WorldWideScience

Sample records for platform construction forecasts

  1. Demand forecasting and information platform in tourism

    Directory of Open Access Journals (Sweden)

    Li Yue

    2017-05-01

    Full Text Available Information asymmetry and the bullwhip effect have been serious problems in the tourism supply chain. Based on platform theory, this paper established a mathematical model to explore the inner mechanism of a platform’s influence on stakeholders’ ability to forecast demand in tourism. Results showed that the variance of stakeholders’ demand predictions with a platform was smaller than the variance without a platform, which meant that a platform would improve predictions of demand for stakeholders. The higher information-processing ability of the platform also had other effects on demand forecasting. Research on the inner logic of the platform’s influence on stakeholders has important theoretical and realistic value. This area is worthy of further study.

  2. Construction Safety Forecast for ITER

    Energy Technology Data Exchange (ETDEWEB)

    cadwallader, lee charles

    2006-11-01

    The International Thermonuclear Experimental Reactor (ITER) project is poised to begin its construction activity. This paper gives an estimate of construction safety as if the experiment was being built in the United States. This estimate of construction injuries and potential fatalities serves as a useful forecast of what can be expected for construction of such a major facility in any country. These data should be considered by the ITER International Team as it plans for safety during the construction phase. Based on average U.S. construction rates, ITER may expect a lost workday case rate of < 4.0 and a fatality count of 0.5 to 0.9 persons per year.

  3. Utilizing platforms in industrialized construction

    DEFF Research Database (Denmark)

    Bonev, Martin; Wörösch, Michael; Hvam, Lars

    2015-01-01

    platform strategies, this researchhighlights key aspects of adapting platform-based developed theory to industrialised construction.Building projects use different layers of product, process and logistics platforms to form the right cost– value ratio for the target market application, while modelling...

  4. Forecasting Canadian nuclear power station construction costs

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions. (author)

  5. Construction feasibility of OTEC platforms. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Brewer, J H; Harwood, P; Solberg, K; Fjeld, S

    1978-12-01

    This study provides an evaluation of the feasibility of constructing either steel or concrete OTEC platforms of both spar and ship shape configurations for a range of platform sizes with respect to existing, developed shipyard or fabrication yard facilities that are currently active in marine vessel construction within the US. This brief study is quite broad in scope. Many parameters, including plant size; vessel type, size, configuration, and dimensions; position of heat exchangers; existing construction facility size, geographic location, and potential for modification; and, availability of undeveloped deep water construction sites affect the conclusions drawn. Nevertheless, the conclusions should remain valid and not change significantly, unless there are major changes in either vessel size or US construction capabilities. The various concepts are ranked in order of their feasibility and practicality of construction in existing or modified existing facilities and new facilities.

  6. 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

    effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.

  7. The construction of enterprise content management platform

    International Nuclear Information System (INIS)

    Liu Diyong

    2010-01-01

    The paper introduces the content management platform development background and the construction mode of Sanmen Nuclear Power Co., Ltd. It also proposes the system design architecture, especially focuses on the implementation of the project, the key technical issues and the project management experience. In addition, it describes how to classify, manage and use the unformatted information, digital assets and documents. (author)

  8. Canadian nuclear power plant construction cost forecast and analysis

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequence of the decision as possible. This understanding must be provided by the evaluation of the situation to take place in the future. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A data base is built and indexes are prepared. Based on these indexes an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of forty years are generated and applications of alternative scenario forecasts and range forecasts to uncertainty assessment are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the very first ever done for Canadian NGS constructions

  9. The Educational Platform: Constructing Conceptual Frameworks.

    Science.gov (United States)

    Peca, Kathy; Isham, Mark

    2001-01-01

    The education faculty at Eastern New Mexico University used educational platforms as a means of developing the unit's conceptual framework. Faculty members developed personal platforms, then synthesized them into one curricular area platform. The resultant unit educational platform became the basis for the unit's conceptual framework, which…

  10. Forecasting manpower requirements for nuclear power plant construction

    International Nuclear Information System (INIS)

    Seltzer, N.; Schriver, W.R.

    1978-01-01

    This paper presents both the methodology and results of a segment of a comprehensive construction manpower demand forecasting system aimed at forecasting virtually all construction manpower requirements in the United States of America. The part of the system dealing with the demand for construction workers needed to build nuclear powered electricity generating plants is discussed here. The object of the system is to forecast manpower construction needs for each of 29 construction crafts on a monthly basis in each of 10 geographical regions of the United States. The method used is to establish profiles of the types of workers and time phasing required in the past. Profiling was done for different types of plants, different capacity classes, and different geographical locations. An appropriate worker profile matrix cannot simply be multiplied by the capacity of the proposed plant if the number of man-hours required per kilowatt of generating capacity is not constant. The value of this latter variable has changed considerably recently - presumably because of an increased awareness of environmental and safety considerations. Econometric techniques are used to forecast values for man-hours per kilowatt which are then multiplied by projected new capacity to be put in place. The resulting total man-hour requirement is then allocated over time and by craft through use of a worker profile matrix. The summary results indicate that 20 percent increases in man-hours required per kilowatt of capacity can be expected between 1977 and 1981. Total construction labour demand will rise from 65,700 work-years in 1977 to nearly 96,600 work-years in 1981. Forecasts of the actual number of different types of workers to be demanded in each month and in each region are available from the system. (author)

  11. Optical microassembly platform for constructing reconfigurable microenvironment for biomedical studies

    DEFF Research Database (Denmark)

    Rodrigo, Peter John; Kelemen, Lóránd; Palima, Darwin

    2009-01-01

    Cellular development is highly influenced by the surrounding microenvironment. We propose user-reconfigurable microenvironments and bio-compatible scaffolds as an approach for understanding cellular development processes. We demonstrate a model platform for constructing versatile microenvironment...

  12. Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

    Science.gov (United States)

    Li, D.; Fang, N. Z.

    2017-12-01

    Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.

  13. LHC Civil Engineering Construction Contracts Cost Monitoring and Budget Forecasting

    CERN Document Server

    Skelton, K

    2000-01-01

    The Civil Engineering project for the LHC is estimated at 350 MCHF, of which about 316 MCHF is for the construction contracts. These contracts are based on a system of remeasurement whereby the consultant estimates the quantities required for the construction of each structure and the contractor commits himself to the unit price, which define the initial tender price. There are many factors that affect the final price for these contracts, from increases or decreases in quantities of the estimated amounts in the original bill of quantities to variations to the contract. This paper will look at how these factors change costs at the individual level of a structure to the overall costs of the contract. It will look at how the Civil Engineering Group monitors these changes to calculate cash flows and final costs and how this information is used as a basis for budget forecasts.

  14. Construction of the migration flows forecasting into Russian regions

    Directory of Open Access Journals (Sweden)

    Aleksandr Aleksandrovich Tarasyev

    2013-06-01

    Full Text Available This paper presents a dynamic model that can predict the dynamics of migration flows between source countries and host regions, as well as the dynamics of wage levels there. The model is constructed within the framework of neoclassical economics and human capital theory in continuous time. Thanks to liberalization of migration policy in Russia in 2007, the model could be successfully employed to Russian regions and the Commonwealth of Independent States (CIS, which have visa-free entry regulations with the Russian Federation. Employing the model on statistical data, we forecast the number and origin composition of foreign labor force from the CIS into Russian regions for 2010-2016. The purpose of our further research is to classify migrants by skills

  15. Constructing collaboration and management platform with spring+ hibernate

    International Nuclear Information System (INIS)

    Zhang Hongmei; Ou Ge; Nie Jianyin; Song Liming; Chen Gang

    2007-01-01

    HCMP is the platform of collaboration and management for HXMT. The documents of HXMT project are the main context of HCMP. Besides the users of HXMT project, HCMP also serves other users. HCMP adopts the hierarchy Web structure to implement context release, documents approval, project management and portal website. HCMP provides the support of informatlization and standardization for HXMT project. This paper adopts Spring + Hibernate technique to construct the J2EE architecture, based on which HCMP is implemented. (authors)

  16. Multi-platform operational validation of the Western Mediterranean SOCIB forecasting system

    Science.gov (United States)

    Juza, Mélanie; Mourre, Baptiste; Renault, Lionel; Tintoré, Joaquin

    2014-05-01

    The development of science-based ocean forecasting systems at global, regional, and local scales can support a better management of the marine environment (maritime security, environmental and resources protection, maritime and commercial operations, tourism, ...). In this context, SOCIB (the Balearic Islands Coastal Observing and Forecasting System, www.socib.es) has developed an operational ocean forecasting system in the Western Mediterranean Sea (WMOP). WMOP uses a regional configuration of the Regional Ocean Modelling System (ROMS, Shchepetkin and McWilliams, 2005) nested in the larger scale Mediterranean Forecasting System (MFS) with a spatial resolution of 1.5-2km. WMOP aims at reproducing both the basin-scale ocean circulation and the mesoscale variability which is known to play a crucial role due to its strong interaction with the large scale circulation in this region. An operational validation system has been developed to systematically assess the model outputs at daily, monthly and seasonal time scales. Multi-platform observations are used for this validation, including satellite products (Sea Surface Temperature, Sea Level Anomaly), in situ measurements (from gliders, Argo floats, drifters and fixed moorings) and High-Frequency radar data. The validation procedures allow to monitor and certify the general realism of the daily production of the ocean forecasting system before its distribution to users. Additionally, different indicators (Sea Surface Temperature and Salinity, Eddy Kinetic Energy, Mixed Layer Depth, Heat Content, transports in key sections) are computed every day both at the basin-scale and in several sub-regions (Alboran Sea, Balearic Sea, Gulf of Lion). The daily forecasts, validation diagnostics and indicators from the operational model over the last months are available at www.socib.es.

  17. Application and Mechanics Analysis of Multi-Function Construction Platforms in Prefabricated-Concrete Construction

    Science.gov (United States)

    Wang, Meihua; Li, Rongshuai; Zhang, Wenze

    2017-11-01

    Multi-function construction platforms (MCPs) as an “old construction technology, new application” of the building facade construction equipment, its efforts to reduce labour intensity, improve labour productivity, ensure construction safety, shorten the duration of construction and other aspects of the effect are significant. In this study, the functional analysis of the multi-function construction platforms is carried out in the construction of the assembly building. Based on the general finite element software ANSYS, the static calculation and dynamic characteristics analysis of the MCPs structure are analysed, the simplified finite element model is constructed, and the selection of the unit, the processing and solution of boundary are under discussion and research. The maximum deformation value, the maximum stress value and the structural dynamic characteristic model are obtained. The dangerous parts of the platform structure are analysed, too. Multiple types of MCPs under engineering construction conditions are calculated, so as to put forward the rationalization suggestions for engineering application of the MCPs.

  18. Model-free aftershock forecasts constructed from similar sequences in the past

    Science.gov (United States)

    van der Elst, N.; Page, M. T.

    2017-12-01

    The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity

  19. Construction cost forecast model : model documentation and technical notes.

    Science.gov (United States)

    2013-05-01

    Construction cost indices are generally estimated with Laspeyres, Paasche, or Fisher indices that allow changes : in the quantities of construction bid items, as well as changes in price to change the cost indices of those items. : These cost indices...

  20. Forecasting Construction Cost Index based on visibility graph: A network approach

    Science.gov (United States)

    Zhang, Rong; Ashuri, Baabak; Shyr, Yu; Deng, Yong

    2018-03-01

    Engineering News-Record (ENR), a professional magazine in the field of global construction engineering, publishes Construction Cost Index (CCI) every month. Cost estimators and contractors assess projects, arrange budgets and prepare bids by forecasting CCI. However, fluctuations and uncertainties of CCI cause irrational estimations now and then. This paper aims at achieving more accurate predictions of CCI based on a network approach in which time series is firstly converted into a visibility graph and future values are forecasted relied on link prediction. According to the experimental results, the proposed method shows satisfactory performance since the error measures are acceptable. Compared with other methods, the proposed method is easier to implement and is able to forecast CCI with less errors. It is convinced that the proposed method is efficient to provide considerably accurate CCI predictions, which will make contributions to the construction engineering by assisting individuals and organizations in reducing costs and making project schedules.

  1. Forecasting of construction and demolition waste in Brazil.

    Science.gov (United States)

    Paz, Diogo Hf; Lafayette, Kalinny Pv

    2016-08-01

    The objective of this article is to develop a computerised tool (software) that facilitates the analysis of strategies for waste management on construction sites through the use of indicators of construction and demolition waste generation. The development involved the following steps: knowledge acquisition, structuring the system, coding and system evaluation. The step of knowledge acquisition aims to provide subsidies for the representation of them through models. In the step of structuring the system, it was presented the structuring and formalisation of knowledge for the development of the system, and has two stages: the construction of the conceptual model and the subsequent instantiation of the model. The coding system aims to implement (code) the conceptual model developed in a model played by computer (digital). The results showed that the system is very useful and applicable in construction sites, helping to improve the quality of waste management, and creating a database that will support new research. © The Author(s) 2016.

  2. The S-curve for forecasting waste generation in construction projects.

    Science.gov (United States)

    Lu, Weisheng; Peng, Yi; Chen, Xi; Skitmore, Martin; Zhang, Xiaoling

    2016-10-01

    Forecasting construction waste generation is the yardstick of any effort by policy-makers, researchers, practitioners and the like to manage construction and demolition (C&D) waste. This paper develops and tests an S-curve model to indicate accumulative waste generation as a project progresses. Using 37,148 disposal records generated from 138 building projects in Hong Kong in four consecutive years from January 2011 to June 2015, a wide range of potential S-curve models are examined, and as a result, the formula that best fits the historical data set is found. The S-curve model is then further linked to project characteristics using artificial neural networks (ANNs) so that it can be used to forecast waste generation in future construction projects. It was found that, among the S-curve models, cumulative logistic distribution is the best formula to fit the historical data. Meanwhile, contract sum, location, public-private nature, and duration can be used to forecast construction waste generation. The study provides contractors with not only an S-curve model to forecast overall waste generation before a project commences, but also with a detailed baseline to benchmark and manage waste during the course of construction. The major contribution of this paper is to the body of knowledge in the field of construction waste generation forecasting. By examining it with an S-curve model, the study elevates construction waste management to a level equivalent to project cost management where the model has already been readily accepted as a standard tool. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Constructing regional advantage: platform policies based on related variety and differentiated knowledge bases.

    NARCIS (Netherlands)

    Asheim, B.T.; Boschma, R.A.; Cooke, P.

    2011-01-01

    Constructing regional advantage: platform policies based on related variety and differentiated knowledge bases, Regional Studies. This paper presents a regional innovation policy model based on the idea of constructing regional advantage. This policy model brings together concepts like related

  4. The Construction of Platform Imperialism in the Globalization Era

    Directory of Open Access Journals (Sweden)

    Dal Yong Jin

    2013-01-01

    Full Text Available In the early 21st century, platforms, known as digital media intermediaries, have greatly influenced people’s daily lives. Due to the importance of platforms for the digital economy and culture, including intellectual property and participatory culture, several countries have developed their own social network sites and Web portals. Nonetheless, a handful of Western countries, primarily the U.S., have dominated the global platform market and society. This paper aims to historicize the concept of imperialism in the globalized 21st century. It investigates whether the recent growth of American-based platforms has resulted in a change to the fundamental idea of the imperialism thesis by analyzing the evolutionary nature of imperialism towards platform imperialism. It then addresses whether we are experiencing a new notion of imperialism by mapping out several core characteristics that define platform imperialism, including the swift growth and global dominance of SNSs and smartphones. It pays close attention to the capitalization of platforms and their global expansion, including the major role of intellectual property rights as the most significant form of capital accumulation in the digital age. It eventually endeavors to make a contribution to the platform imperialism discourse as a form of new imperialism, focusing on the nexus of great powers.

  5. FORECAST OF INFLUENCING THE UNDERGROUND COMPLEX CONSTRUCTION ON A CONTEXT AREA

    OpenAIRE

    Orekhov Vyacheslav Valentinovich; Alekseev German Valer’evich

    2017-01-01

    The present paper is concerned with the method, research objective and the results of numerical simulation of change of stress-strain behaviour of soil masses when constructing underground complex. In order to get consistent results of forecast, all major factors affecting the results of design studies have been taken into account, including spatial performance of soil mass, enclosure structure and an adjacent context area, phasing of construction, site investigation, initial stress-strain be...

  6. Effects of Organisational Characteristics on Contractors’ Construction Cash Flow Forecasting Capabilities

    Directory of Open Access Journals (Sweden)

    Muhammad Abdullahi

    2017-01-01

    Full Text Available Inadequate cash resources resulting from poor cash flows have been among the fundamental causes of construction project failures. Despite the panoply of cash flow forecasting (CFF tools, the cash flow performance of many construction firms have been reported to be poor due weak Cash flow forecasting (CFF process capabilities influenced by a couple of organisational characteristics. Although these organisational characteristics have been reported to significantly influence firms’ CFF process capabilities, the underlying mechanisms of how these organisational features and characteristics exhibit their specific influences on the cash flow forecasting capabilities of construction firms still remains underexplored. Therefore, this study aims at empirically exploring the influence of some organisation characteristics on the CFF process capabilities of construction firms. Best practices in CFF identified from the Royal Institute of Chartered Surveyors (RICS Cash Flow Forecasting (CFF guide were used to develop an assessment criteria used to assess the CFF capabilities of construction firms. The assessment was conducted through a questionnaire survey involving contracting organisations involved in both building and civil engineering works in Nigeria. The key best practices in CFF were ranked based on arithmetic mean value scores and averages were also determined for each of the four CFF components assessed (Knowledge and understanding CFF concepts and principles, Practical application, Practical considerations, and other Managerial issues. Hierarchical regression analysis was then used to examine the relationships between contractors’’ CFF process capabilities and some organisational characteristics. Results of the study reveals that organisational characteristics are strongly associated to firms’ abilities to prudently manage cash flows. The results of this study could serve as a basis for the strategic planning and improvement of Cash Flow

  7. FORECAST - A cloud-based personalized intelligent virtual coaching platform for the well-being of cancer patients.

    Science.gov (United States)

    Kyriazakos, Sofoklis; Valentini, Vincenzo; Cesario, Alfredo; Zachariae, Robert

    2018-01-01

    Well-being of cancer patients and survivors is a challenge worldwide, considering the often chronic nature of the disease. Today, a large number of initiatives, products and services are available that aim to provide strategies to face the challenge of well-being in cancer patients; nevertheless the proposed solutions are often non-sustainable, costly, unavailable to those in need, and less well-received by patients. These challenges were considered in designing FORECAST, a cloud-based personalized intelligent virtual coaching platform for improving the well-being of cancer patients. Personalized coaching for cancer patients focuses on physical, mental, and emotional concerns, which FORECAST is able to identify. Cancer patients can benefit from coaching that addresses their emotional problems, helps them focus on their goals, and supports them in coping with their disease-related stressors. Personalized coaching in FORECAST offers support, encouragement, motivation, confidence, and hope and is a valuable tool for the wellbeing of a patient.

  8. Construction of pipelines on marshlands during summer months with the aid of gang assembly platforms

    Energy Technology Data Exchange (ETDEWEB)

    Kovalev, E P; Girshovich, I I

    1979-05-01

    Because the massive size of conventional pipeline-construction equipment limits its use in swampy areas to winter months, the USSR's SKB Gazstroimashina developed a new system to allow year-round construction activity. The equipment consists of five mobile platforms arranged in series along the pipeline to spread out the load for a lower specific ground pressure than exerted by conventional equipment. Platforms perform the successive functions of emplacement of the pipe lengths, end preparation, welding, cleanup, and insulation. So far, two sets of gang-assembly platforms have been built and are being field-tested.

  9. Forecasting Construction Tender Price Index in Ghana using Autoregressive Integrated Moving Average with Exogenous Variables Model

    Directory of Open Access Journals (Sweden)

    Ernest Kissi

    2018-03-01

    Full Text Available Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.

