advanced solar dynamic concentrators

    Science.gov (United States)

    Richter, Scott W.

    1991-01-01

    The objective of the advanced concentrator program is to develop the technology that will lead to lightweight, highly reflective, accurate, scaleable, and long lived space solar dynamic concentrators. The advanced concentrator program encompasses new and innovative concepts, fabrication techniques, materials selection, and simulated space environmental testing. Fabrication techniques include methods of fabricating the substrates and coating substrate surfaces to produce high quality optical surfaces, acceptable for further coating with vapor deposited optical films. The selected materials to obtain a high quality optical surface include microsheet glass and Eccocoat EP-3 epoxy, with DC-93-500 selected as a candidate silicone adhesive and levelizing layer. The following procedures are defined: cutting, cleaning, forming, and bonding microsheet glass. Procedures are also defined for surface cleaning, and EP-3 epoxy application. The results and analyses from atomic oxygen and thermal cycling tests are used to determine the effects of orbital conditions in a space environment.

  17. Development of technology for coal thermal power generation. Present state and future forecast

    Energy Technology Data Exchange (ETDEWEB)

    Yoshimura, Uichiro

    1987-01-01

    Summary of the 1987 coal technology development projects supported by the Agency of Natural Resources and Energy, and the related data such as positioning of coal thermal power plants, application technoloy system, etc. are presented. The coal power generation technology system projects scheduled for 1980 - 1990 were introduced. For the environmental protection, air polution constitutes a big problem, and technologies of desulfurization, denitration, etc. have been developed. In the field of application technology, liquefaction of coal, utilization of low-grade coals, coal gasification, application to combined cycle power generation, etc. can be quoted. The agency is supporting development of various application technologies as the 1987 projects, among them are: Development of entrained bed coal gasification power plant, Verification experiments of technologies for dry desulfurization for coal thermal power plant, Verification tests for operational improvement of coal thermal power plant, Study on the possibility of introducing large scale fluidized bed boiler to coal thermal power generation, Investigation of new power generation systems, Development of high performance coal thermal power technology, and Development of optimum control system for large scale fluidized bed boiler. (2 tabs, 4 photos)

  18. A Novel Method for Technology Forecasting and Developing R&D Strategy of Building Integrated Photovoltaic Technology Industry

    Directory of Open Access Journals (Sweden)

    Yu-Jing Chiu

    2012-01-01

    Full Text Available Because of global warming, renewable energy technologies have become more essential currently, with solar energy technology advancing worldwide. Therefore, interdisciplinary integration is an important trend, and building-integrated photovoltaic (BIPV is an emerging technology involving the photovoltaic and building fields. The purpose of this study is to understand the technology evolution of BIPV and to determine the R&D planning direction. This paper proposes a hybrid approach to explore the life cycle of BIPV technology and develop the R&D strategy of related industries. The proposed approach comprises the following submodules. First, patent analysis is employed to transform patent documents into structured data. Second, the logistic growth model is used to explore the life cycle of BIPV technology. Third, a patent matrix map analysis is used to develop the R&D strategy of the BIPV industry. Through the analysis by the logistic model, the BIPV technology is transformed from the emerging stage to the growth stage of a long-term life cycle. The other important result is created by the three-dimensional matrix for R&D strategies in this paper.

  19. Needed Actions within Defense Acquisitions Based on a Forecast of Future Mobile Information and Communications Technologies Deployed in Austere Environments

    Science.gov (United States)

    2013-03-01

    almost autonomously by interacting within its environment without human intervention (Gorcin & Arslan, 2008). Accordingly, networks are increasingly...technology: The first technological steps-sharp edges, fire, the wheel -took tens of thousands of years. For people living in this era, there was...Keeney, S., McKenna, H. (2000). Research Guidelines for the Delphi Survey Technique. Journal of Advanced Nursing , 32(4), 1008-1015. Hasson, F

  20. Forecasting Innovation Pathways (FIP) for new and emerging science and technologies

    OpenAIRE

    Robinson, Douglas; Huang, Lu; Guo, Yan; Porter, Alan L

    2013-01-01

    International audience; "New" and "Emerging Science" and "Technologies" ("NESTs") have tremendous innovation potential. However this must be weighed against enormous uncertainties caused by many unknowns. The authors of this paper offer a framework to analyze NESTs to help ascertain likely innovation pathways.We have devised a 10-step framework based on extensive Future-oriented Technology Analyses ("FTA") experience, enriched by in-depth case analyses. In the paper, we describe our analytica...

  1. Forecasting Innovation Pathways (FIP) for new and emerging science and technologies

    OpenAIRE

    Robinson, Douglas,; Huang, Lu; Guo, Yan; Porter, Alan L.

    2013-01-01

    International audience; "New" and "Emerging Science" and "Technologies" ("NESTs") have tremendous innovation potential. However this must be weighed against enormous uncertainties caused by many unknowns. The authors of this paper offer a framework to analyze NESTs to help ascertain likely innovation pathways.We have devised a 10-step framework based on extensive Future-oriented Technology Analyses ("FTA") experience, enriched by in-depth case analyses. In the paper, we describe our analytica...

  2. The ensemble forecasting technique of the thunderstorm and its application%雷暴云的集合预报技术及其应用

    Institute of Scientific and Technical Information of China (English)

    王佳; 智协飞; 陈钰文; 商兆堂; 白卡娃

    2012-01-01

    A thunderstorm ensemble forecasting approach is perti~rmed by the ensemble analysis of the cloud model' s forecast results according to the initial condition aggregation provided by the grid fore-cast results of the mesoscale non-hydrostatic WRF model. The approach is applied to forecast the char-acteristics of thunderstorm around Nanjing one day in advance and is verified by the Doppler radar data of the thunderstorms in summer in Nanjing. Results show that the intensity and distribution of thunder-storms over the research area is reasonably predicted one day in advance. It is particularly good to fore-cast the distribution of the strong thunderstorms by using the ensemble forecasting technique. Moreover, the application of the PDF(probability density function)of thunderstorms' duration into the probability forecasting of the influenced area of thunderstorms improves the radar' s warning and monitoring capac-ity of local thunderstorms.%以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒雷达资料(SCIT,storm cell identification and tracking)进行预报效果的检验。结果表明,雷暴云的集合预报对研究区域内未来一天雷暴强度、分布预报效果较好,尤其对强雷暴的分布有较强的预警预测能力。此外,雷暴持续时间概率密度分布的集合预报产品,在雷暴影响范围概率预报上的应用,提高了雷达对雷暴的预警监测能力。

  3. Comparing source inversion techniques for GPS-based local tsunami forecasting: A case study for the April 2014 M8.1 Iquique, Chile, earthquake

    Science.gov (United States)

    Chen, Kejie; Babeyko, Andrey; Hoechner, Andreas; Ge, Maorong

    2016-04-01

    Real-time GPS is nowadays considered as a valuable component of next generation near-field tsunami early warning systems able to provide fast and reliable source parameters. Looking for optimal methodologies and assessing corresponding uncertainties becomes an important task. We take the opportunity and consider the 2014 Pisagua event as a case study to explore tsunami forecast uncertainty related to the GPS-based source inversion. We intentionally neglect all other sources of uncertainty (observation set, signal processing, wave simulation, etc.) and exclusively assess the effect of inversion technique. In particular, we compare three end-member methods: (1) point-source fastCMT (centroid moment tensor), (2) distributed slip along predefined plate interface, and (3) unconstrained inversion into a single uniform slip finite fault. The three methods provide significantly different far-field tsunami forecast but show surprisingly similar tsunami predictions in the near field.

  4. Day-Ahead Wind Speed Forecasting Using Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Guoqiang Sun

    2014-01-01

    Full Text Available With the development of wind power technology, the security of the power system, power quality, and stable operation will meet new challenges. So, in this paper, we propose a recently developed machine learning technique, relevance vector machine (RVM, for day-ahead wind speed forecasting. We combine Gaussian kernel function and polynomial kernel function to get mixed kernel for RVM. Then, RVM is compared with back propagation neural network (BP and support vector machine (SVM for wind speed forecasting in four seasons in precision and velocity; the forecast results demonstrate that the proposed method is reasonable and effective.

  5. Are Lipases Still Important Biocatalysts? A Study of Scientific Publications and Patents for Technological Forecasting.

    Science.gov (United States)

    Daiha, Karina de Godoy; Angeli, Renata; de Oliveira, Sabrina Dias; Almeida, Rodrigo Volcan

    2015-01-01

    The great potential of lipases is known since 1930 when the work of J. B. S. Haldane was published. After eighty-five years of studies and developments, are lipases still important biocatalysts? For answering this question the present work investigated the technological development of four important industrial sectors where lipases are applied: production of detergent formulations; organic synthesis, focusing on kinetic resolution, production of biodiesel, and production of food and feed products. The analysis was made based on research publications and patent applications, working as scientific and technological indicators, respectively. Their evolution, interaction, the major players of each sector and the main subject matters disclosed in patent documents were discussed. Applying the concept of technology life cycle, S-curves were built by plotting cumulative patent data over time to monitor the attractiveness of each technology for investment. The results lead to a conclusion that the use of lipases as biocatalysts is still a relevant topic for the industrial sector, but developments are still needed for lipase biocatalysis to reach its full potential, which are expected to be achieved within the third, and present, wave of biocatalysis.

  6. Are Lipases Still Important Biocatalysts? A Study of Scientific Publications and Patents for Technological Forecasting.

    Directory of Open Access Journals (Sweden)

    Karina de Godoy Daiha

    Full Text Available The great potential of lipases is known since 1930 when the work of J. B. S. Haldane was published. After eighty-five years of studies and developments, are lipases still important biocatalysts? For answering this question the present work investigated the technological development of four important industrial sectors where lipases are applied: production of detergent formulations; organic synthesis, focusing on kinetic resolution, production of biodiesel, and production of food and feed products. The analysis was made based on research publications and patent applications, working as scientific and technological indicators, respectively. Their evolution, interaction, the major players of each sector and the main subject matters disclosed in patent documents were discussed. Applying the concept of technology life cycle, S-curves were built by plotting cumulative patent data over time to monitor the attractiveness of each technology for investment. The results lead to a conclusion that the use of lipases as biocatalysts is still a relevant topic for the industrial sector, but developments are still needed for lipase biocatalysis to reach its full potential, which are expected to be achieved within the third, and present, wave of biocatalysis.