  10. PanEurasian Experiment (PEEX): Modelling Platform for Earth System Observations and Forecasting

    Science.gov (United States)

    Baklanov, Alexander; Mahura, Alexander; Penenko, Vladimir; Zilitinkevich, Sergej; Kulmala, Markku

    2014-05-01

    As the part of the PEEX initiative, for the purpose of supporting the PEEX observational system and answering on the PEEX scientific questions, a hierarchy/ framework of modern multi-scale models for different elements of the Earth System integrated with the observation system is needed. One of the acute topics in the international debate on land-atmosphere interactions in relation to global change is the Earth System Modeling (ESM). The question is whether the ESM components actually represent how the Earth is functioning. The ESMs consist of equations describing the processes in the atmosphere, ocean, cryosphere, terrestrial and marine biosphere. ESMs are the best tools for analyzing the effect of different environmental changes on future climate or for studying the role of whole processes in the Earth System. These types of analysis and prediction of the future change are especially important in the Arctic latitudes, where climate change is proceeding fastest and where near-surface warming has been about twice the global average during the recent decades. The processes, and hence parameterization, in ESMs are still based on insufficient knowledge of physical, chemical and biological mechanisms involved in the climate system and the resolution of known processes is insufficient. Global scale modeling of land-atmosphere-ocean interactions using ESMs provides a way to explore the influence of spatial and temporal variation in the activities of land system and on climate. There is a lack, however, ways to forward a necessary process understanding effectively to ESMs and to link all this to the decision-making process. Arctic-boreal geographical domain plays significant role in terms of green-house gases and anthropogenic emissions and as an aerosol source area in the Earth System. The PEEX Modelling Platform (PEEX-MP) is characterized by: • An ensemble approach with the integration of modelling results from different models/ countries etc.; • A hierarchy of

  11. FORECAST – A cloud-based personalized intelligent virtual coaching platform for the well-being of cancer patients

    Directory of Open Access Journals (Sweden)

    Sofoklis Kyriazakos

    2018-01-01

    Full Text Available Well-being of cancer patients and survivors is a challenge worldwide, considering the often chronic nature of the disease. Today, a large number of initiatives, products and services are available that aim to provide strategies to face the challenge of well-being in cancer patients; nevertheless the proposed solutions are often non-sustainable, costly, unavailable to those in need, and less well-received by patients. These challenges were considered in designing FORECAST, a cloud-based personalized intelligent virtual coaching platform for improving the well-being of cancer patients. Personalized coaching for cancer patients focuses on physical, mental, and emotional concerns, which FORECAST is able to identify. Cancer patients can benefit from coaching that addresses their emotional problems, helps them focus on their goals, and supports them in coping with their disease-related stressors. Personalized coaching in FORECAST offers support, encouragement, motivation, confidence, and hope and is a valuable tool for the wellbeing of a patient.

  12. EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

    Science.gov (United States)

    MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

    2017-12-01

    Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

  13. Accounting for the inaccuracies in demand forecasts and construction cost estimations in transport project evaluation

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2014-01-01

    For decades researchers have claimedthat particularly demand forecasts and construction cost estimations are assigned with/affected by a large degree of uncertainty. Massively, articles,research documents and reports agree that there exists a tendencytowards underestimating the costs...... in demand and cost estimations and hence the evaluation of transport infrastructure projects. Currently, research within this area is scarce and scattered with no commonagreement on how to embed and operationalise the huge amount of empiricaldata that exist within the frame of Optimism Bias. Therefore...... convertingdeterministic benefit-cost ratios (BCRs) into stochasticinterval results. A new data collection (2009–2013) forms the empirical basis for any risk simulation embeddedwithin the so-calledUP database (UNITE project database),revealing the inaccuracy of both construction costs and demandforecasts. Accordingly...

  14. FORECAST OF INFLUENCING THE UNDERGROUND COMPLEX CONSTRUCTION ON A CONTEXT AREA

    Directory of Open Access Journals (Sweden)

    Orekhov Vyacheslav Valentinovich

    2017-08-01

    Full Text Available The present paper is concerned with the method, research objective and the results of numerical simulation of change of stress-strain behaviour of soil masses when constructing underground complex. In order to get consistent results of forecast, all major factors affecting the results of design studies have been taken into account, including spatial performance of soil mass, enclosure structure and an adjacent context area, phasing of construction, site investigation, initial stress-strain behaviour of soil mass and elasto-plastic strain of soils. The authors give assessment of influence of pit excavation and subsequent construction on a context adjacent area and construction of an underground railroad. Results of the studies show that the proposed construction of an underground complex on the Tverskaya Zastava square would not have a significant impact on the surrounding buildings and subway structures. The spreading of the subsidence crater around the excavating pit is projected by 30...80 m. The ground lift directly below the bottom of the excavation pit in the places of metro stations and transport tunnels will be about 0.1 cm.

  15. Research on website construction based on website group platform of Chengdu sport institution

    Science.gov (United States)

    Hu, Zunyu

    2018-04-01

    This paper describes the necessity of website construction based on the website group of Chengdu sport institute, and discusses the technical features of the website group, Based on the website group platform architecture, the key technologies such as Web Service, AJAX, RSS and other key technologies are used to realize the construction of the website. Based on the website group platform architecture of the site, it effectively solves the information isolated island between the sites, and realizes the information sharing and resource integration. It is also more convenient that site and other sites have composed of site group integrated operation and maintenance.

  16. Constructing a multi-sided business model for a smart horizontal IoT service platform

    NARCIS (Netherlands)

    Berkers, F.; Roelands, M.; Bomhof, F.; Bachet, T.; Van Rijn, M.; Koers, W.

    2013-01-01

    In order to realize a viable business ecosystem in the Internet of Things (IoT), we investigated how a smart horizontal IoT service platform can bring value and economies of scale to all required ecosystem stakeholders. By means of an example application domain case, this paper constructs a

  17. Accessing and constructing driving data to develop fuel consumption forecast model

    Science.gov (United States)

    Yamashita, Rei-Jo; Yao, Hsiu-Hsen; Hung, Shih-Wei; Hackman, Acquah

    2018-02-01

    In this study, we develop a forecasting models, to estimate fuel consumption based on the driving behavior, in which vehicles and routes are known. First, the driving data are collected via telematics and OBDII. Then, the driving fuel consumption formula is used to calculate the estimate fuel consumption, and driving behavior indicators are generated for analysis. Based on statistical analysis method, the driving fuel consumption forecasting model is constructed. Some field experiment results were done in this study to generate hundreds of driving behavior indicators. Based on data mining approach, the Pearson coefficient correlation analysis is used to filter highly fuel consumption related DBIs. Only highly correlated DBI will be used in the model. These DBIs are divided into four classes: speed class, acceleration class, Left/Right/U-turn class and the other category. We then use K-means cluster analysis to group to the driver class and the route class. Finally, more than 12 aggregate models are generated by those highly correlated DBIs, using the neural network model and regression analysis. Based on Mean Absolute Percentage Error (MAPE) to evaluate from the developed AMs. The best MAPE values among these AM is below 5%.

  18. Paradigm change in ocean studies: multi-platform observing and forecasting integrated approach in response to science and society needs

    Science.gov (United States)

    Tintoré, Joaquín

    2017-04-01

    The last 20 years of ocean research have allowed a description of the state of the large-scale ocean circulation. However, it is also well known that there is no such thing as an ocean state and that the ocean varies a wide range of spatial and temporal scales. More recently, in the last 10 years, new monitoring and modelling technologies have emerged allowing quasi real time observation and forecasting of the ocean at regional and local scales. Theses new technologies are key components of recent observing & forecasting systems being progressively implemented in many regional seas and coastal areas of the world oceans. As a result, new capabilities to characterise the ocean state and more important, its variability at small spatial and temporal scales, exists today in many cases in quasi-real time. Examples of relevance for society can be cited, among others our capabilities to detect and understand long-term climatic changes and also our capabilities to better constrain our forecasting capabilities of the coastal ocean circulation at temporal scales from sub-seasonal to inter-annual and spatial from regional to meso and submesoscale. The Mediterranean Sea is a well-known laboratory ocean where meso and submesoscale features can be ideally observed and studied as shown by the key contributions from projects such as Perseus, CMEMS, Jericonext, among others. The challenge for the next 10 years is the integration of theses technologies and multiplatform observing and forecasting systems to (a) monitor the variability at small scales mesoscale/weeks) in order (b) to resolve the sub-basin/seasonal and inter-annual variability and by this (c) establish the decadal variability, understand the associated biases and correct them. In other words, the new observing systems now allow a major change in our focus of ocean observation, now from small to large scales. Recent studies from SOCIB -www.socib.es- have shown the importance of this new small to large-scale multi-platform

  19. CONSTRUCTION OF STATISTICAL MODEL THE OVERALL POPULATION OF THE RUSSIAN FEDERATION ON THE BASIS OF RETROSPECTIVE FORECAST

    Directory of Open Access Journals (Sweden)

    Ol’ga Sergeevna Kochegarova

    2017-06-01

    Full Text Available The article considers the retrospective forecast of the total population of the Russian Federation for the period 2001–2017. comparative analysis of the actual values of the total population of the Russian Federation on 20.03.2017 according to the Federal state statistics service of the Russian Federation received the forecast value. Model selection forecasting was carried out by the method of selection of growth curves on the basis of correlation and regression analysis and least squares method. A quality selection of the regression equation was determined with the least error of approximation of time series levels. Analysis of the significance of the selected regression equation by statistical methods allows to make a conclusion about the right choice of models and the possibility of its use for population estimates. Purpose: to estimate the significance of selected regression equations for the forecast of the population. Methodology in article: the fitting of growth curves on the basis of correlation and regression analysis and least squares method. Results: received confirmation of the effectiveness of the constructed model for forecasts of demographic processes. Practical implications: the obtained results should be used when building forecasts of demographic processes.

  20. An overview of the construction of emergency and pre-hospital first aid platform

    Directory of Open Access Journals (Sweden)

    Song Chen

    2018-01-01

    Full Text Available To further improve the ability of pre-hospital and in-hospital collaborative treatment, strengthen emergency multidisciplinary cooperation and construct a scientific, rational and efficient emergency system, under the support of former chairman Yu Xue-zhong, Dr. Li Chun-sheng and numerous colleagues in the industry, the Emergency Medicine Society of the Chinese Medical Association appeal to us to draft Construction of Emergency and Pre-hospital Platform. Based on this background, the platform of emergency and pre-hospital first aid helps to build a “one horizontal and one Longitudinal” treatment model, using the horizontal and longitudinal patterns to integrate emergency medical resources to satisfy the automatic information integration and intelligent analysis sharing, realizing the emergency management visualization and medical information digitization, simplifying the medical process and establishing a perfect standard for the emergent diseases, thereby ultimately achieving efficient diagnosis and scientific treatment.

  1. Web-GIS platform for monitoring and forecasting of regional climate and ecological changes

    Science.gov (United States)

    Gordov, E. P.; Krupchatnikov, V. N.; Lykosov, V. N.; Okladnikov, I.; Titov, A. G.; Shulgina, T. M.

    2012-12-01

    Growing volume of environmental data from sensors and model outputs makes development of based on modern information-telecommunication technologies software infrastructure for information support of integrated scientific researches in the field of Earth sciences urgent and important task (Gordov et al, 2012, van der Wel, 2005). It should be considered that original heterogeneity of datasets obtained from different sources and institutions not only hampers interchange of data and analysis results but also complicates their intercomparison leading to a decrease in reliability of analysis results. However, modern geophysical data processing techniques allow combining of different technological solutions for organizing such information resources. Nowadays it becomes a generally accepted opinion that information-computational infrastructure should rely on a potential of combined usage of web- and GIS-technologies for creating applied information-computational web-systems (Titov et al, 2009, Gordov et al. 2010, Gordov, Okladnikov and Titov, 2011). Using these approaches for development of internet-accessible thematic information-computational systems, and arranging of data and knowledge interchange between them is a very promising way of creation of distributed information-computation environment for supporting of multidiscipline regional and global research in the field of Earth sciences including analysis of climate changes and their impact on spatial-temporal vegetation distribution and state. Experimental software and hardware platform providing operation of a web-oriented production and research center for regional climate change investigations which combines modern web 2.0 approach, GIS-functionality and capabilities of running climate and meteorological models, large geophysical datasets processing, visualization, joint software development by distributed research groups, scientific analysis and organization of students and post-graduate students education is

  2. A Maltose-Binding Protein Fusion Construct Yields a Robust Crystallography Platform for MCL1.

    Directory of Open Access Journals (Sweden)

    Matthew C Clifton

    Full Text Available Crystallization of a maltose-binding protein MCL1 fusion has yielded a robust crystallography platform that generated the first apo MCL1 crystal structure, as well as five ligand-bound structures. The ability to obtain fragment-bound structures advances structure-based drug design efforts that, despite considerable effort, had previously been intractable by crystallography. In the ligand-independent crystal form we identify inhibitor binding modes not observed in earlier crystallographic systems. This MBP-MCL1 construct dramatically improves the structural understanding of well-validated MCL1 ligands, and will likely catalyze the structure-based optimization of high affinity MCL1 inhibitors.

  3. Platforms.

    Science.gov (United States)

    Josko, Deborah

    2014-01-01

    The advent of DNA sequencing technologies and the various applications that can be performed will have a dramatic effect on medicine and healthcare in the near future. There are several DNA sequencing platforms available on the market for research and clinical use. Based on the medical laboratory scientist or researcher's needs and taking into consideration laboratory space and budget, one can chose which platform will be beneficial to their institution and their patient population. Although some of the instrument costs seem high, diagnosing a patient quickly and accurately will save hospitals money with fewer hospital stays and targeted treatment based on an individual's genetic make-up. By determining the type of disease an individual has, based on the mutations present or having the ability to prescribe the appropriate antimicrobials based on the knowledge of the organism's resistance patterns, the clinician will be better able to treat and diagnose a patient which ultimately will improve patient outcomes and prognosis.

  4. Gravitational and submersible offshore platform, and construction method. Nedsenkbar fralandsplattform av gravitasjonstypen og fremgangsmaate for fremstilling av samme

    Energy Technology Data Exchange (ETDEWEB)

    Berge, T.; Olsen, O.

    1985-06-17

    The invention concerns a submersible offshore platform of the gravitational type designed for great depths. The platform is made of concrete or the like comprising a sea-bed foundation, and a number of at least 3 cantilevered pillars connected to the prop section carrying the load-bearing structure and the platform deck. In addition, the platform consists of a cellular floating section, and the central part of it is lengthened upwards. The central column supports the prop section. There is a considerable space between the floating section and the bed foundation. The various steps of the construction methods are presented. 11 drawings.

  5. [Construction of the study platform for Meridians and Acupoints and the application in the flipped classroom].

    Science.gov (United States)

    Hu, Rong

    2016-11-12

    To construct the study platform for meridians and acupoints by analyzing the status and current problems of teaching Meridians and Acupoints and in accordance with the principles as "knowledge fragmentation, game breakthrough and overall assessment" and observe the application effect in the flipped classroom. Totally two hundred and five 2014 grade bachelor candidates from four classes of the department of acupuncture-moxibustion and tuina were selected from Hunan Junior College of TCM. They were randomized into an observation group (102 cases) and a control group (103 cases). in the observation group, the flipped classroom was performed by adopting the study platform of meridians and acupoints. Additionally, the team cooperation learning and overall assessment were conducted. In the control group, the traditional teaching system was adopted, in which, the mode of "teacher's demonstration-to-discussion in group-to-teachers' assessment" and the operation check at the end of the semester were applied. The learning effect and the self-learning ability were evaluated at the end of semester in the two groups. The satisfaction survey was conducted in the observation group. In the observation group, the drawing of meridian running course and locating the acupoints, as well as the self-learning ability were better than those in the control group, indicating the significant differences (all P flipped classroom and the satisfaction of participation were slightly low. The study platform of learning Meridians and Acupoints was applied in the flipped classroom and has effectively improved the practical manipulation results and self-learning ability. However, the interestingness and interactivity of the platform are expected to be improved. The effective teaching design should be adopted in the flipped classroom to improve the students' desire of participation.

  6. FORECAST - A cloud-based personalized intelligent virtual coaching platform for the well-being of cancer patients

    DEFF Research Database (Denmark)

    Kyriazakos, Sofoklis; Valentini, Vincenzo; Cesario, Alfredo

    2018-01-01

    coaching for cancer patients focuses on physical, mental, and emotional concerns, which FORECAST is able to identify. Cancer patients can benefit from coaching that addresses their emotional problems, helps them focus on their goals, and supports them in coping with their disease-related stressors....... Personalized coaching in FORECAST offers support, encouragement, motivation, confidence, and hope and is a valuable tool for the wellbeing of a patient....

  7. Construction of a test platform for Test Blanket Module (TBM) systems integration and maintenance in ITER Port Cell #16

    Energy Technology Data Exchange (ETDEWEB)

    Vála, Ladislav, E-mail: ladislav.vala@cvrez.cz [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Reungoat, Mathieu, E-mail: mathieu.reungoat@cvrez.cz [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Vician, Martin [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Poitevin, Yves; Ricapito, Italo; Zmitko, Milan; Panayotov, Dobromir [Fusion for Energy, Josep Pla 2, Torres Diagonal Litoral B3, 08019 Barcelona (Spain)

    2015-10-15

    Highlights: • A non-nuclear, full size facility – TBM platform – is under construction in CVR. • It is designed for tests, optimization and validation of TBS maintenance operations. • It will allow testing and validation of specific maintenance tools and RH equipment. • It reproduces ITER Port Cell #16, as well as the TBS interfaces and main equipment. • The TBM platform will be available for full operation in the first half of 2016. - Abstract: This paper describes a project of a non-nuclear, 1:1 scale testing platform dedicated to tests, optimization and validation of integration and maintenance operations for the European TBM systems in the ITER Port Cell #16. This TBM platform is currently under construction in Centrum výzkumu Řež, Czech Republic. The facility is realized within the scope of the SUSEN project and its full operation is foreseen in the first half of 2016.

  8. A Collaborative Training Platform for Peer-Based Co-Construction of Knowledge and Co-Tutoring

    Directory of Open Access Journals (Sweden)

    Laurent Moccozet

    2009-11-01

    Full Text Available We propose a collaborative training platform where students collectively contribute to the co-construction of the required knowledge to produce their individual semester project. Peers feedback is implemented in order to complete trainers’ supervision with peer-training. This collaborative platform is implemented as a social network, where collaborative interactions are organized 1 to engage and stimulate students to share their resources and contributions; 2 to monitor and comment peers’ contributions.

  9. Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

    Science.gov (United States)

    Kasiviswanathan, K.; Sudheer, K.

    2013-05-01

    Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived

  10. Assessing students' sentiments towards the use of a Building Information Modelling (BIM) learning platform in a construction project management course

    Science.gov (United States)

    Suwal, Sunil; Singh, Vishal

    2018-07-01

    Building Information Modelling (BIM) tools and processes are increasingly adopted and implemented in the construction industry. Consequently, BIM education is considered increasingly important in Architecture, Engineering and Construction (AEC) education. While most of the research and literature on BIM education in engineering studies has focused on BIM implementation strategies, processes, benefits, and challenges, there is limited study on students' perception towards the implementation of BIM courses, or about online BIM learning platforms, or about the BIM tools themselves. Therefore, this paper takes the first steps towards addressing this gap. This study analyses students' (57 students) perception and sentiments towards the use of an online BIM learning platform and explores the potential implications of the findings for BIM education. The findings suggest that online BIM learning platforms are highly rated by students as a positive learning experience, indicating the need for greater integration of such tools and approaches in AEC courses.

  11. Biphasic Finite Element Modeling Reconciles Mechanical Properties of Tissue-Engineered Cartilage Constructs Across Testing Platforms.

    Science.gov (United States)

    Meloni, Gregory R; Fisher, Matthew B; Stoeckl, Brendan D; Dodge, George R; Mauck, Robert L

    2017-07-01

    Cartilage tissue engineering is emerging as a promising treatment for osteoarthritis, and the field has progressed toward utilizing large animal models for proof of concept and preclinical studies. Mechanical testing of the regenerative tissue is an essential outcome for functional evaluation. However, testing modalities and constitutive frameworks used to evaluate in vitro grown samples differ substantially from those used to evaluate in vivo derived samples. To address this, we developed finite element (FE) models (using FEBio) of unconfined compression and indentation testing, modalities commonly used for such samples. We determined the model sensitivity to tissue radius and subchondral bone modulus, as well as its ability to estimate material parameters using the built-in parameter optimization tool in FEBio. We then sequentially tested agarose gels of 4%, 6%, 8%, and 10% weight/weight using a custom indentation platform, followed by unconfined compression. Similarly, we evaluated the ability of the model to generate material parameters for living constructs by evaluating engineered cartilage. Juvenile bovine mesenchymal stem cells were seeded (2 × 10 7 cells/mL) in 1% weight/volume hyaluronic acid hydrogels and cultured in a chondrogenic medium for 3, 6, and 9 weeks. Samples were planed and tested sequentially in indentation and unconfined compression. The model successfully completed parameter optimization routines for each testing modality for both acellular and cell-based constructs. Traditional outcome measures and the FE-derived outcomes showed significant changes in material properties during the maturation of engineered cartilage tissue, capturing dynamic changes in functional tissue mechanics. These outcomes were significantly correlated with one another, establishing this FE modeling approach as a singular method for the evaluation of functional engineered and native tissue regeneration, both in vitro and in vivo.

  12. DNA tetrahedral scaffolds-based platform for the construction of electrochemiluminescence biosensor.

    Science.gov (United States)

    Feng, Qiu-Mei; Zhou, Zhen; Li, Mei-Xing; Zhao, Wei; Xu, Jing-Juan; Chen, Hong-Yuan

    2017-04-15

    Proximal metallic nanoparticles (NPs) could quench the electrochemiluminescence (ECL) emission of semiconductor quantum dots (QDs) due to Förster energy transfer (FRET), but at a certain distance, the coupling of light-emission with surface plasmon resonance (SPR) result in enhanced ECL. Thus, the modification strategies and distances control between QDs and metallic NPs are critical for the ECL intensity of QDs. In this strategy, a SPR enhanced ECL sensor based on DNA tetrahedral scaffolds modified platform was reported for the detection of telomerase activity. Due to the rigid three-dimensional structure, DNA tetrahedral scaffolds grafting on the electrode surface could accurately modulate the distance between CdS QDs and luminol labelled gold nanoparticles (L-Au NPs), meanwhile provide an enhanced spatial dimension and accessibility for the assembly of multiple L-Au NPs. The ECL intensities of both CdS QDs (-1.25V vs. SCE) and luminol (+0.33V vs. SCE) gradually increased along with the formation of multiple L-Au NPs at the vertex of DNA tetrahedral scaffolds induced by telomerase, bringing in a dual-potential ECL analysis. The proposed method showed high sensitivity for the identification of telomerase and was successfully applied for the differentiation of cancer cells from normal cells. This work suggests that DNA tetrahedral scaffolds could serve as an excellent choice for the construction of SPR-ECL system. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa

    International Nuclear Information System (INIS)

    Shukla, Shraddhanand; Funk, Christopher; Hoell, Andrew

    2014-01-01

    In this study we implement and evaluate a simple ‘hybrid’ forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble’s (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and limited technological advances, this region has become a recent epicenter of food insecurity. Timely and skillful precipitation forecasts for EA could help decision makers better manage their limited resources, mitigate socio-economic losses, and potentially save human lives. The ‘hybrid approach’ described in this study uses the CA method to translate dynamical precipitation and sea surface temperature (SST) forecasts over the Indian and Pacific Oceans (specifically 30°S to 30°N and 30°E to 270°E) into terrestrial MAM precipitation forecasts over the EA region. In doing so, this approach benefits from the post-1999 teleconnection that exists between precipitation and SSTs over the Indian and tropical Pacific Oceans (Indo-Pacific) and EA MAM rainfall. The coupled atmosphere-ocean dynamical forecasts used in this study were drawn from the NMME. We demonstrate that while the MAM precipitation forecasts (initialized in February) skill of the NMME models over the EA region itself is negligible, the ranked probability skill score of hybrid CA forecasts based on Indo-Pacific NMME precipitation and SST forecasts reach up to 0.45. (letter)

  14. Developing a calibrated CONUS-wide watershed-scale simulation platform for quantifying the influence of different sources of uncertainty on streamflow forecast skill

    Science.gov (United States)

    Newman, A. J.; Sampson, K. M.; Wood, A. W.; Hopson, T. M.; Brekke, L. D.; Arnold, J.; Raff, D. A.; Clark, M. P.

    2013-12-01

    Skill in model-based hydrologic forecasting depends on the ability to estimate a watershed's initial moisture and energy conditions, to forecast future weather and climate inputs, and on the quality of the hydrologic model's representation of watershed processes. The impact of these factors on prediction skill varies regionally, seasonally, and by model. We are investigating these influences using a watershed simulation platform that spans the continental US (CONUS), encompassing a broad range of hydroclimatic variation, and that uses the current simulation models of National Weather Service streamflow forecasting operations. The first phase of this effort centered on the implementation and calibration of the SNOW-17 and Sacramento soil moisture accounting (SAC-SMA) based hydrologic modeling system for a range of watersheds. The base configuration includes 630 basins in the United States Geological Survey's Hydro-Climatic Data Network 2009 (HCDN-2009, Lins 2012) conterminous U.S. basin subset. Retrospective model forcings were derived from Daymet (http://daymet.ornl.gov/), and where available, a priori parameter estimates were based on or compared with the operational NWS model parameters. Model calibration was accomplished by several objective, automated strategies, including the shuffled complex evolution (SCE) optimization approach developed within the NWS in the early 1990s (Duan et al. 1993). This presentation describes outcomes from this effort, including insights about measuring simulation skill, and on relationships between simulation skill and model parameters, basin characteristics (climate, topography, vegetation, soils), and the quality of forcing inputs. References: %Z Thornton, P.; Thornton, M.; Mayer, B.; Wilhelmi, N.; Wei, Y.; Devarakonda, R; Cook, R. Daymet: Daily Surface Weather on a 1 km Grid for North America. 1980-2008; Oak Ridge National Laboratory Distributed Active Archive Center: Oak Ridge, TN, USA, 2012; Volume 10.

  15. Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery.

    Science.gov (United States)

    Therrien, Eric; Englebienne, Pablo; Arrowsmith, Andrew G; Mendoza-Sanchez, Rodrigo; Corbeil, Christopher R; Weill, Nathanael; Campagna-Slater, Valérie; Moitessier, Nicolas

    2012-01-23

    As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

  16. In Vitro Laser Treatment Platform Construction with Dental Implant Thread Surface on Bacterial Adhesion for Peri-Implantitis

    Directory of Open Access Journals (Sweden)

    Hsien-Nan Kuo

    2017-01-01

    Full Text Available This study constructs a standard in vitro laser treatment platform with dental implant thread surface on bacterial adhesion for peri-implantitis at different tooth positions. The standard clinical adult tooth jaw model was scanned to construct the digital model with 6 mm bone loss depth on behalf of serious peri-implantitis at the incisor, first premolar, and first molar. A cylindrical suite connected to the implant and each tooth root in the jaw model was designed as one experimental unit set to allow the suite to be replaced for individual bacterial adhesion. The digital peri-implantitis and suite models were exported to fulfill the physical model using ABS material in a 3D printer. A 3 mm diameter specimen implant on bacterial adhesion against Escherichia coli was performed for gram-negative bacteria. An Er:YAG laser, working with a chisel type glass tip, was moved from the buccal across the implant thread to the lingual for about 30 seconds per sample to verify the in vitro laser treatment platform. The result showed that the sterilization rate can reach 99.3% and the jaw model was not damaged after laser irradiation testing. This study concluded that using integrated image processing, reverse engineering, CAD system, and a 3D printer to construct a peri-implantitis model replacing the implant on bacterial adhesion and acceptable sterilization rate proved the feasibility of the proposed laser treatment platform.

  17. Construction of the Chinese Veteran Clinical Research (CVCR) platform for the assessment of non-communicable diseases.

    Science.gov (United States)

    Tan, Jiping; Li, Nan; Gao, Jing; Guo, Yuhe; Hu, Wei; Yang, Jinsheng; Yu, Baocheng; Yu, Jianmin; Du, Wei; Zhang, Wenjun; Cui, Lianqi; Wang, Qingsong; Xia, Xiangnan; Li, Jianjun; Zhou, Peiyi; Zhang, Baohe; Liu, Zhiying; Zhang, Shaogang; Sun, Lanying; Liu, Nan; Deng, Ruixiang; Dai, Wenguang; Yi, Fang; Chen, Wenjun; Zhang, Yongqing; Xue, Shenwu; Cui, Bo; Zhao, Yiming; Wang, Luning

    2014-01-01

    Based on the excellent medical care and management system for Chinese veterans, as well as the detailed medical documentation available, we aim to construct a Chinese Veteran Clinical Research (CVCR) platform on non-communicable diseases (NCDs) and carry out studies of the primary disabling NCDs. The Geriatric Neurology Department of Chinese People's Liberation Army General Hospital and veterans' hospitals serve as the leading and participating units in the platform construction. The fundamental constituents of the platform are veteran communities. Stratified typical cluster sampling is adopted to recruit veteran communities. A cross-sectional study of mental, neurological, and substance use (MNS) disorders are performed in two stages using screening scale such as the Mini-Mental State Examination and Montreal cognitive assessment, followed by systematic neuropsychological assessments to make clinical diagnoses, evaluated disease awareness and care situation. A total of 9 676 among 277 veteran communities from 18 cities are recruited into this platform, yielding a response rate of 83.86%. 8 812 subjects complete the MNS subproject screening and total response rate is 91.70%. The average participant age is (82.01±4.61) years, 69.47% of veterans are 80 years or older. Most participants are male (94.01%), 83.36% of subjects have at least a junior high school degree. The overall health status of veterans is good and stable. The most common NCD are cardiovascular disorders (86.44%), urinary and genital diseases (73.14%), eye and ear problems (66.25%), endocrine (56.56%) and neuro-psychiatric disturbances (50.78%). We first construct a veterans' comprehensive clinical research platform for the study of NCDs that is primarily composed of highly educated Chinese males of advanced age and utilize this platform to complete a cross-sectional national investigation of MNS disorders among veterans. The good and stable health condition of the veterans could facilitate the long

  18. Social impact assessment: identification, management and follow-up of community concerns associated with construction of the Hibernia offshore platform

    International Nuclear Information System (INIS)

    Storey, K.

    2003-01-01

    Social impact Assessment (SIA) is the systematic analysis, in advance of the likely impacts of a proposed action, that considers 'all social and cultural consequences to human populations of any public or private actions that alter the ways in which people live, work, play, relate to one another, organize to meet their needs, and generally cope as members of society' (US Department of Commerce 1994). Through the SIA for the construction of the Hibernia offshore oil platform concern, and values of local area residents were identified and a management strategy designed to minimise social disruption associated with the project. Monitoring studies showed that the strategy was effective and that few negative social impacts occurred. The Hibernia offshore oil field, was discovered on the Grand Banks, east of the island of Newfoundland, in 1979. The distance from shore (315 km), its isolation, the periodic presence of sea ice, icebergs and fog, and frequently severe wave and wind conditions, make these waters an extremely hostile work environment. Primarily to maximize human safety, the final engineering design chosen for the project was a fixed, gravity base system (GBS). The platform functions as the main drilling and production unit, the first stage processing facility, oil storage and accommodations base for the offshore crews. The concrete base of the platform, one of the five super-modules that make up the top-sides of the platform and eight of tile smaller top-sides-mounted modules, were fabricated in Newfoundland and the entire platform assembled at Bull Arm, Trinity Bay. (author)

  19. Research on sudden environmental pollution public service platform construction based on WebGIS

    Science.gov (United States)

    Bi, T. P.; Gao, D. Y.; Zhong, X. Y.

    2016-08-01

    In order to actualize the social sharing and service of the emergency-response information for sudden pollution accidents, the public can share the risk source information service, dangerous goods control technology service and so on, The SQL Server and ArcSDE software are used to establish a spatial database to restore all kinds of information including risk sources, hazardous chemicals and handling methods in case of accidents. Combined with Chinese atmospheric environmental assessment standards, the SCREEN3 atmospheric dispersion model and one-dimensional liquid diffusion model are established to realize the query of related information and the display of the diffusion effect under B/S structure. Based on the WebGIS technology, C#.Net language is used to develop the sudden environmental pollution public service platform. As a result, the public service platform can make risk assessments and provide the best emergency processing services.

  20. Analysis of Laogang energy internet and construction of the cloud platform

    Science.gov (United States)

    Wang, Selan; Nie, Jianwen; Zhang, Daiyue; Li, Xia; Tai, Jun; Yu, Zhaohui; Lu, Yiqi; Xie, Da

    2018-02-01

    Laogang solid waste recycling base deals with about 70% waste domestic garbage of Shanghai every day. By recycling the garbage, great amount of energy including electricity, heat and gas can be produced. Meanwhile, the base itself consumes much energy as well. Therefore, an energy internet has been designed for the base to analyse the output and usage of the energy so that the energy utilization rate can be enhanced. In addition, a cloud platform has been established basing on the three-layer cloud technology: IaaS, PaaS and SaaS. This cloud platform mainly analysing electricity will judge whether the energy has been used suitably form all sides and furthermore, improve the operation of the whole energy internet in the base.

  1. A platform for communicating construction material information between e-commerce systems

    Institute of Scientific and Technical Information of China (English)

    Stephen C W Kong; LI Heng; SHEN Qi-ping

    2004-01-01

    E-commerce systems for construction material procurement are becoming increasingly important in Hong Kong. These E-commerce systems are non-interoperable and create problems for the buyers who use these systems to purchase construction materials. This paper presents the mobile agent-based approach and Web serv-ices-based approach for enabling interoperation of these systems in the E-Union environment.

  2. [The method and application to construct experience recommendation platform of acupuncture ancient books based on data mining technology].

    Science.gov (United States)

    Chen, Chuyun; Hong, Jiaming; Zhou, Weilin; Lin, Guohua; Wang, Zhengfei; Zhang, Qufei; Lu, Cuina; Lu, Lihong

    2017-07-12

    To construct a knowledge platform of acupuncture ancient books based on data mining technology, and to provide retrieval service for users. The Oracle 10 g database was applied and JAVA was selected as development language; based on the standard library and ancient books database established by manual entry, a variety of data mining technologies, including word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, supervised classification technology were applied to achieve text automatic extraction of ancient books; in the last, through association mining and decision analysis, the comprehensive and intelligent analysis of disease and symptom, meridians, acupoints, rules of acupuncture and moxibustion in acupuncture ancient books were realized, and retrieval service was provided for users through structure of browser/server (B/S). The platform realized full-text retrieval, word frequency analysis and association analysis; when diseases or acupoints were searched, the frequencies of meridian, acupoints (diseases) and techniques were presented from high to low, meanwhile the support degree and confidence coefficient between disease and acupoints (special acupoint), acupoints and acupoints in prescription, disease or acupoints and technique were presented. The experience platform of acupuncture ancient books based on data mining technology could be used as a reference for selection of disease, meridian and acupoint in clinical treatment and education of acupuncture and moxibustion.

  3. CONCEPTION OF THE ARDUINO PLATFORM AS A BASE FOR THE CONSTRUCTION OF DISTRIBUTED DIAGNOSTIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    Tomasz HANISZEWSKI

    2016-12-01

    Full Text Available Systems for distributed parameter measurements are very expensive solutions; however, they offer many possibilities in terms of real-time verification of machine status. Of course, ready, complex and easy-to-use measuring systems can be used, where the cost of such a solution may be prohibitive. In the case of research carried out under the experimental sphere of an object, e.g., using a research measurement system, it is possible to create a project for a system based mainly on the Arduino platform. As an example, the concept of a distributed measurement system will be presented, with the possibility for use on cranes and conveyors, i.e., on the most common machines on industrial plants.

  4. Miniaturized Analytical Platforms From Nanoparticle Components: Studies in the Construction, Characterization, and High-Throughput Usage of These Novel Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Pris, Andrew David [Iowa State Univ., Ames, IA (United States)

    2003-01-01

    The scientific community has recently experienced an overall effort to reduce the physical size of many experimental components to the nanometer size range. This size is unique as the characteristics of this regime involve aspects of pure physics, biology, and chemistry. One extensively studied example of a nanometer sized experimental component, which acts as a junction between these three principle scientific theologies, is deoxyribonucleic acid (DNA) or ribonucleic acid (RNA). These biopolymers not only contain the biological genetic guide to code for the production of life-sustaining materials, but are also being probed by physicists as a means to create electrical circuits and furthermore as controllable architectural and sensor motifs in the chemical disciplines. Possibly the most common nano-sized component between these sciences are nanoparticles composed of a variety of materials. The cross discipline employment of nanoparticles is evident from the vast amount of literature that has been produced from each of the individual communities within the last decade. Along these cross-discipline lines, this dissertation examines the use of several different types of nanoparticles with a wide array of surface chemistries to understand their adsorption properties and to construct unique miniaturized analytical and immunoassay platforms. This introduction will act as a literature review to provide key information regarding the synthesis and surface chemistries of several types of nanoparticles. This material will set the stage for a discussion of assembling ordered arrays of nanoparticles into functional platforms, architectures, and sensors. The introduction will also include a short explanation of the atomic force microscope that is used throughout the thesis to characterize the nanoparticle-based structures. Following the Introduction, four research chapters are presented as separate manuscripts. Chapter 1 examines the self-assembly of polymeric nanoparticles

  5. Forecasting in strategic international marketing. Conception for and application to the construction of large-scale pollution abatement installations

    International Nuclear Information System (INIS)

    Tressin, J.M.

    1992-01-01

    Division of labour continues to progress worldwide, particularly in the European economy, where it is an accompainment to the steady growth of transnational trade relations. In this situation forecasts attain great importance for companies facing structural decisions. This holds not only for large international concerns but also increasingly for medium-sized companies. The methodological approaches adopted by such companies are primarily aimed at reducing the risk of wrong decisions by gathering information and incorporating forecasts in their planning and decision-making processes. The present article describes various forecasting methods, exemplifying them for the area of commercial-sized building projects. Due to the great complexity of such installations and discontinuities in developments in international markets, quantitative forecasting methods and models are only of limited value here. In contrast to this, qualitative methods such as those provided by expert systems and contemporary dp tools for data collection and compression have attained great importance for the design of practiable and reliable forecasting systems. The present study thus lays have the interface between international marketing and corporate planning and decision-making processes. (orig.) [de

  6. Constructing RBAC based security model in u-healthcare service platform.

    Science.gov (United States)

    Shin, Moon Sun; Jeon, Heung Seok; Ju, Yong Wan; Lee, Bum Ju; Jeong, Seon-Phil

    2015-01-01

    In today's era of aging society, people want to handle personal health care by themselves in everyday life. In particular, the evolution of medical and IT convergence technology and mobile smart devices has made it possible for people to gather information on their health status anytime and anywhere easily using biometric information acquisition devices. Healthcare information systems can contribute to the improvement of the nation's healthcare quality and the reduction of related cost. However, there are no perfect security models or mechanisms for healthcare service applications, and privacy information can therefore be leaked. In this paper, we examine security requirements related to privacy protection in u-healthcare service and propose an extended RBAC based security model. We propose and design u-healthcare service integration platform (u-HCSIP) applying RBAC security model. The proposed u-HCSIP performs four main functions: storing and exchanging personal health records (PHR), recommending meals and exercise, buying/selling private health information or experience, and managing personal health data using smart devices.

  7. Constructing RBAC Based Security Model in u-Healthcare Service Platform

    Directory of Open Access Journals (Sweden)

    Moon Sun Shin

    2015-01-01

    Full Text Available In today’s era of aging society, people want to handle personal health care by themselves in everyday life. In particular, the evolution of medical and IT convergence technology and mobile smart devices has made it possible for people to gather information on their health status anytime and anywhere easily using biometric information acquisition devices. Healthcare information systems can contribute to the improvement of the nation’s healthcare quality and the reduction of related cost. However, there are no perfect security models or mechanisms for healthcare service applications, and privacy information can therefore be leaked. In this paper, we examine security requirements related to privacy protection in u-healthcare service and propose an extended RBAC based security model. We propose and design u-healthcare service integration platform (u-HCSIP applying RBAC security model. The proposed u-HCSIP performs four main functions: storing and exchanging personal health records (PHR, recommending meals and exercise, buying/selling private health information or experience, and managing personal health data using smart devices.

  8. Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

    Science.gov (United States)

    Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

    2016-12-01

    Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples.