  7. Forecast Forecasts the Trend

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The latest release of "2009 China Luxury Forecast" shows that while the financial crisis is leading a general decline in demand for luxury brands in Europe,America and Japan,the global economic downturn has had limited impact on Chinese luxury consumption and that there is widespread confidence in the future among Chinese luxury consumers.

  8. Forecast Forecasts the Trend

    Institute of Scientific and Technical Information of China (English)

    Wang Ting

    2009-01-01

    @@ The latest release of "2009 China Luxury Forecast" shows that while the financial crisis is leading a general decline in demand for luxury brands in Europe,America and Japan,the global economic downturn has had limited impact on Chinese luxury consumption and that there is widespread confidence in the future among Chinese luxury consumers.

  9. Technology forecasting for space communication. [analysis of systems for application to Spacecraft Data and Tracking Network

    Science.gov (United States)

    1973-01-01

    A study was conducted to determine techniques for application to space communication. The subjects considered are as follows: (1) optical communication systems, (2) laser communications for data acquisition networks, (3) spacecraft data rate requirements, (4) telemetry, command, and data handling, (5) spacecraft tracking and data network antenna and preamplifier cost tradeoff study, and (6) spacecraft communication terminal evaluation.

  10. Performance of Personal Identification System Technique Using Iris Biometrics Technology

    Directory of Open Access Journals (Sweden)

    V.K. Narendira Kumar

    2013-04-01

    Full Text Available The Iris identification as one of the significant techniques of biometric identification systems s and iris recognition algorithm is described. Biometric technology advances intellectual properties are wanted by many unauthorized personnel. As a result many researchers have being searching ways for more secure authentication methods for the user access. Iris recognition uses iris patterns for personnel identification. The system steps are capturing iris patterns; determining the location of iris boundaries; converting the iris boundary to the stretched polar coordinate system; extracting iris code based on texture analysis. The system has been implemented and tested using dataset of number of samples of iris data with different contrast quality. The developed algorithm performs satisfactorily on the images, provides 93% accuracy. Experimental results show that the proposed method has an encouraging performance.

  11. Knowledge/Data Mining, Assessment and Forecasting of Ground Military Vehicle Technologies

    Science.gov (United States)

    2010-06-11

    or . UNCLASSIFIED 4 National Automotive Center “Shifted- Gears Organization”NAC-TARDECs Technology Thrust Areas TARDEC Chief Scientist Director...Displacement      12. Uniform Potential • To reduce load to lift / lower ‐ Pulleys • Rollers on luggage • Rollerblading to work UNCLASSIFIED 19 Some

  12. Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

    Science.gov (United States)

    Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

    2015-11-01

    One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

  13. The Forecasting of 3G Market in India Based on Revised Technology Acceptance Model

    CERN Document Server

    Singh, Sudha; Singh, M K; Singh, Sujeet Kumar; 10.5121/ijngn.2010.2206

    2010-01-01

    3G, processor of 2G services, is a family of standards for mobile telecommunications defined by the International Telecommunication Union [1]. 3G services include wide-area wireless voice telephone, video calls, and wireless data, all in a mobile environment. It allows simultaneous use of speech and data services and higher data rates.3G is defined to facilitate growth, increased bandwidth and support more diverse applications. The focus of this study is to examine the factors affecting the adoption of 3G services among Indian people. The study adopts the revised Technology Acceptance Model by adding five antecedents-perceived risks, cost of adoption, perceived service quality, subjective norms, and perceived lack of knowledge. Data have collected from more than 400 school/college/Institution students & employees of various Government/Private sectors using interviews & various convenience sampling procedures and analyzed using MS excel and MATLAB. Result shows that perceived usefulness has the most si...

  14. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

    Science.gov (United States)

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  15. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Ani Shabri

    2014-01-01

    Full Text Available Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI, has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  16. 风电预测技术及其性能评价综述%A Review of the Wind Power Forecasting Technology and Its Performance Evaluation

    Institute of Scientific and Technical Information of China (English)

    郑婷婷; 王海霞; 李卫东

    2013-01-01

      随着入网风电比例的增加,风电预测已成为保证电网安全经济运行的必要技术。归纳了风电预测的概念与分类,综述了实用风电预测系统和理论研究的最新进展,尤其是关于风电预测技术的性能评价以及监督考核措施。提出了几点未来工作的思路,为风电预测相关研究提供参考。%With the proportion growth of wind power integrated into the power system, wind power forecasting has become an indispensable technology to ensure the safe and economical operation of the system. Summarizing the concepts and classification of wind power forecasting, this paper does a review on the development of practical application and theoretical study of wind power forecasting system, especially about its performance evaluation and supervision measures. Finally, some challenges and future works are put forward as a reference for the relevant study of wind power forecasting.

  17. Multidisciplinary studies of the social, economic and political impact resulting from recent advances in satellite meteorology. Volume 6: Executive summary. [technological forecasting spacecraft control/attitude (inclination) -classical mechanics

    Science.gov (United States)

    1975-01-01

    An assessment of the technological impact of modern satellite weather forecasting for the United States is presented. Topics discussed are: (1) television broadcasting of weather; (2) agriculture (crop production); (3) water resources; (4) urban development; (5) recreation; and (6) transportation.

  18. Earthquake forecast enrichment scores

    Directory of Open Access Journals (Sweden)

    Christine Smyth

    2012-03-01

    Full Text Available The Collaboratory for the Study of Earthquake Predictability (CSEP is a global project aimed at testing earthquake forecast models in a fair environment. Various metrics are currently used to evaluate the submitted forecasts. However, the CSEP still lacks easily understandable metrics with which to rank the universal performance of the forecast models. In this research, we modify a well-known and respected metric from another statistical field, bioinformatics, to make it suitable for evaluating earthquake forecasts, such as those submitted to the CSEP initiative. The metric, originally called a gene-set enrichment score, is based on a Kolmogorov-Smirnov statistic. Our modified metric assesses if, over a certain time period, the forecast values at locations where earthquakes have occurred are significantly increased compared to the values for all locations where earthquakes did not occur. Permutation testing allows for a significance value to be placed upon the score. Unlike the metrics currently employed by the CSEP, the score places no assumption on the distribution of earthquake occurrence nor requires an arbitrary reference forecast. In this research, we apply the modified metric to simulated data and real forecast data to show it is a powerful and robust technique, capable of ranking competing earthquake forecasts.

  19. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    indicated that forecasting experience has little relationship to forecasting performance. In the latter three studies, neophyte forecasters became... Europe . Within a few months after a new commander was assigned, this unit’s performance rose to first place in the theater and remained there

  20. Improving photovoltaics grid integration through short time forecasting and self-consumption

    OpenAIRE

    Masa Bote, Daniel; Castillo Cagigal, Manuel; Matallanas de Avila, Eduardo; Caamaño Martín, Estefanía; Gutierrez Martín, Alvaro; Monasterio-Huelin Maciá, Felix; Jiménez Leube, Francisco Javier

    2014-01-01

    The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. O...

  1. NEEMO 21: Tools, Techniques, Technologies and Training for Science Exploration

    Science.gov (United States)

    Graff, T.; Young, K.; Coan, D.; Merselis, D.; Bellantuono, A.; Dougan, K.; Rodriguez-Lanetty, M.; Nedimyer, K.; Chappell, S.; Beaton, K.; Naids, A.; Hood, A.; Reagan, M.; Rampe, E.; Todd, W.; Poffenberger, J.; Garrison, D.

    2017-01-01

    The 21st mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated operational field test and evaluation of tools, techniques, technologies, and training for science driven exploration during extravehicular activity (EVA). The mission was conducted in July 2016 from the Aquarius habitat, an underwater laboratory, off the coast of Key Largo in the Florida Keys National Marine Sanctuary. An international crew of eight (comprised of NASA and ESA astronauts, engineers, medical personnel, and habitat technicians) lived and worked in and around Aquarius and its surrounding reef environment for 16 days. The integrated testing (both interior and exterior objectives) conducted from this unique facility continues to support current and future human space exploration endeavors. Expanding on the scientific and operational evaluations conducted during NEEMO 20, the 21st NEEMO mission further incorporated a diverse Science Team comprised of planetary geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center, marine scientists from the Department of Biological Sciences at Florida International University (FIU) Integrative Marine Genomics and Symbiosis (IMaGeS) Lab, and conservationists from the Coral Restoration Foundation. The Science Team worked in close coordination with the long-standing EVA operations, planning, engineering, and research components of NEEMO in all aspects of mission planning, development, and execution.

  2. Genetic technologies to enhance the Sterile Insect Technique (SIT)

    Energy Technology Data Exchange (ETDEWEB)

    Alphey, Luke; Baker, Pam; Condon, George C.; Condon, Kirsty C.; Dafa' alla, Tarig H.; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M.; Nimmo, Derric D.; O' Connell, Sinead; Phillips, Caroline E.; Plackett, Andrew; Scaife, Sarah; Woods, Alexander, E-mail: luke.alphey@zoo.ox.ac.u [Oxitec Ltd., Oxford (United Kingdom); Burton, Rosemary S.; Epton, Matthew J.; Gong, Peng [University of Oxford (United Kingdom). Dept. of Zoology

    2006-07-01

    The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

  3. Analytical techniques for thin films treatise on materials science and technology

    CERN Document Server

    Tu, K N

    1988-01-01

    Treatise on Materials Science and Technology, Volume 27: Analytical Techniques for Thin Films covers a set of analytical techniques developed for thin films and interfaces, all based on scattering and excitation phenomena and theories. The book discusses photon beam and X-ray techniques; electron beam techniques; and ion beam techniques. Materials scientists, materials engineers, chemical engineers, and physicists will find the book invaluable.