  9. Constructing RBAC Based Security Model in u-Healthcare Service Platform

    Science.gov (United States)

    Shin, Moon Sun; Jeon, Heung Seok; Ju, Yong Wan; Lee, Bum Ju; Jeong, Seon-Phil

    2015-01-01

    In today's era of aging society, people want to handle personal health care by themselves in everyday life. In particular, the evolution of medical and IT convergence technology and mobile smart devices has made it possible for people to gather information on their health status anytime and anywhere easily using biometric information acquisition devices. Healthcare information systems can contribute to the improvement of the nation's healthcare quality and the reduction of related cost. However, there are no perfect security models or mechanisms for healthcare service applications, and privacy information can therefore be leaked. In this paper, we examine security requirements related to privacy protection in u-healthcare service and propose an extended RBAC based security model. We propose and design u-healthcare service integration platform (u-HCSIP) applying RBAC security model. The proposed u-HCSIP performs four main functions: storing and exchanging personal health records (PHR), recommending meals and exercise, buying/selling private health information or experience, and managing personal health data using smart devices. PMID:25695104

  10. Nambe Pueblo Water Budget and Forecasting model.

    Energy Technology Data Exchange (ETDEWEB)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  11. Open source platform for collaborative construction of wearable sensor datasets for human motion analysis and an application for gait analysis.

    Science.gov (United States)

    Llamas, César; González, Manuel A; Hernández, Carmen; Vegas, Jesús

    2016-10-01

    Nearly every practical improvement in modeling human motion is well founded in a properly designed collection of data or datasets. These datasets must be made publicly available for the community could validate and accept them. It is reasonable to concede that a collective, guided enterprise could serve to devise solid and substantial datasets, as a result of a collaborative effort, in the same sense as the open software community does. In this way datasets could be complemented, extended and expanded in size with, for example, more individuals, samples and human actions. For this to be possible some commitments must be made by the collaborators, being one of them sharing the same data acquisition platform. In this paper, we offer an affordable open source hardware and software platform based on inertial wearable sensors in a way that several groups could cooperate in the construction of datasets through common software suitable for collaboration. Some experimental results about the throughput of the overall system are reported showing the feasibility of acquiring data from up to 6 sensors with a sampling frequency no less than 118Hz. Also, a proof-of-concept dataset is provided comprising sampled data from 12 subjects suitable for gait analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. FORECASTING ENERGY CONSUMPTION IN SHORT-TERM AND LONG-TERM PERIOD BY USING ARIMAX MODEL IN THE CONSTRUCTION AND MATERIALS SECTOR IN THAILAND

    Directory of Open Access Journals (Sweden)

    Pruethsan Sutthichaimethee

    2017-07-01

    Full Text Available This study aims to analyze the forecasting of energy consumption in the Construction and Materials sectors. The scope of the study covers the forecasting periods of energy consumption for the next 10 years, 2017-2026, 20 years, 2017-2036, and 30 years, 2017-2046, by using ARIMAX Model. The prediction results show that these models are effective in the forecast measured by RMSE, MAE, and MAPE. The results show that from the first model (2,1,1, which predicted the duration of 10 years, 2017-2026, indicates that Thailand has increased an energy consumption rate with the average of 18.09%, while the second model (2,1,2 with the prediction of 20 years, 2017-2036, Thailand arises its energy consumption up to 37.32%. In addition, the third model (2,1,3 predicted the duration of 30 years from 2017 to 2046, and it has found that Thailand increases its energy consumption up to 49.72%.

  13. A User-Centered Mobile Cloud Computing Platform for Improving Knowledge Management in Small-to-Medium Enterprises in the Chilean Construction Industry

    Directory of Open Access Journals (Sweden)

    Daniela Núñez

    2018-03-01

    Full Text Available Knowledge management (KM is a key element for the development of small-to-medium enterprises (SMEs in the construction industry. This is particularly relevant in Chile, where this industry is composed almost entirely of SMEs. Although various KM system proposals can be found in the literature, they are not suitable for SMEs, due to usability problems, budget constraints, and time and connectivity issues. Mobile Cloud Computing (MCC systems offer several advantages to construction SMEs, but they have not yet been exploited to address KM needs. Therefore, this research is aimed at the development of a MCC-based KM platform to manage lessons learned in different construction projects of SMEs, through an iterative and user-centered methodology. Usability and quality evaluations of the proposed platform show that MCC is a feasible and attractive option to address the KM issues in SMEs of the Chilean construction industry, since it is possible to consider both technical and usability requirements.

  14. Modelling and Forecasting of Rice Yield in support of Crop Insurance

    Science.gov (United States)

    Weerts, A.; van Verseveld, W.; Trambauer, P.; de Vries, S.; Conijn, S.; van Valkengoed, E.; Hoekman, D.; Hengsdijk, H.; Schrevel, A.

    2016-12-01

    The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia's farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010 .

  15. Estimates of Uncertainty around the RBA's Forecasts

    OpenAIRE

    Peter Tulip; Stephanie Wallace

    2012-01-01

    We use past forecast errors to construct confidence intervals and other estimates of uncertainty around the Reserve Bank of Australia's forecasts of key macroeconomic variables. Our estimates suggest that uncertainty about forecasts is high. We find that the RBA's forecasts have substantial explanatory power for the inflation rate but not for GDP growth.

  16. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  17. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  18. Construction of the automated system on the basis of the platform 1С: enterprise using the JSON format

    Directory of Open Access Journals (Sweden)

    Fat'yanova A. A.

    2018-04-01

    Full Text Available options of JSON format using to apply it to integrate with third-party applications is discussed in the article. It is offered to use automated systems on platform 1C Enterprise in a parallel mode.

  19. Construction and use of a microfluidic dissection platform for long-term imaging of cellular processes in budding yeast.

    Science.gov (United States)

    Huberts, Daphne H E W; Sik Lee, Sung; Gonzáles, Javier; Janssens, Georges E; Vizcarra, Ima Avalos; Heinemann, Matthias

    2013-06-01

    This protocol describes the production and operation of a microfluidic dissection platform for long-term, high-resolution imaging of budding yeast cells. At the core of this platform is an array of micropads that trap yeast cells in a single focal plane. Newly formed daughter cells are subsequently washed away by a continuous flow of fresh culture medium. In a typical experiment, 50-100 cells can be tracked during their entire replicative lifespan. Apart from aging-related research, the microfluidic platform can also be a valuable tool for other studies requiring the monitoring of single cells over time. Here we provide step-by-step instructions on how to fabricate the silicon wafer mold, how to produce and operate the microfluidic device and how to analyze the obtained data. Production of the microfluidic dissection platform and setting up an aging experiment takes ~7 h.

  20. Supporting Crop Loss Insurance Policy of Indonesia through Rice Yield Modelling and Forecasting

    Science.gov (United States)

    van Verseveld, Willem; Weerts, Albrecht; Trambauer, Patricia; de Vries, Sander; Conijn, Sjaak; van Valkengoed, Eric; Hoekman, Dirk; Grondard, Nicolas; Hengsdijk, Huib; Schrevel, Aart; Vlasbloem, Pieter; Klauser, Dominik

    2017-04-01

    The Government of Indonesia has decided on a crop insurance policy to assist Indonesia's farmers and to boost food security. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform implemented in the Delft-FEWS forecasting system (Werner et al., 2013). The integrated platform brings together remote sensed data (both visible and radar) and hydrologic, crop and reservoir modelling and forecasting to improve the modelling and forecasting of rice yield. The hydrological model (wflow_sbm), crop model (wflow_lintul) and reservoir models (RTC-Tools) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in the integrated platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the G4INDO project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010.

  1. Design, construction, and implementation of an online platform for patients with type 1 diabetes: EncoDiab

    Science.gov (United States)

    Alvarado-Martel, Dácil; Cañas, Francesca; Velasco, Rebeca; Alcubierre, Nuria; López-Ríos, Laura; Rius, Ferran; Nóvoa, Francisco Javier; Carrillo, Armando; Hernández, Marta; Wägner, Ana María; Mauricio, Dídac

    2015-01-01

    Purpose The purpose of this study was to develop, build, and implement a virtual platform equipped with practical tools, relevant contents, and communication rooms, with the aim of facilitating patients’ self-management of type 1 diabetes mellitus (T1DM). Materials and methods The design of the platform was based on the suggestions of T1DM patients who were being managed at two reference hospitals. Patients’ needs and preferences were identified in group discussion sessions. Before having access to the platform, patients underwent a baseline assessment, which included physical examination and the administration of validated questionnaires for evaluation of clinical background, quality of life, treatment satisfaction, and well-being. Results A total of 33 patients were included in the study; 54.5% of them were men, their median age was 34 (18–50) years, the median duration of diabetes was 15 (1–38) years, and the median A1C was 7.4% (6%–12.6%). Based on their suggestions and requests, the online platform EncoDiab was built and organized into four domains: a personal domain, two domains shared by the patients and the staff of each of the two participating hospitals, and one domain that was accessible to all participants. The platform included practical tools (a body mass index calculator, a carbohydrate counting tool, and an insulin-dose calculator), a library with relevant information (documents on prevention and treatment of acute complications, nutrition, exercise, etc), and a chat room. Conclusion Although the study is still ongoing, our current results demonstrate the feasibility of building and implementing an online platform for helping T1DM patients in the self-management of their disease in the public health setting. PMID:26124644

  2. How scientific visions matter: insights from three long-term socio-ecological research (LTSER) platforms under construction in Europe

    NARCIS (Netherlands)

    Mauz, I.; Peltola, T.; Granjou, C.; Bommel, van S.; Buijs, A.E.

    2012-01-01

    Long-Term Socio-Ecological Research (LTSER) has been introduced to change the current approach to ecology and turn it into a big science. LTSER Platforms are currently being created across Europe. They are expected to enhance ecology's capacity to produce useful knowledge for facing global

  3. Using crosslinkable diacetylene phospholipids to construct two-dimensional packed beds in supported lipid bilayer separation platforms

    Directory of Open Access Journals (Sweden)

    Shu-Kai Hu, Sheng-Wen Hsiao, Hsun-Yen Mao, Ya-Ming Chen, Yung Chang and Ling Chao

    2013-01-01

    Full Text Available Separating and purifying cell membrane-associated biomolecules has been a challenge owing to their amphiphilic property. Taking these species out of their native lipid membrane environment usually results in biomolecule degradation. One of the new directions is to use supported lipid bilayer (SLB platforms to separate the membrane species while they are protected in their native environment. Here we used a type of crosslinkable diacetylene phospholipids, diynePC (1,2-bis(10,12-tricosadiynoyl-sn-glycero-3-phosphocholine, as a packed material to create a 'two-dimensional (2D packed bed' in a SLB platform. After the diynePC SLB is exposed to UV light, some of the diynePC lipids in the SLB can crosslink and the non-crosslinked monomer lipids can be washed away, leaving a 2D porous solid matrix. We incorporated the lipid vesicle deposition method with a microfluidic device to pattern the location of the packed-bed region and the feed region with species to be separated in a SLB platform. Our atomic force microscopy result shows that the nano-scaled structure density of the '2D packed bed' can be tuned by the UV dose applied to the diynePC membrane. When the model membrane biomolecules were forced to transport through the packed-bed region, their concentration front velocities were found to decrease linearly with the UV dose, indicating the successful creation of packed obstacles in these 2D lipid membrane separation platforms.

  4. The Impact of Transactive Memory System and Interaction Platform in Collaborative Knowledge Construction on Social Presence and Self-Regulation

    Science.gov (United States)

    Yilmaz, Ramazan; Karaoglan Yilmaz, Fatma Gizem; Kilic Cakmak, Ebru

    2017-01-01

    The purpose of this study is to examine the impacts of transactive memory system (TMS) and interaction platforms in computer-supported collaborative learning (CSCL) on social presence perceptions and self-regulation skills of learners. Within the scope of the study, social presence perceptions and self-regulation skills of students in…

  5. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  6. Innovative Design of Agricultural Cross-border E-commerce Management Platform Construction between Hainan and Taiwan

    Science.gov (United States)

    Song, Jun; Gao, Yanli

    2018-02-01

    The essay is based on the subject research between Hainan and Tai league, by analyzing the comparison of agricultural development between Hainan and other Chinese areas, finds that Hainan agricultural develops slowly. Meanwhile, by using the experience and technology of Taiwan agricultural development for reference, taking full advantage of modern internet technology, we try to find the complementary opportunity of agricultural technology, experience in agricultural development between Hainan and Taiwan. Therefore, by combining the existing resources of Hainan and Taiwan, following the thoughts of the “Internet+ Agriculture”, the essay tries to work out an innovative designation of agricultural cross-border e-commerce management platform, integrate the resource advantages of Hainan and Taiwan, specify the functions of newly designed management platform.

  7. On demand: The singular rht net, an ideal blueprint for the construction of a metal-organic framework (mof) platform

    KAUST Repository

    Eubank, Jarrod F.

    2012-09-07

    The exceptional nature of the rht-MOF platform, based on a singular edge-transitive net (the only net for the combination of 3- and 24-connected nodes), makes it an ideal target in crystal chemistry. The high level of control indicates an unparalleled blueprint for isoreticular functional materials (without concern for interpenetration) for targeted applications. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Design, construction, and implementation of an online platform for patients with type 1 diabetes: EncoDiab

    Directory of Open Access Journals (Sweden)

    Alvarado-Martel D

    2015-06-01

    Full Text Available Dácil Alvarado-Martel,1,2,* Francesca Cañas,3,* Rebeca Velasco,1 Nuria Alcubierre,3 Laura López-Ríos,1,2 Ferran Rius,4 Francisco Javier Nóvoa,1,2 Armando Carrillo,1,2 Marta Hernández,3,4 Ana María Wägner,1,2,* Dídac Mauricio5,6,* 1Department of Endocrinology and Nutrition, Complejo Hospitalario Universitario Insular Materno-Infantil de Gran Canaria, Las Palmas, Spain; 2Instituto Universitario de Investigaciones Biomédicas y Sanitarias, Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain; 3Department of Endocrinology and Nutrition, Institut de Recerca Biomèdica de Lleida (IRBLleida, Lleida, Spain; 4Department of Endocrinology and Nutrition, Hospital Universitari Arnau de Vilanova, Lleida, Spain; 5Hospital Universitari Germans Trias i Pujol, Badalona, Spain; 6Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain *These authors contributed equally to this work Purpose: The purpose of this study was to develop, build, and implement a virtual platform equipped with practical tools, relevant contents, and communication rooms, with the aim of facilitating patients’ self-management of type 1 diabetes mellitus (T1DM.Materials and methods: The design of the platform was based on the suggestions of T1DM patients who were being managed at two reference hospitals. Patients’ needs and preferences were identified in group discussion sessions. Before having access to the platform, patients underwent a baseline assessment, which included physical examination and the administration of validated questionnaires for evaluation of clinical background, quality of life, treatment satisfaction, and well-being.Results: A total of 33 patients were included in the study; 54.5% of them were men, their median age was 34 (18–50 years, the median duration of diabetes was 15 (1–38 years, and the median A1C was 7.4% (6%–12.6%. Based on their suggestions and requests, the online platform EncoDiab was built and organized into

  9. Construction of network model based on crowdfunding platform%基于众筹平台的网络模型的构建

    Institute of Scientific and Technical Information of China (English)

    萧展辉; 严宇平

    2016-01-01

    The global relation is increasingly closed under the environment of the Internet. The Internet finance combines the Internet with finance. The crowdfunding is the product of its development. Since the development of crowdfunding platform is insufficient due to the imperfect domestic institutions in all areas and out⁃dated ideas,on this basis,the network model of the crowdfunding platform is studied. The crowdfunding implementation process and software are integrated to construct the model of the crowdfunding network platform,which can realize the automatic crowdfunding process and standardized operation.%在互联网的背景下,全球的联系越来越紧密,互联网金融把互联网与金融结合在一起,众筹使其发展的产物。当前国内各方面制度的不完善、人们观念的落后等问题致使众筹平台的发展存在不足,基于此研究了众筹平台的网络模型,把众筹的实现过程与软件结合起来构建众筹网络平台模型,以期实现众筹过程的自动化、规范化操作。

  10. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  11. Recent Progress of Solar Weather Forecasting at Naoc

    Science.gov (United States)

    He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

    The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

  12. Exploring the Learner's Knowledge Construction and Cognitive Patterns of Different Asynchronous Platforms: Comparison of an Online Discussion Forum and Facebook

    Science.gov (United States)

    Hou, Huei-Tse; Wang, Shu-Ming; Lin, Peng-Chun; Chang, Kuo-En

    2015-01-01

    The primary purpose of this study is to explore the knowledge construction behaviour and cognitive patterns involved in students' online discussion using online forum and Facebook (FB). This study employed quantitative content analysis and lag sequential analysis to examine the content and behavioural patterns of 50 students from a private…

  13. Construction of a Near-Infrared-Activatable Enzyme Platform To Remotely Trigger Intracellular Signal Transduction Using an Upconversion Nanoparticle.

    Science.gov (United States)

    Gao, Hua-De; Thanasekaran, Pounraj; Chiang, Chao-Wei; Hong, Jia-Lin; Liu, Yen-Chun; Chang, Yu-Hsu; Lee, Hsien-Ming

    2015-07-28

    Photoactivatable (caged) bioeffectors provide a way to remotely trigger or disable biochemical pathways in living organisms at a desired time and location with a pulse of light (uncaging), but the phototoxicity of ultraviolet (UV) often limits its application. In this study, we have demonstrated the near-infrared (NIR) photoactivatable enzyme platform using protein kinase A (PKA), an important enzyme in cell biology. We successfully photoactivated PKA using NIR to phosphorylate its substrate, and this induced a downstream cellular response in living cells with high spatiotemporal resolution. In addition, this system allows NIR to selectively activate the caged enzyme immobilized on the nanoparticle surface without activating other caged proteins in the cytosol. This NIR-responsive enzyme-nanoparticle system provides an innovative approach to remote-control proteins and enzymes, which can be used by researchers who need to avoid direct UV irradiation or use UV as a secondary channel to turn on a bioeffector.

  14. Recurrent networks for wave forecasting

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper presents an application of the Artificial Neural Network, namely Backpropagation Recurrent Neural Network (BRNN) with rprop update algorithm for wave forecasting...

  15. Interval Forecast for Smooth Transition Autoregressive Model ...

    African Journals Online (AJOL)

    In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...

  16. Forecasting Hong Kong economy using factor augmented vector autoregression

    OpenAIRE

    Pang, Iris Ai Jao

    2010-01-01

    This work applies the FAVAR model to forecast GDP growth rate, unemployment rate and inflation rate of the Hong Kong economy. There is no factor model forecasting literature on the Hong Kong economy. The objective is to find out whether factor forecasting of using a large dataset can improve forecast performance of the Hong Kong economy. To avoid misspecification of the number of factors in the FAVAR, combination forecasts are constructed. It is found that forecasts from FAVAR model overall o...

  17. Body surface posture evaluation: construction, validation and protocol of the SPGAP system (Posture evaluation rotating platform system).

    Science.gov (United States)

    Schwertner, Debora Soccal; Oliveira, Raul; Mazo, Giovana Zarpellon; Gioda, Fabiane Rosa; Kelber, Christian Roberto; Swarowsky, Alessandra

    2016-05-04

    Several posture evaluation devices have been used to detect deviations of the vertebral column. However it has been observed that the instruments present measurement errors related to the equipment, environment or measurement protocol. This study aimed to build, validate, analyze the reliability and describe a measurement protocol for the use of the Posture Evaluation Rotating Platform System (SPGAP, Brazilian abbreviation). The posture evaluation system comprises a Posture Evaluation Rotating Platform, video camera, calibration support and measurement software. Two pilot studies were carried out with 102 elderly individuals (average age 69 years old, SD = ±7.3) to establish a protocol for SPGAP, controlling the measurement errors related to the environment, equipment and the person under evaluation. Content validation was completed with input from judges with expertise in posture measurement. The variation coefficient method was used to validate the measurement by the instrument of an object with known dimensions. Finally, reliability was established using repeated measurements of the known object. Expert content judges gave the system excellent ratings for content validity (mean 9.4 out of 10; SD 1.13). The measurement of an object with known dimensions indicated excellent validity (all measurement errors reality. To verify the images of objects with known dimensions the values for the width and height were, respectively, CV 0.88 (width) and 2.33 (height), SD 0.22 (width) and 0.35 (height), minimum and maximum values 24.83-25.2 (width) and 14.56 - 15.75 (height). In the analysis of different images (similar) of an individual, greater discrepancies were observed in the values found. The cervical index, for example, presented minimum and maximum values of 15.38 and 37.5, a coefficient of variation of 0.29 and a standard deviation of 6.78. The SPGAP was shown to be a valid and reliable instrument for the quantitative analysis of body posture with applicability and

  18. Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

    Science.gov (United States)

    Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

    2011-08-01

    The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

  19. The Delft-FEWS flow forecasting system

    NARCIS (Netherlands)

    Werner, M.; Schellekens, J.; Gijsbers, P.; van Dijk, M.; van den Akker, O.; Heynert, K.

    2013-01-01

    Since its introduction in 2002/2003, the current generation of the Delft-FEWS operational forecasting platform has found application in over forty operational centres. In these it is used to link data and models in real time, producing forecasts on a daily basis. In some cases it forms a building

  20. Knowledge platform for calculating climate impact from construction and building materials. Literature study; Kunnskapsplattform for beregning av klimabelastning fra bygg og byggematerialer. Litteraturstudie

    Energy Technology Data Exchange (ETDEWEB)

    Roenning, Anne; Lyng, Kari-Anne; Vold, Mie

    2011-07-01

    Greenhouse gas emissions from building linked today to a large extent to the energy consumption during the operating period. Through increasingly stringent energy requirements and other changes, the energy consumption for the operation could go down over time. This means in this case that the energy required to produce, transport and set up the building, to a greater extent can be relatively more important in a life-cycle analysis. KRD in that regard ha given Oestfoldforskning the commission to conduct a literature study that will provide an overview and assessment of the literature / research papers describing various building materials climate impact and how this translates into a lifetime (LCA - Life Cycle Assessment), and thus describe the knowledge platform these analyzes are based in. It also means a description of the factors that affect the climate and the environment, including the stages of life that are important. Literature study is conducted by searching scientific databases (Springer Link, Science Direct, Google Scholar, Norwegian EPD database of declarations). The literature search is limited to studies that are based on LCA as a methodology for calculating the climate impacts associated with the construction and building materials. Based on the review of literature is also undertaken an analysis focusing on explaining the methodological platform between the studies are based on, in order to explain why the results differ and / or may not be comparable.(eb)

  1. MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for 
the Construction of Sequence Data Warehouses.

    Science.gov (United States)

    Gacesa, Ranko; Zucko, Jurica; Petursdottir, Solveig K; Gudmundsdottir, Elisabet Eik; Fridjonsson, Olafur H; Diminic, Janko; Long, Paul F; Cullum, John; Hranueli, Daslav; Hreggvidsson, Gudmundur O; Starcevic, Antonio

    2017-06-01

    The MEGGASENSE platform constructs relational databases of DNA or protein sequences. The default functional analysis uses 14 106 hidden Markov model (HMM) profiles based on sequences in the KEGG database. The Solr search engine allows sophisticated queries and a BLAST search function is also incorporated. These standard capabilities were used to generate the SCATT database from the predicted proteome of Streptomyces cattleya . The implementation of a specialised metagenome database (AMYLOMICS) for bioprospecting of carbohydrate-modifying enzymes is described. In addition to standard assembly of reads, a novel 'functional' assembly was developed, in which screening of reads with the HMM profiles occurs before the assembly. The AMYLOMICS database incorporates additional HMM profiles for carbohydrate-modifying enzymes and it is illustrated how the combination of HMM and BLAST analyses helps identify interesting genes. A variety of different proteome and metagenome databases have been generated by MEGGASENSE.

  2. Alkynes as a versatile platform for construction of chemical molecular complexity and realization of molecular 3D printing

    International Nuclear Information System (INIS)

    Galkin, K I; Ananikov, V P

    2016-01-01

    The current level of scientific and technological development requires the formation of general tools and techniques. One of the most versatile technologies is 3D printing, which allows fast and efficient creation of materials and biological objects of desired shape and composition. Today, methods have been developed for 3D printing of macro- and nano-sized objects and for production of films and deposited materials with molecular precision but the most promising technology is printing at the molecular level (molecular 3D printing) for the purpose of direct construction of molecular complexity. This process is currently at the initial stage concerning selection of simple molecules to be used as building blocks possessing flexibility, availability and ease of modification. In this review, we examine the possible versatile synthons suitable for preparation of the main types of organic compounds using molecular 3D printing. The surveyed data strongly indicate that alkyne molecules may be used as a building material in a molecular 3D printer working on hydrocarbons. The bibliography includes 428 references

  3. 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...

  4. 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...

  5. 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...

  6. Improved forecasting with leading indicators: the principal covariate index

    NARCIS (Netherlands)

    C. Heij (Christiaan)

    2007-01-01

    textabstractWe propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared

  7. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented.......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...

  8. Short-range forecast of Shershnevskoie (South Ural) water-storage algal blooms: preliminary results of predictors' choosing and membership functions' construction

    Science.gov (United States)

    Gayazova, Anna; Abdullaev, Sanjar

    2014-05-01

    Short-range forecasting of algal blooms in drinking water reservoirs and other waterbodies is an actual element of water treatment system. Particularly, Shershnevskoie reservoir - the source of drinking water for Chelyabinsk city (South Ural region of Russia) - is exposed to interannual, seasonal and short-range fluctuations of blue-green alga Aphanizomenon flos-aquae and other dominant species abundance, which lead to technological problems and economic costs and adversely affect the water treatment quality. Whereas the composition, intensity and the period of blooms affected not only by meteorological seasonal conditions but also by ecological specificity of waterbody, that's important to develop object-oriented forecasting, particularly, search for an optimal number of predictors for such forecasting. Thereby, firstly fuzzy logic and fuzzy artificial neural network patterns for blue-green alga Microcystis aeruginosa (M. aeruginosa) blooms prediction in nearby undrained Smolino lake were developed. These results subsequently served as the base to derive membership functions for Shernevskoie reservoir forecasting patterns. Time series with the total lenght about 138-159 days of dominant species seasonal abundance, water temperature, cloud cover, wind speed, mineralization, phosphate and nitrate concentrations were obtained through field observations held at Lake Smolino (Chelyabinsk) in the warm season of 2009 and 2011 with time resolution of 2-7 days. The cross-correlation analysis of the data revealed the potential predictors of M. aeruginosa abundance quasi-periodic oscillations: green alga Pediastrum duplex (P. duplex) abundance and mineralization for 2009, P. duplex abundance, water temperature and concentration of nitrates for 2011. According to the results of cross-correlation analysis one membership function "P. duplex abundance" and one rule linking M. aeruginosa and P. duplex abundances were set up for database of 2009. Analogically, for database of 2011

  9. 基于区块链的电子仓单流转平台建设%The construction of electronic warehouse receipts circulation platform based on blockchain

    Institute of Scientific and Technical Information of China (English)

    蒋东东; 商玉林; 田野; 陆泽楠

    2017-01-01

    In order to solve the problems of mutual trust and transaction safety in the process of electronic warehouse receipts transfer ,the construction scheme of electronic warehouse trans-fer platform is put forward based on the analysis of the circulation process of electronic ware -house receipts and the the Bitcoin block chain .P2P system is used to package warehouse re-ceipts transaction information into blocks for whole network broadcast ,and all nodes in the whole network can verify its legitimacy and effectiveness .Then the block reaches a consensus through the consensus mechanism ,and it will be added to the block chain .Thus the transaction information can not be tampered with .The result of platform operation shows that the intro -duction of block chain technology can not only ensure the safety and de-centralization of ware-house receipts circulation ,but also improve the commodities trading market .%为了解决电子仓单流转过程中的互信和交易安全等问题,在分析电子仓单的流转过程和比特币区块链的基础上,给出基于区块链的电子仓单流转平台建设方案.采用P2P系统将仓单交易信息打包成区块进行全网广播,全网中所有节点均可验证其合法性和有效性,然后通过共识机制达成共识将区块加入到区块链中,至此仓单交易信息不能被篡改.平台运转结果表明,区块链技术的引入不仅可以保证仓单流转的安全性和去中心化,并且对期货交易市场也有很大的改善.

  10. A Typology of Multi-sided Platforms

    DEFF Research Database (Denmark)

    Staykova, Kalina Stefanova; Damsgaard, Jan

    2015-01-01

    In this paper we address how the composition of a platform impacts the platform’s business model. By platform’s business model we mean platform features, platform architecture and platform governance. To this end, we construct the Platform Business Model Framework. We apply the framework to three...

  11. DESIGN OF OFFSHORE CONCRETE GRAVITY PLATFORMS

    African Journals Online (AJOL)

    gas industry. Manufacturing and construction methods are discussed. Current ... Keywords: concrete gravity platform, offshore, foundation design, manufacturing, ... forms are used to support production drilling ... Manufacture and Construction.

  12. The universal modular platform

    International Nuclear Information System (INIS)

    North, R.B.

    1995-01-01

    A new and patented design for offshore wellhead platforms has been developed to meet a 'fast track' requirement for increased offshore production, from field locations not yet identified. The new design uses modular construction to allow for radical changes in the water depth of the final location and assembly line efficiency in fabrication. By utilizing high strength steels and structural support from the well conductors the new design accommodates all planned production requirements on a support structure significantly lighter and less expensive than the conventional design it replaces. Twenty two platforms based on the new design were ready for installation within 18 months of the project start. Installation of the new platforms began in 1992 for drilling support and 1993 for production support. The new design has become the Company standard for all future production platforms. Large saving and construction costs have been realized through its light weight, flexibility in both positioning and water depth, and its modular construction

  13. Medium-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

    2018-06-01

    Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

  14. Sinking offshore platform. Nedsenkbar fralandsplatform

    Energy Technology Data Exchange (ETDEWEB)

    Einstabland, T.B.; Olsen, O.

    1988-12-19

    The invention deals with a sinking offshore platform of the gravitational type designed for being installed on the sea bed on great depths. The platform consists of at least three inclining pillars placed on a foundation unit. The pillars are at the upper end connected to a tower structure by means of a rigid construction. The tower supports the platform deck. The rigid construction comprises a centre-positioned cylinder connected to the foundation. 11 figs.

  15. Seismic forecast using geostatistics

    International Nuclear Information System (INIS)

    Grecu, Valeriu; Mateiciuc, Doru

    2007-01-01

    The main idea of this research direction consists in the special way of constructing a new type of mathematical function as being a correlation between a computed statistical quantity and another physical quantity. This type of function called 'position function' was taken over by the authors of this study in the field of seismology with the hope of solving - at least partially - the difficult problem of seismic forecast. The geostatistic method of analysis focuses on the process of energy accumulation in a given seismic area, completing this analysis by a so-called loading function. This function - in fact a temporal function - describes the process of energy accumulation during a seismic cycle from a given seismic area. It was possible to discover a law of evolution of the seismic cycles that was materialized in a so-called characteristic function. This special function will help us to forecast the magnitude and the occurrence moment of the largest earthquake in the analysed area. Since 2000, the authors have been evolving to a new stage of testing: real - time analysis, in order to verify the quality of the method. There were five large earthquakes forecasts. (authors)

  16. Ocean wave forecasting using recurrent neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off...

  17. A methodology for Electric Power Load Forecasting

    Directory of Open Access Journals (Sweden)

    Eisa Almeshaiei

    2011-06-01

    Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

  18. Introduction to time series analysis and forecasting

    CERN Document Server

    Montgomery, Douglas C; Kulahci, Murat

    2008-01-01

    An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

  19. kosh 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. kpdt 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...

  1. kewr 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...

  2. kiso 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...

  3. kpga 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...

  4. kbkw 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...

  5. ktcl 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...

  6. pgwt Terminal Aerodrome Forecast

    Data.gov (United States)

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  17. ktix 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. kcod 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. kslk 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. kgfl 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...

  1. kguc 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...

  2. kmlu 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...

  3. kbff 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...

  4. ksmn 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...

  5. kdro 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...

  6. kmce 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...

  7. ktpa 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...

  8. kmot 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...

  9. 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...

  10. klws 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...

  11. kotm 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...

  12. khqm 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. kabr 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. klal 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. kelp 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. kecg 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. khbg 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. kpbf 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. konp 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. pkwa 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...

  1. ktvf 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...

  2. paga 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...

  3. khks 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...

  4. kdsm 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...

  5. kpsm 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...

  6. kgrb 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...

  7. kgmu 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...

  8. papg 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...

  9. kbgm 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...

  10. pamc 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...

  11. klrd 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...

  12. ksan 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. patk 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. kowb 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. klru 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. kfxe 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. kjct 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. kcrg 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. paaq 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. kaex 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...

  1. klbx 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...

  2. kmia 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...

  3. kpit 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...

  4. kcrw 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...

  5. paen 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...

  6. kast 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...

  7. kuin 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...

  8. kmht 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...

  9. kcys 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...

  10. kflo 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...

  11. pakn 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...

  12. pabt 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. krdg 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. khdn 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. kjac 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. kphx 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. Forecasting Space Weather Hazards for Astronauts in Deep Space

    Science.gov (United States)

    Martens, P. C.

    2018-02-01

    Deep Space Gateway provides a unique platform to develop, calibrate, and test a space weather forecasting system for interplanetary travel in a real life setting. We will discuss requirements and design of such a system.

  18. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  19. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  20. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  1. Payment Platform

    DEFF Research Database (Denmark)

    Hjelholt, Morten; Damsgaard, Jan

    2012-01-01

    thoroughly and substitute current payment standards in the decades to come. This paper portrays how digital payment platforms evolve in socio-technical niches and how various technological platforms aim for institutional attention in their attempt to challenge earlier platforms and standards. The paper...... applies a co-evolutionary multilevel perspective to model the interplay and processes between technology and society wherein digital payment platforms potentially will substitute other payment platforms just like the credit card negated the check. On this basis this paper formulate a multilevel conceptual...

  2. Constructing Memory: Competence Maintenance, Education and Training Working Group on the Implementation of Geological Disposal of the Radioactive Waste Technology Platform

    International Nuclear Information System (INIS)

    Palmu, Marjatta

    2015-01-01

    The Implementing Geological Disposal of Radioactive Waste Technology Platform (IGD-TP) community, with over 115 participants in 2014, according to its Vision 2025 (IGD-TP, 2009) aims to proceed to obtaining licences to construct and to safely operate deep geological repositories for spent fuel, high-level waste, and other long-lived radioactive waste in their respective countries. The commitment to Vision 2025 includes developing joint means to facilitate access to expertise and technology, and maintain competencies in the field of geological disposal in Europe. In 2012, IGD-TP launched a Working Group on Competence Maintenance, Education and Training (CMET), as one of its permanent joint activities for addressing its commitment to maintain competencies. In 2013, this permanent organisational working group convened for its first meeting and started working with the support of the IGD-TP Secretariat. The work on competence maintenance within this IGD-TP's working group is first of all focusing on benefiting from and promoting the ECVET approach's application in geological disposal and in future competence building of the community. ECVET approach identifies the LOs that need to be mastered by professionals to carry out their work - starting from the early stages of a waste management programme to running the nuclear waste facilities safely and efficiently. LOs are defined in terms of knowledge, skills and competence (KSC) in ECVET ('attitude' is the corresponding term used by the International Atomic Energy Agency). In their different job functions or tasks the professionals carrying out their work need to master these KSCs at specified European Qualification Framework qualification levels (European Qualification Framework or International Standard Classification for Education according to the job's requirements. The ECVET approach is useful for higher education and continuous professional development, too, not just for vocational education

  3. New offshore platform in the Mexican Gulf

    Energy Technology Data Exchange (ETDEWEB)

    Beisel, T.

    1982-04-01

    After a construction period of only 10 months, the second steel Offshore platform was recently completed in the Mexican Gulf. The pattern for this structure was the Cognac platform. The erection of the new platform, called the 'Cerveza' platform, is described in the article.

  4. Cigeo. The French deep geological repository for radioactive waste. Excavation techniques and technologies tested in underground laboratory and forecasted for the future construction of the project

    International Nuclear Information System (INIS)

    Chauvet, Francois; Bosgiraud, Jean-Michel

    2015-01-01

    Cigeo is the French project for the repository of the high activity and intermediate long-lived radioactive waste. It will be situated at a depth of 500 m, In a clayish rock formation. An underground laboratory was built in the year 2000 and numerous tests are performed since 15 years, in order to know in detail the behavior of the rock and its ability to confine radioactive elements. In addition, this underground laboratory has brought and will continue to bring many lessons on the excavation methods to be chosen for the construction of Cigeo.

  5. 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 ...

  6. Forecasting risks of natural gas consumption in Slovenia

    Energy Technology Data Exchange (ETDEWEB)

    Potocnik, Primoz; Govekar, Edvard; Grabec, Igor [Laboratory of Synergetics, Ljubljana (Slovenia). Faculty of Mechanical Engineering; Thaler, Marko; Poredos, Alojz [Laboratory for Refrigeration, Ljubljana (Slovenia). Faculty of Mechanical Engineering

    2007-08-15

    Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems' cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company. (author)

  7. Forecasting risks of natural gas consumption in Slovenia

    International Nuclear Information System (INIS)

    Potocnik, Primoz; Thaler, Marko; Govekar, Edvard; Grabec, Igor; Poredos, Alojz

    2007-01-01

    Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems' cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company

  8. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  9. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  10. Concerning the justiciability of demand forecasts

    International Nuclear Information System (INIS)

    Nierhaus, M.

    1977-01-01

    This subject plays at present in particular a role in the course of judicial examinations of immediately enforceable orders for the partial construction licences of nuclear power plants. The author distinguishes beween three kinds of forecast decisions: 1. Appraising forecast decisions with standards of judgment taken mainly from the fields of the art, culture, morality, religion are, according to the author, only legally verifyable to a limited extent. 2. With regard to forecast decisions not arguable, e.g. where the future behaviour of persons is concerned, the same should be applied basically. 3. In contrast to this, the following is applicable for programmatic, proceedingslike, or creative forecast decisions, in particular in economics: 'An administrative estimation privilege in a prognostic sense with the consequence that the court has to accept the forecast decision which lies within the forecast margins and which cannot be disproved, and that the court may not replace this forecast decision by its own probability judgment. In these cases, administration has the right to create its own forecast standards.' Judicial control in these cases was limited to certain substantive and procedural mistakes made by the administration in the course of forecast decision finding. (orig./HP) [de

  11. Concerning the justiciability of demand forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Nierhaus, M [Koeln Univ. (Germany, F.R.)

    1977-01-01

    This subject plays at present in particular a role in the course of judicial examinations of immediately enforceable orders for the partial construction licences of nuclear power plants. The author distinguishes beween three kinds of forecast decisions: 1. Appraising forecast decisions with standards of judgment taken mainly from the fields of the art, culture, morality, religion are, according to the author, only legally verifyable to a limited extent. 2. With regard to forecast decisions not arguable, e.g. where the future behaviour of persons is concerned, the same should be applied basically. 3. In contrast to this, the following is applicable for programmatic, proceedingslike, or creative forecast decisions, in particular in economics: 'An administrative estimation privilege in a prognostic sense with the consequence that the court has to accept the forecast decision which lies within the forecast margins and which cannot be disproved, and that the court may not replace this forecast decision by its own probability judgment. In these cases, administration has the right to create its own forecast standards.' Judicial control in these cases was limited to certain substantive and procedural mistakes made by the administration in the course of forecast decision finding.

  12. Combining forecast weights: Why and how?

    Science.gov (United States)

    Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

    2012-09-01

    This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

  13. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  14. Platform Constellations

    DEFF Research Database (Denmark)

    Staykova, Kalina Stefanova; Damsgaard, Jan

    2016-01-01

    This research paper presents an initial attempt to introduce and explain the emergence of new phenomenon, which we refer to as platform constellations. Functioning as highly modular systems, the platform constellations are collections of highly connected platforms which co-exist in parallel and a......’ acquisition and users’ engagement rates as well as unlock new sources of value creation and diversify revenue streams....

  15. Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

    Science.gov (United States)

    Hopson, T. M.

    2014-12-01

    One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

  16. The development rainfall forecasting using kalman filter

    Science.gov (United States)

    Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

    2018-04-01

    Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

  17. Real Time Wave Forecasting Using Wind Time History and Genetic Programming

    Directory of Open Access Journals (Sweden)

    A.R. Kambekar

    2014-12-01

    Full Text Available The significant wave height and average wave period form an essential input for operational activities in ocean and coastal areas. Such information is important in issuing appropriate warnings to people planning any construction or instillation works in the oceanic environment. Many countries over the world routinely collect wave and wind data through a network of wave rider buoys. The data collecting agencies transmit the resulting information online to their registered users through an internet or a web-based system. Operational wave forecasts in addition to the measured data are also made and supplied online to the users. This paper discusses operational wave forecasting in real time mode at locations where wind rather than wave data are continuously recorded. It is based on the time series modeling and incorporates an artificial intelligence technique of genetic programming. The significant wave height and average wave period values are forecasted over a period of 96 hr in future from the observations of wind speed and directions extending to a similar time scale in the past. Wind measurements made by floating buoys at eight different locations around India over a period varying from 1.5 yr to 9.0 yr were considered. The platform of Matlab and C++ was used to develop a graphical user interface that will extend an internet based user-friendly access of the forecasts to any registered user of the data dissemination authority.