  4. RATIONALE FOR PREVENTION OF CARDIO-CEREBRAL COMPLICATIONS IN THE METABOLIC SYNDROME BASED ON MATHEMATICAL FORECASTING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    S. V. Chernavskii

    2011-01-01

    Full Text Available Objective — to study prevention of cardio-cerebral complications of metabolic syndrome on the basis of mathematical methods of forecasting.Subjects and methods. A discriminant analysis of clinical and instrumental data of patients with MS.Results of this study allow the early (prenosological stages of the metabolic syndrome using the linear discriminant equations to predict thedevelopment of myocardial infarction up to 89.3 %, stroke — up to 87.8 %.Conclusion. The diagnostic and treatment algorithms developed based on the stratification of cardiovascular risk index, allow us to give sound recommendations for targeted prevention of cardio-cerebral complications.

  5. Advanced manufacturing techniques for next generation power FET technology

    OpenAIRE

    2005-01-01

    The development and incorporation of an evaporated airbridge technology into an established power pHEMT device is described. Advantages of this technology over a conventional plated technology are discussed. Use of this technology has resulted in improvements to the process flow in terms of reduced complexity and cycle time. Improvements in uniformity and reduced feature size have enabled the use of an automated visual inspection capability to reliably differentiate good and bad die.

  6. Further Discussion the Development on New Weather Forecasting Technology System%再论气象台天气预报技术新体系的发展

    Institute of Scientific and Technical Information of China (English)

    徐羹慧

    2012-01-01

    在前期对气象台天气预报技术发展的现状分析、发展趋势预测的基础上,从气象台天气预报技术的基本属性分析出发,进一步探讨气象台天气预报技术体系的基本框架和内容,并就推进技术发展的若干重要问题进行讨论。本文认为,如同“临床医学”一样,建筑在多种优秀成果基础上气象台天气预报技术的发展已自成体系,要象重视数值天气预报那样重视气象台预报技术体系的发展,发挥气象科技进步的综合效益,加快气象台一线预报服务水平的提高。%Based on the previous analysis upon the progress of weather forecasting system and the prediction of its developing tendency, the fundamental frame and content of weather forecasting technology system and several important issues regarding advancing technology were further discussed in this paper through analyzing the basic attribute of weather prediction skills. It was advocated that, just as "Clinical Medicine" ,the weather prediction technology founded upon various excellent researching outcomes has already had its own system. Just like numerical weather forecast ,the development of weather prediction technology system should be emphasized. Not only the benefit of the advanced meteorological science and technology should be exerted ,but also the improving process of weather prediction should be speeded up.

  7. 数据挖掘技术在精细化温度预报中的应用%Application of Data Mining Technique on Refined Temperature Forecast

    Institute of Scientific and Technical Information of China (English)

    段文广; 周晓军; 石永炜

    2012-01-01

    简要介绍了精细化天气预报和气象数据挖掘应用的现状,在对BP神经网络预测方法详细分析的基础上,研究了基于时间序列数据挖掘实现精细化温度预报的方法。该方法基于时序分析技术,建立起适合于BP神经网络的输入样本模型,通过反复学习从温度时序中建立预测模型,将其用于未来24 h的精细化温度预报。同时,对BP神经网络算法和步骤做了简要介绍,针对原有的BP算法存在的不足,做了一些改进。最后,通过对预测挖掘系统的设计和在Matlab6.5仿真平台上的试验,建立了温度预报模型,以兰州市观测站数据为时间序列研究对象,对精细化温度预报进行了仿真实现。对基于时序的数据挖掘理论的应用和开发精细化温度预报方法做了有益的探索。%The paper introduces the domestic and international current situation about the development of refined weather forecast and data mining application.On the basis of detailed analysis of BP neural network forecasting method,this paper researches a data mining method based on time series analysis technology which can be used on refined temperature forecast.This method can build an input sample pattern which is suit for the BP neural networks of data mining and finally establish a predictive model by studying temperature time series again and again,which used for the next 24 hours refined temperature forecast.At the same time,a brief introduction of the algorithm and steps of the BP neural network is given out in the paper,and some further improvement is made aiming at the deficiency of the original BP algorithm.Finally,through design data mining system and test on the Matlab6.5 simulation platform,the temperature forecast model was established.This study had done some helpful exploration on application of data mining theory based on time series analysis technology and developed method of refined weather forecast.

  8. Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean.

    Science.gov (United States)

    Marcos, Raül; Llasat, Ma Carmen; Quintana-Seguí, Pere; Turco, Marco

    2017-08-09

    In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Artificial neural networks environmental forecasting in comparison with multiple linear regression technique: From heavy metals to organic micropollutants screening in agricultural soils

    Science.gov (United States)

    Bonelli, Maria Grazia; Ferrini, Mauro; Manni, Andrea

    2016-12-01

    The assessment of metals and organic micropollutants contamination in agricultural soils is a difficult challenge due to the extensive area used to collect and analyze a very large number of samples. With Dioxins and dioxin-like PCBs measurement methods and subsequent the treatment of data, the European Community advises the develop low-cost and fast methods allowing routing analysis of a great number of samples, providing rapid measurement of these compounds in the environment, feeds and food. The aim of the present work has been to find a method suitable to describe the relations occurring between organic and inorganic contaminants and use the value of the latter in order to forecast the former. In practice, the use of a metal portable soil analyzer coupled with an efficient statistical procedure enables the required objective to be achieved. Compared to Multiple Linear Regression, the Artificial Neural Networks technique has shown to be an excellent forecasting method, though there is no linear correlation between the variables to be analyzed.

  10. Forecasting in marketing

    OpenAIRE

    Franses, Philip Hans

    2004-01-01

    textabstractWith the advent of advanced data collection techniques, there is an increased interest in using econometric models to support decisions in marketing. Due to the sometimes specific nature of variables in marketing, the discipline uses econometric models that are rarely, if ever, used elsewhere. This chapter deals with techniques to derive forecasts from these models. Due to the intrinsic non-linear nature of these models, these techniques draw heavliy on simulation techniques.

  11. Forecasting in marketing

    OpenAIRE

    Franses, Philip Hans

    2004-01-01

    textabstractWith the advent of advanced data collection techniques, there is an increased interest in using econometric models to support decisions in marketing. Due to the sometimes specific nature of variables in marketing, the discipline uses econometric models that are rarely, if ever, used elsewhere. This chapter deals with techniques to derive forecasts from these models. Due to the intrinsic non-linear nature of these models, these techniques draw heavliy on simulation techniques.

  12. Forecasting Daily Demand in Cash Supply Chains

    National Research Council Canada - National Science Library

    Michael Wagner

    2010-01-01

    ...: This study contrasted competing techniques of forecasting daily demand in cash supply chains in order to determine the overall performance and the potential of joint forecasting for integrated planning...

  13. Demand forecasting

    OpenAIRE

    Gregor, Belčec

    2011-01-01

    Companies operate in an increasingly challenging environment that requires them to continuously improve all areas of the business process. Demand forecasting is one area in manufacturing companies where we can hope to gain great advantages. Improvements in forecasting can result in cost savings throughout the supply chain, improve the reliability of information and the quality of the service for our customers. In the company Danfoss Trata, d. o. o. we did not have a system for demand forecast...

  14. Construction Project Forecasting "Practical Use of EV Metrics"

    Institute of Scientific and Technical Information of China (English)

    Reda Abbas Sabry

    2014-01-01

    During this professional research--Construction Project Forecasting (Practical Use of EV Metrics), which criticize earned value management as a most distinguished methodology for forecasting the project expected end dates and expecting budget at completion, the field for the research is construction field and specially the projects which content different phases without repetitive tasks. Forecasting for construction project is a complicated process need more than applying one equation only. As assuming that, project performance during finishing stage will be similar to project performance during concrete stage is totally wrong. The case study techniques have been used to prove an important idea and also to implement a suggested protocol which actually implemented and tested and it should be considered as a research finding. The project used in this case study is "Hurgadah Intemational Airport--New Terminal Building", while executing this complex construction projects with different stages the forecasting for the project end date and final end budget were completely not realistic. The above leads to questioning the next: "Is it true that using the earned value indexes for forecasting construction projects end date and final budget is the right way? And if not, what is the right process that should be used in order to reach acceptable forecasting method?" We implement the EV measurements by the normal technique and also implement in the same month the suggested protocol for forecasting, comparing the results proof the effectiveness of the suggested protocol. The findings prove that, the construction projects need special treatment when use the EVM for forecasting. The earned value indexes created to serve the projects which have repeated tasks or can say which got one stage only, like information technology (IT) projects as those projects depending on manpower productivity and also based on few different qualifications. On such type of projects

  15. Technology Assessment of Dust Suppression Techniques Applied During Structural Demolition

    Energy Technology Data Exchange (ETDEWEB)

    Boudreaux, J.F.; Ebadian, M.A.; Williams, P.T.; Dua, S.K.

    1998-10-20

    Hanford, Fernald, Savannah River, and other sites are currently reviewing technologies that can be implemented to demolish buildings in a cost-effective manner. In order to demolish a structure properly and, at the same time, minimize the amount of dust generated from a given technology, an evaluation must be conducted to choose the most appropriate dust suppression technology given site-specific conditions. Thus, the purpose of this research, which was carried out at the Hemispheric Center for Environmental Technology (HCET) at Florida International University, was to conduct an experimental study of dust aerosol abatement (dust suppression) methods as applied to nuclear D and D. This experimental study targeted the problem of dust suppression during the demolition of nuclear facilities. The resulting data were employed to assist in the development of mathematical correlations that can be applied to predict dust generation during structural demolition.

  16. Human monitoring, smart health and assisted living techniques and technologies

    CERN Document Server

    Longhi, Sauro; Freddi, Alessandro

    2017-01-01

    This book covers the three main scientific and technological areas critical for improving people's quality of life - namely human monitoring, smart health and assisted living - from both the research and development points of view.