  18. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  19. E-Learning Environment of Traditional Chinese Medicine Network Platform Construction%E-Learning环境下的中医药网络平台的研究

    Institute of Scientific and Technical Information of China (English)

    温川飙; 吴莉; 聂鑫; 陈菊

    2016-01-01

    E-Learning as a kind of new study way, which makes use of the data sharing of Internet and rapid transport and infor-mation technology into the combination of content dissemination and learn quickly, more and more favored by all walks of life. Network platform of traditional Chinese medicine with E-Learning approach, combined with a large number of digital research data of traditional Chinese medicine, TCM characteristics of network platform is set up. According to the characteristics of the medicine, teaching and research, provide students with a Learning tool, increase the students and teachers interact;At the same time also for researchers and clinicians to build a collaborative communication platform.%E-Learning(网络学习)作为是一种全新的学习方式,它利用互联网的数据共享、快速传输等特点和信息科技相结合,进行内容传播和快速学习,越来越为各行各业所青睐。中医药网络平台则利用E-Learning的方式,结合大量数字中医药研究数据,建立具有中医药特色的网络平台。结合医、教、研、学的特点,为学生提供一个学习工具,增加学生与教师互动交流,同时也为研究人员、临床医生搭建一个协作交流的平台。

  20. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  1. Forecasting exchange rates: a robust regression approach

    OpenAIRE

    Preminger, Arie; Franck, Raphael

    2005-01-01

    The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...

  2. 基于区块链的第三代中药追溯平台构建研究%Research for Platform Construction of the Third Generation of Traceability for TCM Based on the Blockchain

    Institute of Scientific and Technical Information of China (English)

    温川飙; 赵姝婷; 陈菊; 施明毅; 高原

    2017-01-01

    本文回顾了中药追溯技术发展的8年历程,从基本架构、应用开发到开放平台的三个阶段,探讨中药追溯体系当前面临的主要技术问题和解决思路,重点阐述基于区块链技术的第三代中药追溯平台的开放共享架构原理和方法,讨论物联网、大数据、标准化和接口规范等关键技术对去中心化中药追溯平台构建的意义和作用,为新一代中药追溯体系提供建设思路.%This paper reviews the development of traceability technology for Traditional Chinese Medicine (TCM) backing 8 years,from the stage of the basic architecture,application development to the open platform,to explore the main technical problems of traceability system for TCM facing and solutions,focusing on the blockchain technology of the third-generation TCM traceability platform of open architecture based on the principle and method of sharing.Finally the paper discuss the key technologies,such as the Internet of things,big data,standardization and interface specification,make great significance and function to the construction of the decentralized traceability platform for TCM,which will provide the construction ideas for the new generation of traceability system for TCM.

  3. CORRECTION OF FORECASTS OF INTERRELATED CURRENCY PAIRS IN TERMS OF SYSTEMS OF BALANCE RATIOS

    OpenAIRE

    Gertsekovich D. A.

    2015-01-01

    In this paper the problem of exchange rates forecast is logically considered a) traditionally as a task of forecast on the base of «stand-alone» equations of autoregression for each currency pair and b) as a result of forecast correction of autoregression equations system on the base of boundary conditions of balance ratios systems. As a criterion for quality of forecast constructed with empirical models we take the sum of deficiency quadrates of forecasts estimated for deductive currency pai...

  4. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  5. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  6. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  7. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  8. 基于大数据平台的电力营销信息化建设分析%Informatization Construction of Power Marketing Based on Big Data Platform

    Institute of Scientific and Technical Information of China (English)

    王志坚

    2016-01-01

    Traditional power marketing is lack of deep analysis, mining capacity of data correlation analysis. To solve these problems the author proposes informatization construction of power marketing programme based on big data platform. Based on the huge data of power marketing system, making full use of the huge amount of power data in power marketing system to predict business trends and generate strategy, optimize the marketing and service mode targetedly. The informatization of power marketing of contains the comprehensive service system based on big data platform, the informatization of power marketing based on mobile internet and the technical architecture of big data platform. Informatization construction of power marketing based on the big data platform will enhance the capacity of data mining and analysis in marketing, and improve the ability and the quality of marketing service.%针对传统电力营销存在的电力数据深度分析和发掘能力不足、未涉及数据关联分析等问题,提出了基于大数据平台的营销信息化建设规划。以电力营销系统的海量电力数据为依据,充分挖掘电力数据中有价值的信息,实现业务趋势预测、营销策略制订等,在此基础上有针对性地优化营销方式,改善服务模式。营销信息化包括基于大数据平台的全方位服务体系、基于移动互联网的智能营销服务和大数据平台的技术架构。基于大数据平台的营销信息化建设将增强营销相关领域的数据分析和数据挖掘能力,从而提高营销业务的服务能力和服务质量。

  9. WE-DE-BRA-03: Construction of An Ultrasound Guidance Platform for Image-Guided Radiotherapy with the Intent to Treat Transitional Cell Carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Sick, J; Rancilio, N; Fulkerson, C; LaPetina, P; Poulson, J; Knapp, D; Stantz, K [Purdue University, West Lafayette, IN (United States)

    2016-06-15

    Purpose: Ultrasound (US) is a noninvasive, nonradiographic imaging technique with high spatial and temporal resolution that can be used for localizing soft-tissue structures and tumors in real-time during radiotherapy (inter- and intra-fraction). A detailed methodology integrating 3D-US within RT is presented. This method is easier to adopt into current treatment protocol than current US based systems and reduces user variability for image acquisition, thus eliminating transducer induced changes that limit CT planning system. Methods: We designed an in-house integrated US manipulator and platform to relate CT, 3D-US and linear accelerator coordinate systems. To validate the platform, an agar-based phantom with measured densities and speed-of-sound consistent with tissues surrounding the bladder, was rotated (0–45°) resulting in translations (up to 55mm) relative to the CT and US coordinate systems. After acquiring and integrating CT and US images into the treatment planning system, US-to-US and US-to-CT images were co-registered to re-align the phantom relative to the linear accelerator. Errors in the transformation matrix components were calculate to determine precision of this method under different patient positions. Results: Statistical errors from US-US registrations for different patient orientations ranged from 0.06–1.66mm for x, y, and z translational components, and 0.00–1.05° for rotational components. Statistical errors from US-CT registrations were 0.23–1.18mm for the x, y and z translational components, and 0.08–2.52° for the rotational components. Conclusion: Based on our result, this is consistent with currently used techniques for positioning prostate patients if couch re-positioning is less than a 5 degree rotation. We are now testing this on a dog patient to obtain both inter and intra-fractional positional errors. Additional design considerations include the future use of ultrasound-based functionality (photoacoustics, radioacoustics

  10. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  11. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  12. Modelling and precision of the localization of the robotic mobile platforms for constructions with laser tracker and SmartTrack sensor

    Science.gov (United States)

    Dima, M.; Francu, C.

    2016-08-01

    This paper presents a way to expand the field of use of the laser tracker and SmartTrack sensor localization device used in lately for the localisation of the end effector of the industrial robots to the localization of the mobile construction robots. The research paper presents the equipment along with its characteristics, determines the relationships for the localization coordinates by comparison to the forward kinematics of the industrial robot's spherical arm (positioning mechanism in spherical coordinates) and the orientation mechanism with three revolute axes. In the end of the paper the accuracy of the mobile robot's localization is analysed.

  13. Construction of a new functional platform by grafting poly(4-vinylpyridine) in multi-walled carbon nanotubes for complexing copper ions aiming the amperometric detection of L-cysteine

    International Nuclear Information System (INIS)

    Carvalho Castro e Silva, Cecília de; Breitkreitz, Márcia Cristina; Santhiago, Murilo; Crispilho Corrêa, Cátia; Tatsuo Kubota, Lauro

    2012-01-01

    Highlights: ► Construction of new nanostructured platform based on MWCNTs–PVP to complex copper(II) ions. ► Development of an amperometric sensor for highly selective determination of Cys in food supplement samples. ► Combination of nanocomposite and the copper(II) ions causes a dramatic enhancement in the sensitivity of Cys quantification at low overpotential. - Abstract: This work describes the preparation of an amperometric sensor for electrocatalytical detection of L-cysteine (Cys). The developed sensor is based on a functional platform to complex copper ions on multi-walled carbon nanotubes (MWCNTs) modified with poly-4-vinylpyridine (PVP) through an in situ polymerization. The obtained values for the kinetic constants of heterogeneous electron transfer rate (k s ) and for chemical reaction (k obs ) between Cu 2+ and cysteine were 5.78 s −1 and 6.96 L mol −1 s −1 , respectively. The analytical curve showed a linear response range for detecting L-cysteine in concentrations from 5 to 60 μmol L −1 . The detection and quantification limits obtained were 1.50 and 5.00 μmol L −1 , respectively with a response time of 0.10 s at an applied potential of 150 mV vs SCE.

  14. Flood Forecasting in River System Using ANFIS

    International Nuclear Information System (INIS)

    Ullah, Nazrin; Choudhury, P.

    2010-01-01

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  15. RESGen: Renewable Energy Scenario Generation Platform

    DEFF Research Database (Denmark)

    Iversen, Jan Emil Banning; Pinson, Pierre

    2016-01-01

    studies remains. Consequently, our aim here is to propose an open-source platform for space-time probabilistic forecasting of renewable energy generation (wind and solar power). This document covers both methodological and implementation aspects, to be seen as a companion document for the open......-source scenario generation platform. It can generate predictive densities, trajectories and space-time interdependencies for renewable energy generation. The underlying model works as a post-processing of point forecasts. For illustration, two setups are considered: the case of day-ahead forecasts to be issued......Space-time scenarios of renewable power generation are increasingly used as input to decision-making in operational problems. They may also be used in planning studies to account for the inherent uncertainty in operations. Similarly using scenarios to derive chance-constraints or robust...

  16. Cash Flow Forecasting : Proposal for New Long-Term Cash Flow Forecast in the Case Company

    OpenAIRE

    Pitkänen, Annika

    2016-01-01

    The purpose of this study was to develop a cash flow forecast model for the case company. The case company in this thesis was a Finnish building construction company. The group controlling set a target to improve the corporate treasury’s current long-term cash flow forecast because it was inaccurate and it often had outstanding deficiencies between actual and forecasted figures. A project team was set up to investigate on this issue and this research and development project is documented in t...

  17. Platform computing

    CERN Multimedia

    2002-01-01

    "Platform Computing releases first grid-enabled workload management solution for IBM eServer Intel and UNIX high performance computing clusters. This Out-of-the-box solution maximizes the performance and capability of applications on IBM HPC clusters" (1/2 page) .

  18. The oceanic forecasting system near the Shimokita Peninsula, Japan

    International Nuclear Information System (INIS)

    In, Teiji; Nakayama, Tomoharu; Matsuura, Yasutaka; Shima, Shigeki; Ishikawa, Yoichi; Awaji, Toshiyuki; Kobayashi, Takuya; Kawamura, Hideyuki; Togawa, Orihiko; Toyoda, Takahiro

    2007-01-01

    The oceanic forecasting system off the Shimokita Peninsula was constructed. To evaluate the performance of this system, we carried out the hindcast experiment for the oceanic conditions in 2003. The results showed the system had good reproducibility. Especially, it was able to reproduce the feature of seasonal variation of the Tsugaru Warm Water (TWW). We expect it has enough performance in actual forecasting. (author)

  19. Forecasting Value-at-Risk Under Temporal and Portfolio Aggregation

    NARCIS (Netherlands)

    H.J.W.G. Kole (Erik); T.D. Markwat (Thijs); A. Opschoor (Anne); D.J.C. van Dijk (Dick)

    2016-01-01

    textabstractWe examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of ten trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly or

  20. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

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

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... 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...

  1. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

    This article deals with the problems of forecasting models. First part of the article is dedicated to definition of the relevant areas (vertical and horizontal pillar of definition) and then the forecasting model itself is defined; as article presents theoretical background for further primary research, this definition is crucial. Finally the position of forecasting models within the management system is identified. The paper is a part of the outputs of FEM CULS grant no. 1312/11/3121.

  2. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  3. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  4. [Orange Platform].

    Science.gov (United States)

    Toba, Kenji

    2017-07-01

    The Organized Registration for the Assessment of dementia on Nationwide General consortium toward Effective treatment in Japan (ORANGE platform) is a recently established nationwide clinical registry for dementia. This platform consists of multiple registries of patients with dementia stratified by the following clinical stages: preclinical, mild cognitive impairment, early-stage, and advanced-stage dementia. Patients will be examined in a super-longitudinal fashion, and their lifestyle, social background, genetic risk factors, and required care process will be assessed. This project is also notable because the care registry includes information on the successful, comprehensive management of patients with dementia. Therefore, this multicenter prospective cohort study will contribute participants to all clinical trials for Alzheimer's disease as well as improve the understanding of individuals with dementia.

  5. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  6. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  7. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  8. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  9. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  10. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

    Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

  11. On density forecast evaluation

    NARCIS (Netherlands)

    Diks, C.

    2008-01-01

    Traditionally, probability integral transforms (PITs) have been popular means for evaluating density forecasts. For an ideal density forecast, the PITs should be uniformly distributed on the unit interval and independent. However, this is only a necessary condition, and not a sufficient one, as

  12. Spatiotemporal drought forecasting using nonlinear models

    Science.gov (United States)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  13. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  14. Forecast Inaccuracies in Power Plant Projects From Project Managers' Perspectives

    Science.gov (United States)

    Sanabria, Orlando

    Guided by organizational theory, this phenomenological study explored the factors affecting forecast preparation and inaccuracies during the construction of fossil fuel-fired power plants in the United States. Forecast inaccuracies can create financial stress and uncertain profits during the project construction phase. A combination of purposeful and snowball sampling supported the selection of participants. Twenty project managers with over 15 years of experience in power generation and project experience across the United States were interviewed within a 2-month period. From the inductive codification and descriptive analysis, 5 themes emerged: (a) project monitoring, (b) cost control, (c) management review frequency, (d) factors to achieve a precise forecast, and (e) factors causing forecast inaccuracies. The findings of the study showed the factors necessary to achieve a precise forecast includes a detailed project schedule, accurate labor cost estimates, monthly project reviews and risk assessment, and proper utilization of accounting systems to monitor costs. The primary factors reported as causing forecast inaccuracies were cost overruns by subcontractors, scope gaps, labor cost and availability of labor, and equipment and material cost. Results of this study could improve planning accuracy and the effective use of resources during construction of power plants. The study results could contribute to social change by providing a framework to project managers to lessen forecast inaccuracies, and promote construction of power plants that will generate employment opportunities and economic development.

  15. Evaluation of statistical models for forecast errors from the HBV model

    Science.gov (United States)

    Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

    2010-04-01

    SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

  16. Software selection based on analysis and forecasting methods, practised in 1C

    Science.gov (United States)

    Vazhdaev, A. N.; Chernysheva, T. Y.; Lisacheva, E. I.

    2015-09-01

    The research focuses on the problem of a “1C: Enterprise 8” platform inboard mechanisms for data analysis and forecasting. It is important to evaluate and select proper software to develop effective strategies for customer relationship management in terms of sales, as well as implementation and further maintenance of software. Research data allows creating new forecast models to schedule further software distribution.

  17. Introduction to time series analysis and forecasting

    CERN Document Server

    Montgomery, Douglas C; Kulahci, Murat

    2015-01-01

    Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

  18. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  19. Housing and construction

    Science.gov (United States)

    Delton Alderman

    2014-01-01

    OECD economies, in aggregate, have been sluggish; unemployment remains high in several countries, and minimal gross domestic product gains are forecast for the Euro area through 2016. Recession, sovereign debt problems and lethargic economies continue to constrain Europe’s housing construction market; no improvement is expected before 2015 or...

  20. About the National Forecast Chart

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. The National Forecast Charts

  1. Multicomponent ensemble models to forecast induced seismicity

    Science.gov (United States)

    Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

    2018-01-01

    In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

  2. Marine Point Forecasts

    Science.gov (United States)

    will link to the zone forecast and then allow further zooming to the point of interest whereas on the Honolulu, HI Chicago, IL Northern Indiana, IN Lake Charles, LA New Orleans, LA Boston, MA Caribou, ME

  3. Socioeconomic Forecasting : [Technical Summary

    Science.gov (United States)

    2012-01-01

    Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

  4. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  5. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

    McManamon, A. [Bonneville Power Administration, Portland, OR (United States)

    2007-07-01

    The Columbia River Power System operates with consideration for flood control, endangered species, navigation, irrigation, water supply, recreation, other fish and wildlife concerns and power production. The Bonneville Power Association (BPA) located in Portland, Oregon is responsible for 35-40 per cent of the power consumed within the region. This presentation discussed inflow power concerns at BPA. The presentation illustrated elevational relief of projects; annual and daily variability; the hydrologic cycle; national river service weather forecasting service (NRSWFS); components of NRSWFS; and hydrologic forecast locations. Project operations and inventory were included along with a comparison of the 71-year average unregulated flow with regulated flow at the Dalles. Consistency between short-term and long-term forecasts and long-term streamflow forecasts were also illustrated in graphical format. The presentation also discussed the issue of reducing model and parameter uncertainty; reducing initial conditions uncertainty; snow updating; and reducing meteorological uncertainty. tabs., figs.

  6. CCAA seasonal forecasting

    International Development Research Centre (IDRC) Digital Library (Canada)

    Integrating meteorological and indigenous knowledge-based seasonal climate forecasts in ..... Explanation is based on spiritual and social values. Taught by .... that provided medicine and food became the subject of strict rules and practices ...

  7. Forecast Icing Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Forecast Icing Product (FIP) is an automatically-generated index suitable for depicting areas of potentially hazardous airframe icing. The FIP algorithm uses...

  8. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

    2003-01-01

    Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

  9. Conditional probabilistic population forecasting

    OpenAIRE

    Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

    2003-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

  10. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

    2004-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

  11. EU pharmaceutical expenditure forecast

    OpenAIRE

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives: With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ ph...

  12. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  13. MACROECONOMIC FORECASTING USING BAYESIAN VECTOR AUTOREGRESSIVE APPROACH

    Directory of Open Access Journals (Sweden)

    D. Tutberidze

    2017-04-01

    Full Text Available There are many arguments that can be advanced to support the forecasting activities of business entities. The underlying argument in favor of forecasting is that managerial decisions are significantly dependent on proper evaluation of future trends as market conditions are constantly changing and require a detailed analysis of future dynamics. The article discusses the importance of using reasonable macro-econometric tool by suggesting the idea of conditional forecasting through a Vector Autoregressive (VAR modeling framework. Under this framework, a macroeconomic model for Georgian economy is constructed with the few variables believed to be shaping business environment. Based on the model, forecasts of macroeconomic variables are produced, and three types of scenarios are analyzed - a baseline and two alternative ones. The results of the study provide confirmatory evidence that suggested methodology is adequately addressing the research phenomenon and can be used widely by business entities in responding their strategic and operational planning challenges. Given this set-up, it is shown empirically that Bayesian Vector Autoregressive approach provides reasonable forecasts for the variables of interest.

  14. Against all odds -- Probabilistic forecasts and decision making

    Science.gov (United States)

    Liechti, Katharina; Zappa, Massimiliano

    2015-04-01

    In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

  15. Next-generation probabilistic seismicity forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Hiemer, S.

    2014-07-01

    The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

  16. Next-generation probabilistic seismicity forecasting

    International Nuclear Information System (INIS)

    Hiemer, S.

    2014-01-01

    The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

  17. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  18. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  19. Forecasting Spanish natural life expectancy.

    Science.gov (United States)

    Guillen, Montserrat; Vidiella-i-Anguera, Antoni

    2005-10-01

    Knowledge of trends in life expectancy is of major importance for policy planning. It is also a key indicator for assessing future development of life insurance products, substantiality of existing retirement schemes, and long-term care for the elderly. This article examines the feasibility of decomposing age-gender-specific accidental and natural mortality rates. We study this decomposition by using the Lee and Carter model. In particular, we fit the Poisson log-bilinear version of this model proposed by Wilmoth and Brouhns et al. to historical (1975-1998) Spanish mortality rates. In addition, by using the model introduced by Wilmoth and Valkonen we analyze mortality-gender differentials for accidental and natural rates. We present aggregated life expectancy forecasts compared with those constructed using nondecomposed mortality rates.