  17. Passive RF component technology materials, techniques, and applications

    CERN Document Server

    Wang, Guoan

    2012-01-01

    Focusing on novel materials and techniques, this pioneering volume provides you with a solid understanding of the design and fabrication of smart RF passive components. You find comprehensive details on LCP, metal materials, ferrite materials, nano materials, high aspect ratio enabled materials, green materials for RFID, and silicon micromachining techniques. Moreover, this practical book offers expert guidance on how to apply these materials and techniques to design a wide range of cutting-edge RF passive components, from MEMS switch based tunable passives and 3D passives, to metamaterial-bas

  18. Selective Chemical-Lithographic Reaction Techniques Using Radiation Technology for Biological Application

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Kwan Woo; Kim, Keo Su; Kim, Hyun Jung; Kim, Hee Suk; Lee, Mi Jin [Sogang University, Seoul (Korea, Republic of)

    2010-05-15

    This report, titled 'selective Chemical-Lithographic Reaction Techniques Using Radiation Technology for Biological Application' contains a research summary, 1) development of selective reaction technology using irradiation of electron beams, 2) preparation of functional surfaces using selective radiation technology on carbon-based nanomaterials, and 3) development of bio-applicable biochips using combinatorial surface modification

  19. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting......, there is so far no systematic research to study and compare their performance. How to select effective techniques of feature preprocessing in a forecasting model remains a problem. In this paper, the authors conduct a comprehensive study of existing feature preprocessing techniques to evaluate their empirical...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...

  20. Training Manual on Food Irradiation Technology and Techniques.

    Science.gov (United States)

    United Nations Food and Agriculture Organization, Rome (Italy).

    This training manual consists of two parts. The first covers general information and outlines various applications of food irradiation technology. The second section details laboratory exercises used to demonstrate the principles of radiation processing and the effects of radiation treatment on certain types of food. The chapters outline…

  1. Novel microstructures and technologies applied in chemical analysis techniques

    NARCIS (Netherlands)

    Spiering, Vincent L.; Spiering, V.L.; van der Moolen, Johannes N.; Burger, Gert-Jan; Burger, G.J.; van den Berg, Albert

    1997-01-01

    Novel glass and silicon microstructures and their application in chemical analysis are presented. The micro technologies comprise (deep) dry etching, thin layer growth and anodic bonding. With this combination it is possible to create high resolution electrically isolating silicon dioxide structures

  2. New Product Development: Can Technique Substitute for Technology?

    Science.gov (United States)

    Meyers, Barbara E.

    1984-01-01

    Overview of research techniques involved in gathering information on current products that can provide input into new product development highlights consumer purchase and use patterns. Comparison of mail questionnaires, telephone surveys, focus group sessions, and in-person interviews notes type of data, timing, relative costs, and advantages and…

  3. New technology - demonstration of a vector velocity technique

    DEFF Research Database (Denmark)

    Møller Hansen, Peter; Pedersen, Mads M; Hansen, Kristoffer L;

    2011-01-01

    With conventional Doppler ultrasound it is not possible to estimate direction and velocity of blood flow, when the angle of insonation exceeds 60-70°. Transverse oscillation is an angle independent vector velocity technique which is now implemented on a conventional ultrasound scanner. In this pa...

  4. Analog/RF Circuit Design Techniques for Nanometerscale IC Technologies

    NARCIS (Netherlands)

    Nauta, Bram; Annema, Anne-Johan

    2005-01-01

    CMOS evolution introduces several problems in analog design. Gate-leakage mismatch exceeds conventional matching tolerances requiring active cancellation techniques or alternative architectures. One strategy to deal with the use of lower supply voltages is to operate critical parts at higher supply

  5. New Product Development: Can Technique Substitute for Technology?

    Science.gov (United States)

    Meyers, Barbara E.

    1984-01-01

    Overview of research techniques involved in gathering information on current products that can provide input into new product development highlights consumer purchase and use patterns. Comparison of mail questionnaires, telephone surveys, focus group sessions, and in-person interviews notes type of data, timing, relative costs, and advantages and…

  6. The case for better PV forecasting

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    Rising levels of PV penetration mean increasingly sophisticated forecasting technologies are needed to maintain grid stability and maximise the economic value of PV systems. The Grid Integration working group of the European Technology and Innovation Platform – Photovoltaics (ETIP PV) shares...... the results of its ongoing research into the advantages and limitations of current forecasting technologies....

  7. An Overview of Optical Character Recognition (OCR) Technology and Techniques.

    Science.gov (United States)

    1978-06-01

    using optico -electric filters. In practice, the choice of preprocessing techniques must necessarily be related to the recognition method. For example...inter- face), Recognition Unit and Operator Communication device. A brief description of each major system component including the Input Sensor follows...accomplish several types of mark- sensor recognition. Together, they are ’ capable of recognizing machine and handprinted data intermixed on the same line. .3

  8. Beat the Instructor: An Introductory Forecasting Game

    Science.gov (United States)

    Snider, Brent R.; Eliasson, Janice B.

    2013-01-01

    This teaching brief describes a 30-minute game where student groups compete in-class in an introductory time-series forecasting exercise. The students are challenged to "beat the instructor" who competes using forecasting techniques that will be subsequently taught. All forecasts are graphed prior to revealing the randomly generated…

  9. Beat the Instructor: An Introductory Forecasting Game

    Science.gov (United States)

    Snider, Brent R.; Eliasson, Janice B.

    2013-01-01

    This teaching brief describes a 30-minute game where student groups compete in-class in an introductory time-series forecasting exercise. The students are challenged to "beat the instructor" who competes using forecasting techniques that will be subsequently taught. All forecasts are graphed prior to revealing the randomly generated…

  10. Forecasting ocean wave energy: A Comparison of the ECMWF wave model with time series methods

    DEFF Research Database (Denmark)

    Reikard, Gordon; Pinson, Pierre; Bidlot, Jean

    2011-01-01

    days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts......Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several...... energy flux. In the initial tests, the ECMWF model and the statistical models are compared directly. The statistical models do better at short horizons, producing more accurate forecasts in the 1–5 h range. The ECMWF model is superior at longer horizons. The convergence point, at which the two methods...

  11. Operational Solar Forecasting System for DNI and GHI for Horizons Covering 5 Minutes to 72 Hours

    Science.gov (United States)

    Coimbra, C. F.

    2014-12-01

    I will describe the methodology used to develop and deploy operationally a comprehensive solar forecasting system for both concentrated and non-concentrated solar technologies. This operational forecasting system ingests data from local telemetry, remote sensing and Numerical Weather Prediction (NWP) models, processes all the diferent types of data (time series, sky images, satellite images, gridded data, etc.) to produce concatenated solar forecasts from 5 minutes out to 72 hours into the future. Each forecast is optimized with stochastic learning techniques that include input selection, model topology optimization, model output statistics, metric fitness optimization and machine learning. These forecasts are used by solar generators (plant managers), utilities and independent system operators for operations, scheduling, dispatching and market participation.

  12. Research on the Forecast Model of Total Viable Count on Bacon Based on Hyper spectral Imaging Technique

    Directory of Open Access Journals (Sweden)

    Zhao Junhua

    2016-01-01

    Full Text Available The total viable count (TVC in bacon overweight can cause serious damage to human health. In order to find a rapid and nondestructive method of TVC, hyper spectral imaging technique was applied to quantitatively analysis of TVC on bacon. Comprehensively comparing the pretreatment method of multiple scattering, derivative method and so on finally the multiple scattering for pretreatment was used. And the interval optimization method of least squares model was set up to predict, and get a good prediction results. The correlation coefficient of the calibration and predictions respectively was 0.808 and 0.808, interactive authentication root mean square error was 0.115 and 0.198 respectively. Therefore, hyper spectral imaging technique combining iPLS can be used for the rapid detection of TVC on bacon.

  13. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  14. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  15. Procedure of Forecasting Operational and Extremal State of Critical Systems of the Rocket Technique Under Repeated Thermo-Force Loading

    Directory of Open Access Journals (Sweden)

    Shevchenko Yu.M.

    2015-09-01

    Full Text Available The mathematical model for investigation of the thermoelastoplastic stress-strain state and the strength of the rocket technique systems under the repeated starting is proposed. The thermal conductivity equation and constitutive equations of thermoplasticity for the repeated elastic-plastic deformation processes of isotropic materials along small-curvature paths, the strength and low-cyclic fatigue criteria, numerical methods for solving the boundary-value heat conduction problems and corresponding computer software are used.

  16. Comparison between the corrosion forecast based on the potential measurement and the determination of the corrosion rate of the reinforcement bar by means of electrochemical techniques

    Directory of Open Access Journals (Sweden)

    Castaneda, A.

    2003-12-01

    Full Text Available The ASTA4 876-91 standard establishes a corrosion forecast of concrete reinforced bar by measuring the electrochemical potential. This forecast is based on thermodynamic considerations without taking into account the kinetic of the corrosion process. A comparison was made between the results obtained based on this standard and others using electrochemical techniques (Tafel, Rp, EIS, Electrochemical Noise. These techniques allows to obtain the corrosion rate in samples having 0.4, 0.5 and 0.66 water/cement ratios submitted to salt spray outdoors and by immersion in 3% saline solution during a test time of 20 months. Differences were detected between the results obtained using the ASTM standard and the electrochemical techniques used. The main difference is that samples submitted to immersion shows a higher probability of corrosion than samples submitted to salt spray; however, the electrochemical techniques showed the contrary concerning the corrosion kinetic process .A comparison respecting corrosion rate was also made between the results obtained by the different electrochemical techniques. It is very well known that all electrochemical techniques supposed always general corrosion except electrochemical noise. Using the technique the pitting index can be calculated. It shows that localized corrosion is the most predominant

    La norma ASTM 876-91 establece un pronóstico de corrosión de la barra de refuerzo del hormigón armado mediante la determinación de potenciales electroquímicos. Este pronóstico se basa en consideraciones termodinámicas, sin tener en cuenta la cinética del proceso de corrosión. Se comparan los resultados obtenidos aplicando esta norma con técnicas electroquímicas (Tafel, Rp, EIS, Ruido Electroquímico que permiten calcular la velocidad de corrosión en probetas con relaciones agua/cemento 0,4, 0,5 y 0,66 sometidas a niebla salina en condiciones naturales y en inmersión en solución salina al 3% durante un

  17. IR Drop Analysis and Its Reduction Techniques in Deep Submicron Technology

    Directory of Open Access Journals (Sweden)

    Vanpreet Kaur

    2015-01-01

    Full Text Available This paper presents a detailed conceptual analysis of IR Drop effect in deep submicron technologies and its reduction techniques. The IR Drop effect in power/ground network increases rapidly with technology scaling. This affects the timing of the design and hence the desired speed. It is shown that in present day designs, using well known reduction techniques such as wire sizing and decoupling capacitor insertion, may not be sufficient to limit the voltage fluctuations and hence, two more important methods such as selective glitch reduction technique and IR Drop reduction through combinational circuit partitioning are discussed and the issues related to all the techniques are revised.