  20. Forecasting Analysis of Shanghai Stock Index Based on ARIMA Model

    Directory of Open Access Journals (Sweden)

    Li Chenggang

    2017-01-01

    Full Text Available Prediction and analysis of the Shanghai Composite Index is conducive for investors to investing in the stock market, and providing investors with reference. This paper selects Shanghai Composite Index monthly closing price from Jan, 2005 to Oct, 2016 to construct ARIMA model. This paper carries on the forecast of the last three monthly closing price of Shanghai Stock Index that have occurred, and compared it with the actual value, which tests the accuracy and feasibility of the model in the short term Shanghai Stock Index forecast. At last, this paper uses the ARIMA model to forecast the Shanghai Composite Index closing price of the last two months in 2016.

  1. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  2. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    . The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  3. Wind power forecast

    Energy Technology Data Exchange (ETDEWEB)

    Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

    2012-07-01

    Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

  4. A Time Series Forecasting Method

    Directory of Open Access Journals (Sweden)

    Wang Zhao-Yu

    2017-01-01

    Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.

  5. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  6. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  7. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  8. Analysis of offshore platforms lifting with fixed pile structure type (fixed platform) based on ASD89

    Science.gov (United States)

    Sugianto, Agus; Indriani, Andi Marini

    2017-11-01

    Platform construction GTS (Gathering Testing Sattelite) is offshore construction platform with fix pile structure type/fixed platform functioning to support the mining of petroleum exploitation. After construction fabrication process platform was moved to barges, then shipped to the installation site. Moving process is generally done by pull or push based on construction design determined when planning. But at the time of lifting equipment/cranes available in the work area then the moving process can be done by lifting so that moving activity can be implemented more quickly of work. This analysis moving process of GTS platform in a different way that is generally done to GTS platform types by lifting using problem is construction reinforcement required, so the construction can be moved by lifting with analyzing and checking structure working stress that occurs due to construction moving process by lifting AISC code standard and analysis using the SAP2000 structure analysis program. The analysis result showed that existing condition cannot be moved by lifting because stress ratio is above maximum allowable value that is 0.950 (AISC-ASD89). Overstress occurs on the member 295 and 324 with stress ratio value 0.97 and 0.95 so that it is required structural reinforcement. Box plate aplication at both members so that it produces stress ratio values 0.78 at the member 295 and stress ratio of 0.77 at the member 324. These results indicate that the construction have qualified structural reinforcement for being moved by lifting.

  9. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  10. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  11. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    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.

  12. Earth Remote Sensing for Weather Forecasting and Disaster Applications

    Science.gov (United States)

    Molthan, Andrew; Bell, Jordan; Case, Jonathan; Cole, Tony; Elmer, Nicholas; McGrath, Kevin; Schultz, Lori; Zavodsky, Brad

    2016-01-01

    NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

  13. Forecasting of superconducting compounds

    International Nuclear Information System (INIS)

    Savitskii, E.M.; Gribulya, V.G.; Kiseleva, N.N.

    1981-01-01

    In forecasting new superconducting intermetallic compounds of the A15 and Mo 3 Se types most promising from the viewpoint of high critical temperature Tsub(c), high critical magnetic fields Hsub(c), and high critical currents and in estimating their transition temperature it is proposed to apply cybernetic methods of computer learning

  14. Forecast of nuclear energetics

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, W

    1976-01-01

    The forecast concerning the development of nuclear energetics is presented. Some information on economics of nuclear power plants is given. The nuclear fuel reserves are estimated on the background of power resources of the world. The safety and environment protection problems are mentioned.

  15. Climate Forecast System

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

  16. 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...

  17. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models

  18. NWS Marine Forecast Areas

    Science.gov (United States)

    of Commerce Ocean Prediction Center National Oceanic and Atmospheric Administration Analysis & Unified Surface Analysis Ocean Ocean Products Ice & Icebergs NIC Ice Products NAIS Iceberg Analysis Social Media Facebook Twitter YouTube Search Search For Go NWS All NOAA NWS Marine Forecast Areas

  19. The Latest Forecast.

    Science.gov (United States)

    Laurence, David

    2002-01-01

    Discusses the "latest forecast" for the future of English departments. Addresses departmental and institutional staffing practices, employment opportunities for PhDs, the acceleration of change in the institution, and the general state of the study and teaching of English. (RS)

  20. Ecological forecasts: An emerging imperative

    Science.gov (United States)

    James S. Clark; Steven R. Carpenter; Mary Barber; Scott Collins; Andy Dobson; Jonathan A. Foley; David M. Lodge; Mercedes Pascual; Roger Pielke; William Pizer; Cathy Pringle; Walter V. Reid; Kenneth A. Rose; Osvaldo Sala; William H. Schlesinger; Diana H. Wall; David Wear

    2001-01-01

    Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts...

  1. Air Pollution Forecasts: An Overview

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  2. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  3. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  4. Storm Prediction Center Forecast Products

    Science.gov (United States)

    select the go button to submit request Local forecast by "City, St" or "ZIP" City, St Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC services. Forecast Products Current Weather Watches This is the current graphic showing any severe

  5. Load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Aalborg Nielsen, Henrik

    This report presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. The load for refrigeration is the sum of all cabinets in the supermarket, both low and medium temperature cabinets, and spans a period of one year. As input to the forecasting models the ambient temperature observed near the supermarket together with weather forecasts are used. Every hour...

  6. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

    Science.gov (United States)

    Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.

    2018-07-01

    Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.

  7. Probabilistic Forecasting of Photovoltaic Generation: An Efficient Statistical Approach

    DEFF Research Database (Denmark)

    Wan, Can; Lin, Jin; Song, Yonghua

    2017-01-01

    This letter proposes a novel efficient probabilistic forecasting approach to accurately quantify the variability and uncertainty of the power production from photovoltaic (PV) systems. Distinguished from most existing models, a linear programming based prediction interval construction model for P...... power generation is proposed based on extreme learning machine and quantile regression, featuring high reliability and computational efficiency. The proposed approach is validated through the numerical studies on PV data from Denmark.......This letter proposes a novel efficient probabilistic forecasting approach to accurately quantify the variability and uncertainty of the power production from photovoltaic (PV) systems. Distinguished from most existing models, a linear programming based prediction interval construction model for PV...

  8. Non-seismic tsunamis: filling the forecast gap

    Science.gov (United States)

    Moore, C. W.; Titov, V. V.; Spillane, M. C.

    2015-12-01

    Earthquakes are the generation mechanism in over 85% of tsunamis. However, non-seismic tsunamis, including those generated by meteorological events, landslides, volcanoes, and asteroid impacts, can inundate significant area and have a large far-field effect. The current National Oceanographic and Atmospheric Administration (NOAA) tsunami forecast system falls short in detecting these phenomena. This study attempts to classify the range of effects possible from these non-seismic threats, and to investigate detection methods appropriate for use in a forecast system. Typical observation platforms are assessed, including DART bottom pressure recorders and tide gauges. Other detection paths include atmospheric pressure anomaly algorithms for detecting meteotsunamis and the early identification of asteroids large enough to produce a regional hazard. Real-time assessment of observations for forecast use can provide guidance to mitigate the effects of a non-seismic tsunami.

  9. 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.

  10. The forecaster's added value

    Science.gov (United States)

    Turco, M.; Milelli, M.

    2009-09-01

    To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the

  11. Forecasting carbon dioxide emissions.

    Science.gov (United States)

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Forecasting potential crises

    International Nuclear Information System (INIS)

    Neufeld, W.P.

    1984-01-01

    Recently, the Trend Analysis Program (TAP) of the American Council of Life Insurance commissioned the Futures Group of Glastonbury, Connecticut, to examine the potential for large-scale catastrophic events in the near future. TAP was specifically concerned with five potential crises: the warming of the earth's atmosphere, the water shortage, the collapse of the physical infrastructure, the global financial crisis, and the threat of nuclear war. We are often unprepared to take action; in these cases, we lose an advantage we might have otherwise had. This is the whole idea behind forecasting: to foresee possibilities and to project how we can respond. If we are able to create forecasts against which we can test policy options and choices, we may have the luxury of adopting policies ahead of events. Rather than simply fighting fires, we have the option of creating a future more to our choosing. Short descriptions of these five potential crises and, in some cases, possible solutions are presented

  13. Forecasting oilfield economic performance

    International Nuclear Information System (INIS)

    Bradley, M.E.; Wood, A.R.O.

    1994-01-01

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended

  14. Frost Forecasting for Fruitgrowers

    Science.gov (United States)

    Martsolf, J. D.; Chen, E.

    1983-01-01

    Progress in forecasting from satellite data reviewed. University study found data from satellites displayed in color and used to predict frost are valuable aid to agriculture. Study evaluated scheme to use Earth-temperature data from Geostationary Operational Environmental Satellite in computer model that determines when and where freezing temperatures endanger developing fruit crops, such as apples, peaches and cherries in spring and citrus crops in winter.

  15. Uranium price forecasting methods

    International Nuclear Information System (INIS)

    Fuller, D.M.

    1994-01-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again

  16. Affective Forecasting and Self-Rated Symptoms of Depression, Anxiety, and Hypomania: Evidence for a Dysphoric Forecasting Bias

    Science.gov (United States)

    Hoerger, Michael; Quirk, Stuart W.; Chapman, Benjamin P.; Duberstein, Paul R.

    2011-01-01

    Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n = 325) supplied predicted and actual emotional reactions for three days surrounding an emotionally-evocative relational event, Valentine’s Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias – the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalizations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information processing constructs, decision making, and broader domains of psychopathology. PMID:22397734

  17. Affective forecasting and self-rated symptoms of depression, anxiety, and hypomania: evidence for a dysphoric forecasting bias.

    Science.gov (United States)

    Hoerger, Michael; Quirk, Stuart W; Chapman, Benjamin P; Duberstein, Paul R

    2012-01-01

    Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n=325) supplied predicted and actual emotional reactions for three days surrounding an emotionally evocative relational event, Valentine's Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias-the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalisations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long-assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information-processing constructs, decision making, and broader domains of psychopathology.

  18. PyForecastTools

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    The PyForecastTools package provides Python routines for calculating metrics for model validation, forecast verification and model comparison. For continuous predictands the package provides functions for calculating bias (mean error, mean percentage error, median log accuracy, symmetric signed bias), and for calculating accuracy (mean squared error, mean absolute error, mean absolute scaled error, normalized RMSE, median symmetric accuracy). Convenience routines to calculate the component parts (e.g. forecast error, scaled error) of each metric are also provided. To compare models the package provides: generic skill score; percent better. Robust measures of scale including median absolute deviation, robust standard deviation, robust coefficient of variation and the Sn estimator are all provided by the package. Finally, the package implements Python classes for NxN contingency tables. In the case of a multi-class prediction, accuracy and skill metrics such as proportion correct and the Heidke and Peirce skill scores are provided as object methods. The special case of a 2x2 contingency table inherits from the NxN class and provides many additional metrics for binary classification: probability of detection, probability of false detection, false alarm ration, threat score, equitable threat score, bias. Confidence intervals for many of these quantities can be calculated using either the Wald method or Agresti-Coull intervals.

  19. Statistical methods for forecasting

    CERN Document Server

    Abraham, Bovas

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...

  20. Analysing UK real estate market forecast disagreement

    OpenAIRE

    McAllister, Patrick; Newell, G.; Matysiak, George

    2005-01-01

    Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The re...

  1. 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....

  2. Cloud-Based Software Platform for Smart Meter Data Management

    DEFF Research Database (Denmark)

    Liu, Xiufeng; Nielsen, Per Sieverts

    of the so-called big data possible. This can improve energy management, e.g., help utility companies to forecast energy loads and improve services, and help households to manage energy usage and save money. As this regard, the proposed paper focuses on building an innovative software platform for smart...... their knowledge; scalable data analytics platform for data mining over big data sets for energy demand forecasting and consumption discovering; data as the service for other applications using smart meter data; and a portal for visualizing data analytics results. The design will incorporate hybrid clouds......, including Infrastructure as a Service (IaaS) and Platform as a Service (PaaS), which are suitable for on-demand provisioning, massive scaling, and manageability. Besides, the design will impose extensibility, eciency, and high availability on the system. The paper will evaluate the system comprehensively...

  3. EU pharmaceutical expenditure forecast.

    Science.gov (United States)

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (-€9,367 million), France (-€5,589 million), and, far behind them

  4. Evaluation Of Statistical Models For Forecast Errors From The HBV-Model

    Science.gov (United States)

    Engeland, K.; Kolberg, S.; Renard, B.; Stensland, I.

    2009-04-01

    Three statistical models for the forecast errors for inflow to the Langvatn reservoir in Northern Norway have been constructed and tested according to how well the distribution and median values of the forecasts errors fit to the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order autoregressive model was constructed for the forecast errors. The parameters were conditioned on climatic conditions. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order autoregressive model was constructed for the forecast errors. For the last model positive and negative errors were modeled separately. The errors were first NQT-transformed before a model where the mean values were conditioned on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: We wanted a) the median values to be close to the observed values; b) the forecast intervals to be narrow; c) the distribution to be correct. The results showed that it is difficult to obtain a correct model for the forecast errors, and that the main challenge is to account for the auto-correlation in the errors. Model 1 and 2 gave similar results, and the main drawback is that the distributions are not correct. The 95% forecast intervals were well identified, but smaller forecast intervals were over-estimated, and larger intervals were under-estimated. Model 3 gave a distribution that fits better, but the median values do not fit well since the auto-correlation is not properly accounted for. If the 95% forecast interval is of interest, Model 2 is recommended. If the whole distribution is of interest, Model 3 is recommended.

  5. Evaluation of Probabilistic Disease Forecasts.

    Science.gov (United States)

    Hughes, Gareth; Burnett, Fiona J

    2017-10-01

    The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

  6. Product Platform Performance

    DEFF Research Database (Denmark)

    Munk, Lone

    The aim of this research is to improve understanding of platform-based product development by studying platform performance in relation to internal effects in companies. Platform-based product development makes it possible to deliver product variety and at the same time reduce the needed resources...... engaging in platform-based product development. Similarly platform assessment criteria lack empirical verification regarding relevance and sufficiency. The thesis focuses on • the process of identifying and estimating internal effects, • verification of performance of product platforms, (i...... experienced representatives from the different life systems phase systems of the platform products. The effects are estimated and modeled within different scenarios, taking into account financial and real option aspects. The model illustrates and supports estimation and quantification of internal platform...

  7. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  8. Mobile platform security

    CERN Document Server

    Asokan, N; Dmitrienko, Alexandra

    2013-01-01

    Recently, mobile security has garnered considerable interest in both the research community and industry due to the popularity of smartphones. The current smartphone platforms are open systems that allow application development, also for malicious parties. To protect the mobile device, its user, and other mobile ecosystem stakeholders such as network operators, application execution is controlled by a platform security architecture. This book explores how such mobile platform security architectures work. We present a generic model for mobile platform security architectures: the model illustrat

  9. Research and application of mobile teaching platform

    Science.gov (United States)

    Yang, Ping; Xue, Hongjiao

    2017-08-01

    The application of mobile technology in university digital campus is ripe. This article mainly introduced the necessity of teaching platform based on mobile Internet in the teaching of higher vocational education, and the key to the construction of the feasibility of mobile learning platform, which is a feasible and effective teaching model under the new situation, worthy of promotion. The design and application of teaching platform based on mobile Internet is the change of educational ideas and working methods, and is the new starting point of Higher Vocational education.

  10. Polymer-based platform for microfluidic systems

    Science.gov (United States)

    Benett, William [Livermore, CA; Krulevitch, Peter [Pleasanton, CA; Maghribi, Mariam [Livermore, CA; Hamilton, Julie [Tracy, CA; Rose, Klint [Boston, MA; Wang, Amy W [Oakland, CA

    2009-10-13

    A method of forming a polymer-based microfluidic system platform using network building blocks selected from a set of interconnectable network building blocks, such as wire, pins, blocks, and interconnects. The selected building blocks are interconnectably assembled and fixedly positioned in precise positions in a mold cavity of a mold frame to construct a three-dimensional model construction of a microfluidic flow path network preferably having meso-scale dimensions. A hardenable liquid, such as poly (dimethylsiloxane) is then introduced into the mold cavity and hardened to form a platform structure as well as to mold the microfluidic flow path network having channels, reservoirs and ports. Pre-fabricated elbows, T's and other joints are used to interconnect various building block elements together. After hardening the liquid the building blocks are removed from the platform structure to make available the channels, cavities and ports within the platform structure. Microdevices may be embedded within the cast polymer-based platform, or bonded to the platform structure subsequent to molding, to create an integrated microfluidic system. In this manner, the new microfluidic platform is versatile and capable of quickly generating prototype systems, and could easily be adapted to a manufacturing setting.

  11. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...... on the aspects of the problem, the data, and a summary of the methods used by selected top entries. We also discuss the lessons learned from this competition from the organizers’ perspective. The complete data set, including the solution data, is published along with this paper, in an effort to establish...

  12. Data Platforms and Cities

    DEFF Research Database (Denmark)

    Blok, Anders; Courmont, Antoine; Hoyng, Rolien

    2017-01-01

    This section offers a series of joint reflections on (open) data platform from a variety of cases, from cycling, traffic and mapping to activism, environment and data brokering. Data platforms play a key role in contemporary urban governance. Linked to open data initiatives, such platforms are of...

  13. Dynamic Gaming Platform (DGP)

    Science.gov (United States)

    2009-04-01

    GAMING PLATFORM (DGP) Lockheed Martin Corporation...YYYY) APR 09 2. REPORT TYPE Final 3. DATES COVERED (From - To) Jul 07 – Mar 09 4. TITLE AND SUBTITLE DYNAMIC GAMING PLATFORM (DGP) 5a...CMU Carnegie Mellon University DGP Dynamic Gaming Platform GA Genetic Algorithm IARPA Intelligence Advanced Research Projects Activity LM ATL Lockheed Martin Advanced Technology Laboratories PAINT ProActive INTelligence

  14. ITS Platform North Denmark

    DEFF Research Database (Denmark)

    Lahrmann, Harry; Agerholm, Niels; Juhl, Jens

    2012-01-01

    This paper presents the project entitled “ITS Platform North Denmark” which is used as a test platform for Intelligent Transportation System (ITS) solutions. The platform consists of a newly developed GNSS/GPRS On Board Unit (OBU) to be installed in 500 cars, a backend server and a specially...

  15. Constructing Regional advantage

    DEFF Research Database (Denmark)

    Asheim, Bjørn T.; Boschma, Ron; Cooke, Phil

    2011-01-01

    This paper presents a regional innovation policy model based on the idea of constructing regional advantage. This policy model brings together concepts like related variety, knowledge bases and policy platforms. Related variety attaches importance to knowledge spillovers across complementary...... economic development within and between regions in action lines appropriate to incorporate the basic principles behind related variety and differentiated knowledge bases....

  16. Forecasting in Complex Systems

    Science.gov (United States)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  17. Rebuttal of "Polar bear population forecasts: a public-policy forecasting audit"

    Science.gov (United States)

    Amstrup, Steven C.; Caswell, Hal; DeWeaver, Eric; Stirling, Ian; Douglas, David C.; Marcot, Bruce G.; Hunter, Christine M.