  18. Internationalizing undergraduate psychology education: Trends, techniques, and technologies.

    Science.gov (United States)

    Takooshian, Harold; Gielen, Uwe P; Plous, Scott; Rich, Grant J; Velayo, Richard S

    2016-01-01

    How can we best internationalize undergraduate psychology education in the United States and elsewhere? This question is more timely than ever, for at least 2 reasons: Within the United States, educators and students seek greater contact with psychology programs abroad, and outside the United States, psychology is growing apace, with educators and students in other nations often looking to U.S. curricula and practices as models. In this article, we outline international developments in undergraduate psychology education both in the United States and abroad, and analyze the dramatic rise of online courses and Internet-based technologies from an instructional and international point of view. Building on the recommendations of the 2005 APA Working Group on Internationalizing the Undergraduate Psychology Curriculum, we then advance 14 recommendations on internationalizing undergraduate psychology education--for students, faculty, and institutions.

  19. Flash floods: forecasting and warning

    National Research Council Canada - National Science Library

    Sene, Kevin

    2013-01-01

    ... and levees.The volume discusses the increasing use of meteorological observation and forecasting techniques to extend the lead time available for warning, combined with hydrological models for the river response...

  20. Human factors multi-technique approach to teenage engagement in digital technologies health research

    OpenAIRE

    Lang, Alexandra R; Craven, Michael P; Atkinson, Sarah; Simons, Lucy; Cobb, Sue; Mazzola, Marco

    2016-01-01

    This chapter explores the use of multi-techniques for teenage HCI health research. Through four case studies we present information about adolescents as users of healthcare services and technologies, adolescent personal development and the human factors approaches through which teenagers have been involved in healthcare research projects. In each case study; comprising of the design or evaluation of a new digital technology for supporting health or well-being, the techniques used by researche...

  1. Foresight and Forecasts

    DEFF Research Database (Denmark)

    Kilbourn, Kyle; Bay, Marie Brøndum

    In predicting areas of growth, public innovation projects may rely on optimistic visions of technology still in development as a way of ensuring novelty for funding. This paper explores what happens when forecasts of robotic technology meets the practice of sterile supply in a preliminary stage......, the most sustainable innovation stems from the dialogical interaction between practitioner foresight and societal forecasting, requiring continued development of participatory design as it moves into new contexts....... of an ongoing project. We examine the nature of participation in design on three levels: in the sterilization ward, this particular project and society in general. From our case, we suggest that while innovation projects proceeding from a certain technological perspective can succeed at building excitement...

  2. An Overview of Short-term Statistical Forecasting Methods

    DEFF Research Database (Denmark)

    Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat

    2006-01-01

    An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...

  3. An Overview of Short-term Statistical Forecasting Methods

    DEFF Research Database (Denmark)

    Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat

    2006-01-01

    An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...

  4. Adapting a Markov Monte Carlo simulation model for forecasting the number of coronary artery revascularisation procedures in an era of rapidly changing technology and policy.

    Science.gov (United States)

    Mannan, Haider R; Knuiman, Matthew; Hobbs, Michael

    2008-06-25

    Treatments for coronary heart disease (CHD) have evolved rapidly over the last 15 years with considerable change in the number and effectiveness of both medical and surgical treatments. This period has seen the rapid development and uptake of statin drugs and coronary artery revascularization procedures (CARPs) that include Coronary Artery Bypass Graft procedures (CABGs) and Percutaneous Coronary Interventions (PCIs). It is difficult in an era of such rapid change to accurately forecast requirements for treatment services such as CARPs. In a previous paper we have described and outlined the use of a Markov Monte Carlo simulation model for analyzing and predicting the requirements for CARPs for the population of Western Australia (Mannan et al, 2007). In this paper, we expand on the use of this model for forecasting CARPs in Western Australia with a focus on the lack of adequate performance of the (standard) model for forecasting CARPs in a period during the mid 1990s when there were considerable changes to CARP technology and implementation policy and an exploration and demonstration of how the standard model may be adapted to achieve better performance. Selected key CARP event model probabilities are modified based on information relating to changes in the effectiveness of CARPs from clinical trial evidence and an awareness of trends in policy and practice of CARPs. These modified model probabilities and the ones obtained by standard methods are used as inputs in our Markov simulation model. The projected numbers of CARPs in the population of Western Australia over 1995-99 only improve marginally when modifications to model probabilities are made to incorporate an increase in effectiveness of PCI procedures. However, the projected numbers improve substantially when, in addition, further modifications are incorporated that relate to the increased probability of a PCI procedure and the reduced probability of a CABG procedure stemming from changed CARP preference

  5. Adapting a Markov Monte Carlo simulation model for forecasting the number of Coronary Artery Revascularisation Procedures in an era of rapidly changing technology and policy

    Directory of Open Access Journals (Sweden)

    Knuiman Matthew

    2008-06-01

    Full Text Available Abstract Background Treatments for coronary heart disease (CHD have evolved rapidly over the last 15 years with considerable change in the number and effectiveness of both medical and surgical treatments. This period has seen the rapid development and uptake of statin drugs and coronary artery revascularization procedures (CARPs that include Coronary Artery Bypass Graft procedures (CABGs and Percutaneous Coronary Interventions (PCIs. It is difficult in an era of such rapid change to accurately forecast requirements for treatment services such as CARPs. In a previous paper we have described and outlined the use of a Markov Monte Carlo simulation model for analyzing and predicting the requirements for CARPs for the population of Western Australia (Mannan et al, 2007. In this paper, we expand on the use of this model for forecasting CARPs in Western Australia with a focus on the lack of adequate performance of the (standard model for forecasting CARPs in a period during the mid 1990s when there were considerable changes to CARP technology and implementation policy and an exploration and demonstration of how the standard model may be adapted to achieve better performance. Methods Selected key CARP event model probabilities are modified based on information relating to changes in the effectiveness of CARPs from clinical trial evidence and an awareness of trends in policy and practice of CARPs. These modified model probabilities and the ones obtained by standard methods are used as inputs in our Markov simulation model. Results The projected numbers of CARPs in the population of Western Australia over 1995–99 only improve marginally when modifications to model probabilities are made to incorporate an increase in effectiveness of PCI procedures. However, the projected numbers improve substantially when, in addition, further modifications are incorporated that relate to the increased probability of a PCI procedure and the reduced probability of a CABG

  6. An Operational Technology for Assimilating Lagrangian Data Based on Dynamical Systems Techniques

    Science.gov (United States)

    2016-06-07

    An Operational Technology for Assimilating Lagrangian Data Based on Dynamical Systems Techniques Christopher K. R. T. Jones Department of... technology for assimilating Lagrangian data. This new Lagrangian data assimilation platform is expected to be particularly effective in ocean regions where...COVERED 00-00-2006 to 00-00-2006 4. TITLE AND SUBTITLE An Operational Technology for Assimilating Lagrangian Data Based on Dynamical Systems

  7. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  8. Changing teaching techniques and adapting new technologies to improve student learning in an introductory meteorology and climate course

    Science.gov (United States)

    Cutrim, E. M.; Rudge, D.; Kits, K.; Mitchell, J.; Nogueira, R.

    2006-06-01

    Responding to the call for reform in science education, changes were made in an introductory meteorology and climate course offered at a large public university. These changes were a part of a larger project aimed at deepening and extending a program of science content courses that model effective teaching strategies for prospective middle school science teachers. Therefore, revisions were made to address misconceptions about meteorological phenomena, foster deeper understanding of key concepts, encourage engagement with the text, and promote inquiry-based learning. Techniques introduced include: use of a flash cards, student reflection questionnaires, writing assignments, and interactive discussions on weather and forecast data using computer technology such as Integrated Data Viewer (IDV). The revision process is described in a case study format. Preliminary results (self-reflection by the instructor, surveys of student opinion, and measurements of student achievement), suggest student learning has been positively influenced. This study is supported by three grants: NSF grant No. 0202923, the Unidata Equipment Award, and the Lucia Harrison Endowment Fund.

  9. Changing teaching techniques and adapting new technologies to improve student learning in an introductory meteorology and climate course

    Directory of Open Access Journals (Sweden)

    E. M. Cutrim

    2006-01-01

    Full Text Available Responding to the call for reform in science education, changes were made in an introductory meteorology and climate course offered at a large public university. These changes were a part of a larger project aimed at deepening and extending a program of science content courses that model effective teaching strategies for prospective middle school science teachers. Therefore, revisions were made to address misconceptions about meteorological phenomena, foster deeper understanding of key concepts, encourage engagement with the text, and promote inquiry-based learning. Techniques introduced include: use of a flash cards, student reflection questionnaires, writing assignments, and interactive discussions on weather and forecast data using computer technology such as Integrated Data Viewer (IDV. The revision process is described in a case study format. Preliminary results (self-reflection by the instructor, surveys of student opinion, and measurements of student achievement, suggest student learning has been positively influenced. This study is supported by three grants: NSF grant No. 0202923, the Unidata Equipment Award, and the Lucia Harrison Endowment Fund.

  10. Broadband Traffic Forecasting in the Transport Network

    Directory of Open Access Journals (Sweden)

    Valentina Radojičić

    2012-07-01

    Full Text Available This paper proposes a modification of traffic forecast model generated by residential and small business (SOHO, Small Office Home Office users. The model includes forecasted values of different relevant factors and competition on broadband market. It allows forecasting the number of users for various broadband technologies and interaction impact of long-standing technologies as well as the impact of the new technology entrant on the market. All the necessary parameters are evaluated for the Serbian broadband market. The long-term forecasted results of broadband traffic are given. The analyses and evaluations performed are important inputs for the transport network resources planning.

  11. Groundwork for the Concept of Technique in Education: Herbert Marcuse and Technological Society

    Science.gov (United States)

    Pierce, Clayton

    2006-01-01

    This article articulates the groundwork for a new understanding of the concept of technique through a critical engagement with Herbert Marcuse's critical theory of technology. To this end, it identifies and engages three expressions of technique in Marcuse's work: mimesis, reified labor, and the happy consciousness. It is argued that this mapping…

  12. Groundwork for the Concept of Technique in Education: Herbert Marcuse and Technological Society

    Science.gov (United States)

    Pierce, Clayton

    2006-01-01

    This article articulates the groundwork for a new understanding of the concept of technique through a critical engagement with Herbert Marcuse's critical theory of technology. To this end, it identifies and engages three expressions of technique in Marcuse's work: mimesis, reified labor, and the happy consciousness. It is argued that this mapping…

  13. Interactive Forecasting with the National Weather Service River Forecast System

    Science.gov (United States)

    Smith, George F.; Page, Donna

    1993-01-01

    The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

  14. Advanced digital modulation: Communication techniques and monolithic GaAs technology

    Science.gov (United States)

    Wilson, S. G.; Oliver, J. D., Jr.; Kot, R. C.; Richards, C. R.

    1983-01-01

    Communications theory and practice are merged with state-of-the-art technology in IC fabrication, especially monolithic GaAs technology, to examine the general feasibility of a number of advanced technology digital transmission systems. Satellite-channel models with (1) superior throughput, perhaps 2 Gbps; (2) attractive weight and cost; and (3) high RF power and spectrum efficiency are discussed. Transmission techniques possessing reasonably simple architectures capable of monolithic fabrication at high speeds were surveyed. This included a review of amplitude/phase shift keying (APSK) techniques and the continuous-phase-modulation (CPM) methods, of which MSK represents the simplest case.

  15. Ensemble Forecast: A New Approach to Uncertainty and Predictability

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ensemble forecasts is to try to assimilate the initial uncertainty (initial error) and the forecast uncertainty (forecast error) by applying either the initial perturbation method or the multi-model/multiphysics method. In fact, the mean of an ensemble forecast offers a better forecast than a deterministic (or control) forecast after a short lead time (3 5 days) for global modelling applications. There is about a 1-2-day improvement in the forecast skill when using an ensemble mean instead of a single forecast for longer lead-time. The skillful forecast (65% and above of an anomaly correlation) could be extended to 8 days (or longer) by present-day ensemble forecast systems. Furthermore, ensemble forecasts can deliver a probabilistic forecast to the users, which is based on the probability density function (PDF)instead of a single-value forecast from a traditional deterministic system. It has long been recognized that the ensemble forecast not only improves our weather forecast predictability but also offers a remarkable forecast for the future uncertainty, such as the relative measure of predictability (RMOP) and probabilistic quantitative precipitation forecast (PQPF). Not surprisingly, the success of the ensemble forecast and its wide application greatly increase the confidence of model developers and research communities.

  16. Continuous renal replacement therapy. Keeping pace with changes in technology and technique.

    Science.gov (United States)

    Baldwin, Ian

    2002-01-01

    The rapidly changing nature of new technologies and techniques in acute health care means it can be difficult keeping pace. Most facilities, large or small, are usually in continuous evaluation of a new technology. Published reviews and professional group guidelines can assist the process of change for continuous renal replacement therapy (CRRT) technologies and techniques. The current techniques and technologies are a mixed application of old and new technologies providing a combination of convective and diffusive solute clearance methods. There are a variety of anticoagulation approaches. New, purpose-built CRRT machines offer many advantages over old technology but their costs can be prohibitive and users do not always meet them with rapid behavioral change. Reading journal publications and texts, scientific meetings, education and training, Internet web site review/participation, quality improvement activities and an accurate local data base are the keys to keeping pace with changes and identifying whether a benefit can be anticipated and demonstrated. Possible changes for the future of techniques and technologies may be in the areas of modified approaches to continuous therapy with tailored approaches for specific patient care settings. Improved membrane characteristics for wider indications and the bio-artificial kidney are emerging along with blood pump and circuit design improvements, with new machine/operator interfaces.

  17. Forecast Combination under Heavy-Tailed Errors

    Directory of Open Access Journals (Sweden)

    Gang Cheng

    2015-11-01

    Full Text Available Forecast combination has been proven to be a very important technique to obtain accurate predictions for various applications in economics, finance, marketing and many other areas. In many applications, forecast errors exhibit heavy-tailed behaviors for various reasons. Unfortunately, to our knowledge, little has been done to obtain reliable forecast combinations for such situations. The familiar forecast combination methods, such as simple average, least squares regression or those based on the variance-covariance of the forecasts, may perform very poorly due to the fact that outliers tend to occur, and they make these methods have unstable weights, leading to un-robust forecasts. To address this problem, in this paper, we propose two nonparametric forecast combination methods. One is specially proposed for the situations in which the forecast errors are strongly believed to have heavy tails that can be modeled by a scaled Student’s t-distribution; the other is designed for relatively more general situations when there is a lack of strong or consistent evidence on the tail behaviors of the forecast errors due to a shortage of data and/or an evolving data-generating process. Adaptive risk bounds of both methods are developed. They show that the resulting combined forecasts yield near optimal mean forecast errors relative to the candidate forecasts. Simulations and a real example demonstrate their superior performance in that they indeed tend to have significantly smaller prediction errors than the previous combination methods in the presence of forecast outliers.

  18. Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

    Science.gov (United States)

    Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  19. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    Directory of Open Access Journals (Sweden)

    Wensheng Dai

    2014-01-01

    Full Text Available Sales forecasting is one of the most important issues in managing information technology (IT chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR, is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA, temporal ICA (tICA, and spatiotemporal ICA (stICA to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  20. General forecasting correcting formula

    OpenAIRE

    Harin, Alexander

    2009-01-01

    A general forecasting correcting formula, as a framework for long-use and standardized forecasts, is created. The formula provides new forecasting resources and new possibilities for expansion of forecasting including economic forecasting into the areas of municipal needs, middle-size and small-size business and, even, to individual forecasting.

  1. General forecasting correcting formula

    OpenAIRE

    2009-01-01

    A general forecasting correcting formula, as a framework for long-use and standardized forecasts, is created. The formula provides new forecasting resources and new possibilities for expansion of forecasting including economic forecasting into the areas of municipal needs, middle-size and small-size business and, even, to individual forecasting.

  2. A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques

    Science.gov (United States)

    Chang, Fi-John; Tsai, Meng-Jung

    2016-04-01

    Accurate multi-step-ahead inflow forecasting during typhoon periods is extremely crucial for real-time reservoir flood control. We propose a spatio-temporal lumping of radar rainfall for modeling inflow forecasts to mitigate time-lag problems and improve forecasting accuracy. Spatial aggregation of radar cells is made based on the sub-catchment partitioning obtained from the Self-Organizing Map (SOM), and then flood forecasting is made by the Adaptive Neuro Fuzzy Inference System (ANFIS) models coupled with a 2-staged Gamma Test (2-GT) procedure that identifies the optimal non-trivial rainfall inputs. The Shihmen Reservoir in northern Taiwan is used as a case study. The results show that the proposed methods can, in general, precisely make 1- to 4-hour-ahead forecasts and the lag time between predicted and observed flood peaks could be mitigated. The constructed ANFIS models with only two fuzzy if-then rules can effectively categorize inputs into two levels (i.e. high and low) and provide an insightful view (perspective) of the rainfall-runoff process, which demonstrate their capability in modeling the complex rainfall-runoff process. In addition, the confidence level of forecasts with acceptable error can reach as high as 97% at horizon t+1 and 77% at horizon t+4, respectively, which evidently promotes model reliability and leads to better decisions on real-time reservoir operation during typhoon events.

  3. Information Forecasting.

    Science.gov (United States)

    Hanneman, Gerhard J.

    Information forecasting provides a means of anticipating future message needs of a society or predicting the necessary types of information that will allow smooth social functioning. Periods of unrest and uncertainty in societies contribute to "societal information overload," whereby an abundance of information channels can create communication…

  4. Emerging Technologies and Techniques for Wide Area Radiological Survey and Remediation

    Energy Technology Data Exchange (ETDEWEB)

    Sutton, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zhao, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-24

    Technologies to survey and decontaminate wide-area contamination and process the subsequent radioactive waste have been developed and implemented following the Chernobyl nuclear power plant release and the breach of a radiological source resulting in contamination in Goiania, Brazil. These civilian examples of radioactive material releases provided some of the first examples of urban radiological remediation. Many emerging technologies have recently been developed and demonstrated in Japan following the release of radioactive cesium isotopes (Cs-134 and Cs-137) from the Fukushima Dai-ichi nuclear power plant in 2011. Information on technologies reported by several Japanese government agencies, such as the Japan Atomic Energy Agency (JAEA), the Ministry of the Environment (MOE) and the National Institute for Environmental Science (NIES), together with academic institutions and industry are summarized and compared to recently developed, deployed and available technologies in the United States. The technologies and techniques presented in this report may be deployed in response to a wide area contamination event in the United States. In some cases, additional research and testing is needed to adequately validate the technology effectiveness over wide areas. Survey techniques can be deployed on the ground or from the air, allowing a range of coverage rates and sensitivities. Survey technologies also include those useful in measuring decontamination progress and mapping contamination. Decontamination technologies and techniques range from non-destructive (e.g., high pressure washing) and minimally destructive (plowing), to fully destructive (surface removal or demolition). Waste minimization techniques can greatly impact the long-term environmental consequences and cost following remediation efforts. Recommendations on technical improvements to address technology gaps are presented together with observations on remediation in Japan.

  5. The impact of information technology on productivity using structural equations technique in Iran Behnoush Company

    Directory of Open Access Journals (Sweden)

    Mina Beig

    2012-08-01

    Full Text Available Information technology plays an important role on increasing productivity in many organizations. The primary objective of the present survey is to study the impact of information technology on productivity and find a positive and significant relationship between these two factors. Structural equations technique and LISREL software are used for analysis of the questionnaires distributed among managers and some employees of Iran Behnoush Company. Organizations try to improve their performance by investment in information technology. However, many of the previous studies indicate insignificance of the impact of information technology on productivity of the organizations. The present survey studies the impact of information technology on organizations' productivity through the collected data from the above company. Results confirm existence of a positive relationship between information technology and productivity.

  6. PRONOSTICANDO EL ÍNDICE ENSO VARIOS PASOS EN ADELANTE MEDIANTE TÉCNICAS DE MODELAMIENTO NO LINEAL FORECASTING ENSO SEVERAL STEPS AHEAD THROUGH NONLINEAR MODELING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Giovanni Salini Calderón

    2010-12-01

    we studied a monthly database corresponding to South Oscillation Index (SOI and between the years 1886 to 2006. It explains how there must manipulated this database whose data possess nonlinear characteristic, which will be used to do forecasts several steps ahead. Two standard tests to this database were applied, the Average Mutual Information (AMI and the False Nearest Neighbours (FNN. The optimal spacing of the information was obtained as well as the number of values backward necessary to predict values towards the future. Then, several models were designed of artificial neural nets (ANN, with different learning rules, function of transfer, elements of process (or neurons in the hidden layer, etc., that allowed to do forecasting of up to 20 steps ahead. The best networks were those that possessed the rules of learning called extDBD and Delta-Rule, and sigmoid as well as hyperbolic tangent as function of transfer. The type of used network was one of feedforward multilayer perceptron and trained by means of backpropagation technique. Networks were proved by one, two hidden layers and without any hidden layer. The best model that was obtained it turned out to be one that consisted with an alone hidden layer.

  7. Numerical Techniques for Ocean Forecasting.

    Science.gov (United States)

    1980-09-30

    inccnsistency in the links, caused by .i logic error in the topology routine, or More usually by storage corruption causej by array bound overflow or...be A 11/54 1’ whereiIk A k if is a vertex ot k, else L ik 0. CVLW is invoked as follows: CALL C’YLU( TIPOS ) IF’TS is a poi ,ter to a set of , var iat...cells contai) in9 each vertex. Wi:thin the limits of roundinq errors , the two inteqrals are zero. TSTCTU is called as shown: CALL TSICTU(IPOS) where

  8. Technology and geomorphology: Are improvements in data collection techniques transforming geomorphic science?

    Science.gov (United States)

    Viles, Heather

    2016-10-01

    In recent years technological developments have revolutionized our ability to collect data in geomorphology. Enhanced data collection not only enables us to provide deeper answers to a wider range of fundamental questions about the Earth's surface, but also encourages us to pose new questions. This paper considers in more detail the relationships between science, technology and the development of geomorphological tools and techniques, reviews the spectrum of tools and techniques now available to geomorphologists, and critically assesses what impact 'new technologies' are having on geomorphology. It focuses on the role of technology in biogeomorphology and weathering research, and how it is advancing theoretical, empirical and applied dimensions of these growing sub-fields of geomorphology. Five areas of important technological development are reviewed: remote sensing, dating, geophysical techniques, field and laboratory based analysis and sensing of physical and chemical characteristics, and field and laboratory based analysis of biological properties. There is good evidence that, taken together, technological developments are revolutionizing geomorphology through opening the doors to better cross-scalar investigations, blurring the boundaries between laboratory, field and computer model, and facilitating cross-disciplinary and democratized research.

  9. A New Technique to Backup and Restore DBMS using XML and .NET Technologies

    CERN Document Server

    Kadry, Seifedine; Kassem, Hussam; Hayek, Hassan

    2011-01-01

    In this paper, we proposed a new technique for backing up and restoring different Database Management Systems (DBMS). The technique is enabling to backup and restore a part of or the whole database using a unified interface using ASP.NET and XML technologies. It presents a Web Solution allowing the administrators to do their jobs from everywhere, locally or remotely. To show the importance of our solution, we have taken two case studies, oracle 11g and SQL Server 2008.

  10. Skillful seasonal forecasts of Arctic sea ice retreat and advance dates in a dynamical forecast system

    Science.gov (United States)

    Sigmond, M.; Reader, M. C.; Flato, G. M.; Merryfield, W. J.; Tivy, A.

    2016-12-01

    The need for skillful seasonal forecasts of Arctic sea ice is rapidly increasing. Technology to perform such forecasts with coupled atmosphere-ocean-sea ice systems has only recently become available, with previous skill evaluations mainly limited to area-integrated quantities. Here we show, based on a large set of retrospective ensemble model forecasts, that a dynamical forecast system produces skillful seasonal forecasts of local sea ice retreat and advance dates - variables that are of great interest to a wide range of end users. Advance dates can generally be skillfully predicted at longer lead times ( 5 months on average) than retreat dates ( 3 months). The skill of retreat date forecasts mainly stems from persistence of initial sea ice anomalies, whereas advance date forecasts benefit from longer time scale and more predictable variability in ocean temperatures. These results suggest that further investments in the development of dynamical seasonal forecast systems may result in significant socioeconomic benefits.

  11. Univariate time series forecasting algorithm validation

    Science.gov (United States)

    Ismail, Suzilah; Zakaria, Rohaiza; Muda, Tuan Zalizam Tuan

    2014-12-01

    Forecasting is a complex process which requires expert tacit knowledge in producing accurate forecast values. This complexity contributes to the gaps between end users and expert. Automating this process by using algorithm can act as a bridge between them. Algorithm is a well-defined rule for solving a problem. In this study a univariate time series forecasting algorithm was developed in JAVA and validated using SPSS and Excel. Two set of simulated data (yearly and non-yearly); several univariate forecasting techniques (i.e. Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) and recent forecasting process (such as data partition, several error measures, recursive evaluation and etc.) were employed. Successfully, the results of the algorithm tally with the results of SPSS and Excel. This algorithm will not just benefit forecaster but also end users that lacking in depth knowledge of forecasting process.

  12. Logical Design of a Decision Support System to Forecast Technology, Prices and Costs for the National Communications System.

    Science.gov (United States)

    1984-09-01

    digital services upon ISDN technology growth can be modeled. The DSS is executed with the impacts as subjective values and are defined as desirable...communications media cost =I’ 2. Number of ISDN trained personnel = ’PI 3. Ccmpetiticn to provide digital services = ’C’ 4. Growth rate of ISDN

  13. Rain gauge network design for flood forecasting using multi-criteria decision analysis and clustering techniques in lower Mahanadi river basin, India

    Directory of Open Access Journals (Sweden)

    Anil Kumar Kar

    2015-09-01

    New hydrological insights for the region: This study establishes different possible key RG networks using Hall’s method, analytical hierarchical process (AHP, self organization map (SOM and hierarchical clustering (HC using the characteristics of each rain gauge occupied Thiessen polygon area. Efficiency of the key networks is tested by artificial neural network (ANN, Fuzzy and NAM rainfall-runoff models. Furthermore, flood forecasting has been carried out using the three most effective RG networks which uses only 7 RGs instead of 14 gauges established in the Kantamal sub-catchment, Mahanadi basin. The Fuzzy logic applied on the key RG network derived using AHP has shown the best result for flood forecasting with efficiency of 82.74% for 1-day lead period. This study demonstrates the design procedure of key RG network for effective flood forecasting particularly when there is difficulty in gathering the information from all RGs.

  14. Applications of Modern Analysis Techniques in Searching back Ancient Art Ceramic Technologies

    Directory of Open Access Journals (Sweden)

    Nguyen Quang Liem

    2011-12-01

    Full Text Available This report highlights the promising applications of modern analysis techniques such as Scanning Electron Microsopy, X-ray fluorescence, X-ray diffraction, Raman scattering spectroscopy, and thermal expansion measurement in searching back the ancient art ceramics technologies.

  15. Just-in-Time Teaching Techniques through Web Technologies for Vocational Students' Reading and Writing Abilities

    Science.gov (United States)

    Chantoem, Rewadee; Rattanavich, Saowalak

    2016-01-01

    This research compares the English language achievements of vocational students, their reading and writing abilities, and their attitudes towards learning English taught with just-in-time teaching techniques through web technologies and conventional methods. The experimental and control groups were formed, a randomized true control group…

  16. The Using of the Teaching Methods and Techniques by Science and Technology Teachers and Class Teachers

    Directory of Open Access Journals (Sweden)

    Tohit Gunesa

    2012-04-01

    Full Text Available The purpose of this study is to determine which teaching strategies, techniques and methods are used by teachers in science and technology classes and also to determine the shortcomings they have. A questionnaire was conducted to a total of 95 teachers, 45 of whom were science and technology teachers and 50 of whom were class teachers, and 33 teachers were interviewed. It was found out that the teachers did not have enough information about teaching strategies, methods and techniques and thus were not able to make a precise distinction between them. It was determined that although the teachers were aware that the most convenient teaching technique is experiment technique, they used direct instruction or question and answer technique more and they sometimes used methods and techniques such as laboratory, trip-observation and drama. It was stated that the teachers were not able to implement teaching methods and techniques in which the students could actively participate due to reasons such as insufficient time, intensive curriculum and overcrowded classes. It was also determined that the teachers who were not able to practice different teaching methods although they knew how useful they were needed in-service training.

  17. Technical and Economic Forecast in Selection of Optimum Biomass and Local Fossil Fuel Application Technology for Thermal Electric Energy Generation

    Directory of Open Access Journals (Sweden)

    I. A. Bokun

    2010-01-01

    Full Text Available The paper provides a technical and economic analysis pertaining to selection of optimum biomass and local fossil fuel application technology for thermal electric energy generation while using a matrix of costs and a method of minimum value. Calculation results give grounds to assert that it is expedient to burn in the boiling layer – 69 % and 31 % of wood pellets and wastes, respectively and 54 % of peat and 46 % of slate stones. A steam and gas unit (SGU can fully operate on peat. Taking into account reorientation on decentralized power supply and increase of small power plants up to 3–5 MW the paper specifies variants of the most efficient technologies for burning biomass and local fossil fuels. 

  18. Forecast analysis on satellites that need de-orbit technologies: future scenarios for passive de-orbit devices

    Science.gov (United States)

    Palla, Chiara; Kingston, Jennifer

    2016-09-01

    Propulsion-based de-orbit is a space-proven technology; however, this strategy can strongly limit operational lifetime, as fuel mass is dedicated to the de-orbiting. In addition previous reliability studies have identified the propulsion subsystem as one of the major contributors driving satellite failures. This issue brings the need to develop affordable de-orbit technologies with a limited reliance on the system level performance of the host satellite, ideally largely passive methods. Passive disposal strategies which take advantage of aerodynamic drag as the de-orbit force are particularly attractive because they are independent of spacecraft propulsion capabilities. This paper investigates the future market for passive de-orbit devices in LEO to aid in defining top-level requirements for the design of such devices. This is performed by considering the compliances of projected future satellites with the Inter Agency Space Debris Coordination Committee de-orbit time, to quantify the number of spacecraft that are compliant or non-compliant with the guidelines and, in this way, determine their need for the previously discussed devices. The study is performed by using the SpaceTrak™ database which provides future launch schedules, and spacecraft information; the de-orbit analysis is carried out by means of simulations with STELA. A case study of a passive strategy is given by the de-orbit mechanism technological demonstrator, which is currently under development at Cranfield University and designed to deploy a drag sail at the end of the ESEO satellite mission.

  19. Technology and Technique Standards for Camera-Acquired Digital Dermatologic Images: A Systematic Review.

    Science.gov (United States)

    Quigley, Elizabeth A; Tokay, Barbara A; Jewell, Sarah T; Marchetti, Michael A; Halpern, Allan C

    2015-08-01

    Photographs are invaluable dermatologic diagnostic, management, research, teaching, and documentation tools. Digital Imaging and Communications in Medicine (DICOM) standards exist for many types of digital medical images, but there are no DICOM standards for camera-acquired dermatologic images to date. To identify and describe existing or proposed technology and technique standards for camera-acquired dermatologic images in the scientific literature. Systematic searches of the PubMed, EMBASE, and Cochrane databases were performed in January 2013 using photography and digital imaging, standardization, and medical specialty and medical illustration search terms and augmented by a gray literature search of 14 websites using Google. Two reviewers independently screened titles of 7371 unique publications, followed by 3 sequential full-text reviews, leading to the selection of 49 publications with the most recent (1985-2013) or detailed description of technology or technique standards related to the acquisition or use of images of skin disease (or related conditions). No universally accepted existing technology or technique standards for camera-based digital images in dermatology were identified. Recommendations are summarized for technology imaging standards, including spatial resolution, color resolution, reproduction (magnification) ratios, postacquisition image processing, color calibration, compression, output, archiving and storage, and security during storage and transmission. Recommendations are also summarized for technique imaging standards, including environmental conditions (lighting, background, and camera position), patient pose and standard view sets, and patient consent, privacy, and confidentiality. Proposed standards for specific-use cases in total body photography, teledermatology, and dermoscopy are described. The literature is replete with descriptions of obtaining photographs of skin disease, but universal imaging standards have not been developed

  20. Forecasting military expenditure

    Directory of Open Access Journals (Sweden)

    Tobias Böhmelt

    2014-05-01

    Full Text Available To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

  1. FORECASTING THE NUMBER OF SPORT TOURISM ARRIVALS IN SOUTHWEST BULGARIA

    Directory of Open Access Journals (Sweden)

    Preslav Mihaylov Dimitrov

    2016-12-01

    Full Text Available This paper presents an application of some forecasting methods concerning sport tourism arrivals in Southwest Bulgaria: linear trend forecasting, double exponential forecasting (Holt’s method, triple exponential forecasting (the Holt-Winters Method, and the ARIMA method. A specially designed model for estimating the weight coefficient needed for determining the size of the sport tourism’s sector in the time series of the available data and in the forecast values is presented. In order to test the forecasting methods and produce forecasts up to the year 2030, a time series and past period predictions have been constructed based on statistical records since 1964. Several major problems in the application of the exponential smoothing methods for the purpose of the long-run forecasting and the needs of the sport tourism subsector of Bulgaria tourism industry are addressed. These problems include (a finding a suitable general indicator, (b calculating short-term and long-term forecasts, (c comparing the results of the forecast techniques on the basis of the errors in the forecasts, (d estimating the size of the sport tourism in Southwest Bulgaria in certain terms so that the forecast(s of the above-mentioned general indicator could be particularized especially for examined sub-sector and region. The results from the different forecasting methods and techniques are presented and conclusions are drawn regarding the reliability of the forecasts.

  2. Forecasting Electrical Load Using a Multi-time-scale Approach

    OpenAIRE

    RINGWOOD John; Murray, F.T.

    1999-01-01

    This paper describes the application of a multi-time-scale technique to the modelling and forecasting of short-term electrical load. The multi-time-scale technique is based on adjusting the underlying short sampling period forecast time series with specific target points and possible aggregated demand. This allows not only improvement of the short sampling period forecast, but also focuses on weighting the accuracy of the forecast at certain critical points e.g. the ov...

  3. Research on the development of green chemistry technology assessment techniques: a material reutilization case

    Science.gov (United States)

    Hong, Seokpyo; Ahn, Kilsoo; Kim, Sungjune; Gong, Sungyong

    2015-01-01

    Objectives This study presents a methodology that enables a quantitative assessment of green chemistry technologies. Methods The study carries out a quantitative evaluation of a particular case of material reutilization by calculating the level of “greenness” i.e., the level of compliance with the principles of green chemistry that was achieved by implementing a green chemistry technology. Results The results indicate that the greenness level was enhanced by 42% compared to the pre-improvement level, thus demonstrating the economic feasibility of green chemistry. Conclusions The assessment technique established in this study will serve as a useful reference for setting the direction of industry-level and government-level technological R&D and for evaluating newly developed technologies, which can greatly contribute toward gaining a competitive advantage in the global market. PMID:26206363

  4. Research on the development of green chemistry technology assessment techniques: a material reutilization case.

    Science.gov (United States)

    Hong, Seokpyo; Ahn, Kilsoo; Kim, Sungjune; Gong, Sungyong

    2015-01-01

    This study presents a methodology that enables a quantitative assessment of green chemistry technologies. The study carries out a quantitative evaluation of a particular case of material reutilization by calculating the level of "greenness" i.e., the level of compliance with the principles of green chemistry that was achieved by implementing a green chemistry technology. The results indicate that the greenness level was enhanced by 42% compared to the pre-improvement level, thus demonstrating the economic feasibility of green chemistry. The assessment technique established in this study will serve as a useful reference for setting the direction of industry-level and government-level technological R&D and for evaluating newly developed technologies, which can greatly contribute toward gaining a competitive advantage in the global market.

  5. Factor Model Forecasts of Exchange Rates

    OpenAIRE

    Charles Engel; Nelson C. Mark; Kenneth D. West

    2012-01-01

    We construct factors from a cross section of exchange rates and use the idiosyncratic deviations from the factors to forecast. In a stylized data generating process, we show that such forecasts can be effective even if there is essentially no serial correlation in the univariate exchange rate processes. We apply the technique to a panel of bilateral U.S. dollar rates against 17 OECD countries. We forecast using factors, and using factors combined with any of fundamentals suggested by Taylor r...

  6. Landscaping climate change: a mapping technique for understanding science and technology debates on the world wide web

    NARCIS (Netherlands)

    Rogers, R.; Marres, N.

    2000-01-01

    New World Wide Web (web) mapping techniques may inform and ultimately facilitate meaningful participation in current science and technology debates. The technique described here "landscapes" a debate by displaying key "webby" relationships between organizations. "Debate-scaping" plots two organizati

  7. Landscaping climate change: a mapping technique for understanding science and technology debates on the world wide web

    NARCIS (Netherlands)

    Rogers, R.; Marres, N.

    2000-01-01

    New World Wide Web (web) mapping techniques may inform and ultimately facilitate meaningful participation in current science and technology debates. The technique described here "landscapes" a debate by displaying key "webby" relationships between organizations. "Debate-scaping" plots two organizati

  8. Landscaping climate change: a mapping technique for understanding science and technology debates on the world wide web

    NARCIS (Netherlands)

    Rogers, R.; Marres, N.

    2000-01-01

    New World Wide Web (web) mapping techniques may inform and ultimately facilitate meaningful participation in current science and technology debates. The technique described here "landscapes" a debate by displaying key "webby" relationships between organizations. "Debate-scaping" plots two

  9. Methods and technologies for surveying and forecasting the rice stem borers%水稻钻蛀性螟虫田间调查及测报技术

    Institute of Scientific and Technical Information of China (English)

    陆明星; 陆自强; 杜予州

    2014-01-01

    For a long time, the rice stem borers are main insect pest in rice. With the change of rice cultivation and climate change, the populations of the rice stem borers increase gradually, which damage the rice yield more and more seriously in recent years. Therefore, it’s very meaningful for the integrated management of the rice stem borers to investigate the dynamics scientifically and forecast accurately their trends. According to biological characteristics of Sesamia inferens (Walker), Chilo suppressalis (Walker), Scirpophaga incertulas (Walker), the surveying methods of these borers in the field were summarized. And three forecasting methods of occurrence stage were demonstrated. Moreover, some attentions during the survey were discussed. In conclusion, these methods and technologies will provide a strong foundation for the integrated management of the rice stem borers.%长期以来,水稻钻蛀性螟虫都是我国水稻上的重要害虫。近年来,随着水稻栽培制度的变更及全球性气候的变化,种群数量逐渐回升,为害日趋严重。因此,科学的调查方法和准确的预测预报,对该类害虫的综合治理具有重要意义。本文根据大螟Sesamia inferens(Walker)、二化螟Chilo suppressalis(Walker)和三化螟Scirpophaga incertulas(Walker)的生物学特性,总结了这3种水稻钻蛀性螟虫的田间调查方法;阐述了它们的发生期预测方法;探讨了在调查取样过程中的注意事项,以期为我国水稻钻蛀性螟虫的综合防治提供可靠的数据支撑。

  10. kwmc Terminal Aerodrome Forecast

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. khib Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. khum Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. pakt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kmci Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. krwl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kpsp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. kcmi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kbwi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...