    2009-01-01

    Observed declines in the Arctic sea ice have resulted in a variety of negative effects on polar bears (Ursus maritimus). Projections for additional future declines in sea ice resulted in a proposal to list polar bears as a threatened species under the United States Endangered Species Act. To provide information for the Department of the Interior's listing-decision process, the US Geological Survey (USGS) produced a series of nine research reports evaluating the present and future status of polar bears throughout their range. In response, Armstrong et al. [Armstrong, J. S., K. C. Green, W. Soon. 2008. Polar bear population forecasts: A public-policy forecasting audit. Interfaces 38(5) 382–405], which we will refer to as AGS, performed an audit of two of these nine reports. AGS claimed that the general circulation models upon which the USGS reports relied were not valid forecasting tools, that USGS researchers were not objective or lacked independence from policy decisions, that they did not utilize all available information in constructing their forecasts, and that they violated numerous principles of forecasting espoused by AGS. AGS (p. 382) concluded that the two USGS reports were "unscientific and inconsequential to decision makers." We evaluate the AGS audit and show how AGS are mistaken or misleading on every claim. We provide evidence that general circulation models are useful in forecasting future climate conditions and that corporate and government leaders are relying on these models to do so. We clarify the strict independence of the USGS from the listing decision. We show that the allegations of failure to follow the principles of forecasting espoused by AGS are either incorrect or are based on misconceptions about the Arctic environment, polar bear biology, or statistical and mathematical methods. We conclude by showing that the AGS principles of forecasting are too ambiguous and subjective to be used as a reliable basis for auditing scientific

  18. Visualizing Uncertainty for Probabilistic Weather Forecasting based on Reforecast Analogs

    Science.gov (United States)

    Pelorosso, Leandro; Diehl, Alexandra; Matković, Krešimir; Delrieux, Claudio; Ruiz, Juan; Gröeller, M. Eduard; Bruckner, Stefan

    2016-04-01

    Numerical weather forecasts are prone to uncertainty coming from inaccuracies in the initial and boundary conditions and lack of precision in numerical models. Ensemble of forecasts partially addresses these problems by considering several runs of the numerical model. Each forecast is generated with different initial and boundary conditions and different model configurations [GR05]. The ensembles can be expressed as probabilistic forecasts, which have proven to be very effective in the decision-making processes [DE06]. The ensemble of forecasts represents only some of the possible future atmospheric states, usually underestimating the degree of uncertainty in the predictions [KAL03, PH06]. Hamill and Whitaker [HW06] introduced the "Reforecast Analog Regression" (RAR) technique to overcome the limitations of ensemble forecasting. This technique produces probabilistic predictions based on the analysis of historical forecasts and observations. Visual analytics provides tools for processing, visualizing, and exploring data to get new insights and discover hidden information patterns in an interactive exchange between the user and the application [KMS08]. In this work, we introduce Albero, a visual analytics solution for probabilistic weather forecasting based on the RAR technique. Albero targets at least two different type of users: "forecasters", who are meteorologists working in operational weather forecasting and "researchers", who work in the construction of numerical prediction models. Albero is an efficient tool for analyzing precipitation forecasts, allowing forecasters to make and communicate quick decisions. Our solution facilitates the analysis of a set of probabilistic forecasts, associated statistical data, observations and uncertainty. A dashboard with small-multiples of probabilistic forecasts allows the forecasters to analyze at a glance the distribution of probabilities as a function of time, space, and magnitude. It provides the user with a more

  19. Naive forecasting: the fiasco of coal gasification

    Energy Technology Data Exchange (ETDEWEB)

    Peirce, W S

    1985-01-01

    The decision by the U.S. government to subsidize the development of coal gasification was based on a naive forecast that neglected the influence of price on both conventional sources of supply and consumer demand. Even before substantial construction costs were incurred on the Great Plains plant, a surplus of natural gas has developed. The political process, however, did not include the sort of critical review that often accompanies the financing decision in the private sector and that would surely have prevented this error. 17 references.

  20. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  1. Continuous Platform Development

    DEFF Research Database (Denmark)

    Nielsen, Ole Fiil

    low risks and investments but also with relatively fuzzy results. When looking for new platform projects, it is important to make sure that the company and market is ready for the introduction of platforms, and to make sure that people from marketing and sales, product development, and downstream......, but continuous product family evolution challenges this strategy. The concept of continuous platform development is based on the fact that platform development should not be a one-time experience but rather an ongoing process of developing new platforms and updating existing ones, so that product family...

  2. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    Energy Technology Data Exchange (ETDEWEB)

    Finley, Cathy [WindLogics, St. Paul, MN (United States)

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  3. Research on energy supply, demand and economy forecasting in Japan

    International Nuclear Information System (INIS)

    Shiba, Tsuyoshi; Kamezaki, Hiroshi; Yuyama, Tomonori; Suzuki, Atsushi

    1999-10-01

    This project aims to do research on forecasts of energy demand structure and electricity generation cost in each power plant in Japan in the 21st century, considering constructing successful FBR scenario. During the process of doing research on forecasts of energy demand structure in Japan, documents published from organizations in inside and outside of Japan were collected. These documents include prospects of economic growth rate, forecasts of amount for energy supply and demand, the maximum amount of introducing new energy resources, CO2 regulation, and evaluation of energy best mixture. Organizations in Japan such as Economic Council and Japan Energy Economic Research Institute have provided long-term forecasts until the early 21st century. Meanwhile, organizations overseas have provided forecasts of economic structure, and demand and supply for energy in OECD and East Asia including Japan. In connection with forecasts of electricity generation cost in each power plant, views on the ultimate reserves and cost of resources are reviewed in this report. According to some views on oil reserves, making assumptions based on reserves/production ratio, the maximum length of the time that oil reserves will last is 150 years. In addition, this report provides summaries of cost and potential role of various resources, including solar energy and wind energy; and views on waste, safety, energy security-related externality cost, and the price of transferring CO2 emission right. (author)

  4. Macroeconomic Forecasts in Models with Bayesian Averaging of Classical Estimates

    Directory of Open Access Journals (Sweden)

    Piotr Białowolski

    2012-03-01

    Full Text Available The aim of this paper is to construct a forecasting model oriented on predicting basic macroeconomic variables, namely: the GDP growth rate, the unemployment rate, and the consumer price inflation. In order to select the set of the best regressors, Bayesian Averaging of Classical Estimators (BACE is employed. The models are atheoretical (i.e. they do not reflect causal relationships postulated by the macroeconomic theory and the role of regressors is played by business and consumer tendency survey-based indicators. Additionally, survey-based indicators are included with a lag that enables to forecast the variables of interest (GDP, unemployment, and inflation for the four forthcoming quarters without the need to make any additional assumptions concerning the values of predictor variables in the forecast period.  Bayesian Averaging of Classical Estimators is a method allowing for full and controlled overview of all econometric models which can be obtained out of a particular set of regressors. In this paper authors describe the method of generating a family of econometric models and the procedure for selection of a final forecasting model. Verification of the procedure is performed by means of out-of-sample forecasts of main economic variables for the quarters of 2011. The accuracy of the forecasts implies that there is still a need to search for new solutions in the atheoretical modelling.

  5. FORECASTING NEW PRODUCT SALES

    Directory of Open Access Journals (Sweden)

    R. Siriram

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper tests the accuracy of using Linear regression, Logistics regression, and Bass curves in selected new product rollouts, based on sales data. The selected new products come from the electronics and electrical engineering and information and communications technology industries. The eight selected products are: electronic switchgear, electric motors, supervisory control and data acquisition systems, programmable logic controllers, cell phones, wireless modules, routers, and antennas. We compare the Linear regression, Logistics regression and Bass curves with respect to forecasting using analysis of variance. The accuracy of these three curves is studied and conclusions are drawn. We use an expert panel to compare the different curves and provide lessons for managers to improve forecasting new product sales. In addition, comparison between the two industries is drawn, and areas for further research are indicated.

    AFRIKAANSE OPSOMMING: Hierdie artikel toets die akkuraatheid van die gebruik van linêere regressie, logistiese regressie en Bass-krommes by die bekendstelling van nuwe produkte gebaseer op verkoopsdata. Die geselekteerde nuwe produkte is uit die elektriese en elektroniese asook informasietegnologie- en kommunikasie bedrywe. Linêere regressie, logistiese regressie en Bass-krommes word vergelyk ten opsigte van vooruitskatting deur variansie te ontleed. Die akkuraatheid word ontleed en gevolgtrekkings gemaak. Die doel is om vooruitskatting van nuwe produkverkope te verbeter.

  6. Issues in Forecasting CMEs

    Science.gov (United States)

    Pizzo, V. J.

    2017-12-01

    I will present my view of the current status of space weather forecasting abilities related to CMEs. This talk will address the large-scale aspects, but specifically not energetic particle phenomena. A key point is that all models, whether sophisticated numerical contraptions or quasi-empirical ones, are only as good as the data you feed them. Hence the emphasis will be on observations and analysis methods. First I will review where we stand with regard to the near-Sun quantitative data needed to drive any model, no matter how complex or simple-minded, and I will discuss technological roadblocks that suggest it may be some time before we see any meaningful improvements beyond what we have today. Then I cover issues related to characterizing CME propagation out through the corona and into interplanetary space, as well as to observational limitations in the vicinity of 1 AU. Since none of these observational constraints are likely to be resolved anytime soon, the real challenge is to make more informed use of what is available. Thus, this talk will focus on how we may identify and pursue the most profitable approaches, for both forecast and research applications. The discussion will highlight a number of promising leads, including those related to inclusion of solar backside information, joint magnetograph observations from L5 and Earth, how to use (not just run) ensembles, more rational use of HI observations, and suggestions for using cube-sats for deep space observations of CMEs and MCs.

  7. CORRECTION OF FORECASTS OF INTERRELATED CURRENCY PAIRS IN TERMS OF SYSTEMS OF BALANCE RATIOS

    Directory of Open Access Journals (Sweden)

    Gertsekovich D. A.

    2015-03-01

    Full Text Available In this paper the problem of exchange rates forecast is logically considered a traditionally as a task of forecast on the base of «stand-alone» equations of autoregression for each currency pair and b as a result of forecast correction of autoregression equations system on the base of boundary conditions of balance ratios systems. As a criterion for quality of forecast constructed with empirical models we take the sum of deficiency quadrates of forecasts estimated for deductive currency pairs. Practical approval confirmed that deductive models meet common requirements, provide accepted precision, show resistance to initial data and are free from series of deficiency of one index. However, extreme forecast errors tell that practical application of the approach offered needs further improvement.

  8. Cross-Platform Technologies

    Directory of Open Access Journals (Sweden)

    Maria Cristina ENACHE

    2017-04-01

    Full Text Available Cross-platform - a concept becoming increasingly used in recent years especially in the development of mobile apps, but this consistently over time and in the development of conventional desktop applications. The notion of cross-platform software (multi-platform or platform-independent refers to a software application that can run on more than one operating system or computing architecture. Thus, a cross-platform application can operate independent of software or hardware platform on which it is execute. As a generic definition presents a wide range of meanings for purposes of this paper we individualize this definition as follows: we will reduce the horizon of meaning and we use functionally following definition: a cross-platform application is a software application that can run on more than one operating system (desktop or mobile identical or in a similar way.

  9. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  10. Ecological Forecasting Project Management with Examples

    Science.gov (United States)

    Skiles, J. W.; Schmidt, Cindy; Estes, Maury; Turner, Woody

    2017-01-01

    Once scientists publish results of their projects and studies, all too often they end up on the shelf and are not otherwise used. The NASA Earth Science Division established its Applied Sciences Program (ASP) to apply research findings to help solve and manage real-world problems and needs. ASP-funded projects generally produce decision support systems for operational applications which are expected to last beyond the end of the NASA funding. Because of NASAs unique perspective of looking down on the Earth from space, ASP studies involve the use of remotely sensed information consisting of satellite data and imagery as well as information from sub-orbital platforms. ASP regularly solicits Earth science proposals that address one or more focus areas; disasters mitigation, ecological forecasting, health and air quality, and water resources. Reporting requirements for ASP-funded projects are different from those typical for research grants from NASA and other granting agencies, requiring management approaches different from other programs. This presentation will address the foregoing in some detail and give examples of three ASP-funded ecological forecasting projects that include: 1) the detection and survey of chimpanzee habitat in Africa from space, 2) harmful algal blooms (HABs) in the California Current System affecting aquaculture facilities and marine mammal populations, and 3) a call for the public to identify North America wildlife in Wisconsin using trail camera photos. Contact information to propose to ASP solicitations for those PIs interested is also provided.

  11. Forecasting Chronic Diseases Using Data Fusion.

    Science.gov (United States)

    Acar, Evrim; Gürdeniz, Gözde; Savorani, Francesco; Hansen, Louise; Olsen, Anja; Tjønneland, Anne; Dragsted, Lars Ove; Bro, Rasmus

    2017-07-07

    Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC-MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC-MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer.

  12. Guidelines for forecasting energy demand

    International Nuclear Information System (INIS)

    Sonino, T.

    1976-11-01

    Four methodologies for forecasting energy demand are reviewed here after considering the role of energy in the economy and the analysis of energy use in different economic sectors. The special case of Israel is considered throughout, and some forecasts for energy demands in the year 2000 are presented. An energy supply mix that may be considered feasible is proposed. (author)

  13. Regional-seasonal weather forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  14. Forecasting the future of biodiversity

    DEFF Research Database (Denmark)

    Fitzpatrick, M. C.; Sanders, Nate; Ferrier, Simon

    2011-01-01

    , but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single-species models to those from a multi-species modeling approach, Generalized Dissimilarity Modeling (GDM...... climate change impacts on biodiversity....

  15. Ensemble hydromoeteorological forecasting in Denmark

    DEFF Research Database (Denmark)

    Lucatero Villasenor, Diana

    forecasts where a dampening of the differences of precipitation quality occurs. Seasonal meteorological forecasts are possible due to changes of large scale patterns of the ocean and land, such as el Niño, that evolve at a much slower pace than the atmosphere, which can have an impact on its evolution later...

  16. Now, Here's the Weather Forecast...

    Science.gov (United States)

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  17. How accurate are the weather forecasts for Bierun (southern Poland)?

    Science.gov (United States)

    Gawor, J.

    2012-04-01

    Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why

  18. The long-run forecasting of energy prices using the model of shifting trend

    International Nuclear Information System (INIS)

    Radchenko, Stanislav

    2005-01-01

    Developing models for accurate long-term energy price forecasting is an important problem because these forecasts should be useful in determining both supply and demand of energy. On the supply side, long-term forecasts determine investment decisions of energy-related companies. On the demand side, investments in physical capital and durable goods depend on price forecasts of a particular energy type. Forecasting long-run rend movements in energy prices is very important on the macroeconomic level for several developing countries because energy prices have large impacts on their real output, the balance of payments, fiscal policy, etc. Pindyck (1999) argues that the dynamics of real energy prices is mean-reverting to trend lines with slopes and levels that are shifting unpredictably over time. The hypothesis of shifting long-term trend lines was statistically tested by Benard et al. (2004). The authors find statistically significant instabilities for coal and natural gas prices. I continue the research of energy prices in the framework of continuously shifting levels and slopes of trend lines started by Pindyck (1999). The examined model offers both parsimonious approach and perspective on the developments in energy markets. Using the model of depletable resource production, Pindyck (1999) argued that the forecast of energy prices in the model is based on the long-run total marginal cost. Because the model of a shifting trend is based on the competitive behavior, one may examine deviations of oil producers from the competitive behavior by studying the difference between actual prices and long-term forecasts. To construct the long-run forecasts (10-year-ahead and 15-year-ahead) of energy prices, I modify the univariate shifting trends model of Pindyck (1999). I relax some assumptions on model parameters, the assumption of white noise error term, and propose a new Bayesian approach utilizing a Gibbs sampling algorithm to estimate the model with autocorrelation. To

  19. Method of forecasting power distribution

    International Nuclear Information System (INIS)

    Kaneto, Kunikazu.

    1981-01-01

    Purpose: To obtain forecasting results at high accuracy by reflecting the signals from neutron detectors disposed in the reactor core on the forecasting results. Method: An on-line computer transfers, to a simulator, those process data such as temperature and flow rate for coolants in each of the sections and various measuring signals such as control rod positions from the nuclear reactor. The simulator calculates the present power distribution before the control operation. The signals from the neutron detectors at each of the positions in the reactor core are estimated from the power distribution and errors are determined based on the estimated values and the measured values to determine the smooth error distribution in the axial direction. Then, input conditions at the time to be forecast are set by a data setter. The simulator calculates the forecast power distribution after the control operation based on the set conditions. The forecast power distribution is corrected using the error distribution. (Yoshino, Y.)

  20. Energy forecasts, perspectives and methods

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J E; Mogren, A

    1984-01-01

    The authors have analyzed different methods for long term energy prognoses, in particular energy consumption forecasts. Energy supply and price prognoses are also treated, but in a less detailed manner. After defining and discussing the various methods/models used in forecasts, a generalized discussion of the influence on the prognoses from the perspectives (background factors, world view, norms, ideology) of the prognosis makers is given. Some basic formal demands that should be asked from any rational forecast are formulated and discussed. The authors conclude that different forecasting methodologies are supplementing each other. There is no best method, forecasts should be accepted as views of the future from differing perspectives. The primary prognostic problem is to show the possible futures, selecting the wanted future is a question of political process.

  1. Sirocco - Fukushima Forecast Description

    International Nuclear Information System (INIS)

    2011-01-01

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  2. Sirocco - Fukushima Forecast Description

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-04-10

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  3. Forecasting global atmospheric CO2

    International Nuclear Information System (INIS)

    Agusti-Panareda, A.; Massart, S.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Engelen, R.; Jones, L.; Peuch, V.H.; Chevallier, F.; Ciais, P.; Paris, J.D.; Sherlock, V.

    2014-01-01

    A new global atmospheric carbon dioxide (CO 2 ) real-time forecast is now available as part of the preoperational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO 2 forecasting system is that the land surface, including vegetation CO 2 fluxes, is modelled online within the IFS. Other CO 2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO 2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO 2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO 2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO 2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO 2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO 2 fluxes also lead to accumulating errors in the CO 2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO 2 fluxes compared to total optimized fluxes and the atmospheric CO 2 compared to observations. The largest biases in the atmospheric CO 2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO 2 analyses based on the assimilation of CO 2 products retrieved from satellite

  4. ADMS Evaluation Platform

    Energy Technology Data Exchange (ETDEWEB)

    2018-01-23

    Deploying an ADMS or looking to optimize its value? NREL offers a low-cost, low-risk evaluation platform for assessing ADMS performance. The National Renewable Energy Laboratory (NREL) has developed a vendor-neutral advanced distribution management system (ADMS) evaluation platform and is expanding its capabilities. The platform uses actual grid-scale hardware, large-scale distribution system models, and advanced visualization to simulate realworld conditions for the most accurate ADMS evaluation and experimentation.

  5. APPLIED ORGANIZATION OF CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    Kievskiy Leonid Vladimirovich

    2017-03-01

    Full Text Available Applied disciplines in the sphere of construction which are engaged in the solution of vital macroeconomical problems (the general trend of development of these disciplines is the expansion of problematics and mutual integration are considered. Construction organization characteristic at the present stage as a systems engineering discipline covering the investment process of creation of real estate items, is given. The main source of current research trends for applied sciences (socio-economic development forecasts, regional and local programs is determined. Interpenetration and integration of various fields of knowledge exemplified by the current interindustry problem of blocks renovation organization of existing development, is demonstrated. Mathematical model of wave construction (for the period of deployment is proposed. Nature of dependence of the total duration of renovation on the limit of annual input and coefficient of renovation, is established. Overall structure of the Moscow region housing market is presented, and approaches to definition of effective demand are proposed.

  6. Platform development supportedby gaming

    DEFF Research Database (Denmark)

    Mikkola, Juliana Hsuan; Hansen, Poul H. Kyvsgård

    2007-01-01

    The challenge of implementing industrial platforms in practice can be described as a configuration problem caused by high number of variables, which often have contradictory influences on the total performance of the firm. Consequently, the specific platform decisions become extremely complex......, possibly increasing the strategic risks for the firm. This paper reports preliminary findings on platform management process at LEGO, a Danish toy company.  Specifically, we report the process of applying games combined with simulations and workshops in the platform development. We also propose a framework...

  7. Omnidirectional holonomic platforms

    International Nuclear Information System (INIS)

    Pin, F.G.; Killough, S.M.

    1994-01-01

    This paper presents the concepts for a new family of wheeled platforms which feature full omnidirectionality with simultaneous and independently controlled rotational and translational motion capabilities. The authors first present the orthogonal-wheels concept and the two major wheel assemblies on which these platforms are based. They then describe how a combination of these assemblies with appropriate control can be used to generate an omnidirectional capability for mobile robot platforms. The design and control of two prototype platforms are then presented and their respective characteristics with respect to rotational and translational motion control are discussed

  8. Platform decommissioning costs

    International Nuclear Information System (INIS)

    Rodger, David

    1998-01-01

    There are over 6500 platforms worldwide contributing to the offshore oil and gas production industry. In the North Sea there are around 500 platforms in place. There are many factors to be considered in planning for platform decommissioning and the evaluation of options for removal and disposal. The environmental impact, technical feasibility, safety and cost factors all have to be considered. This presentation considers what information is available about the overall decommissioning costs for the North Sea and the costs of different removal and disposal options for individual platforms. 2 figs., 1 tab

  9. An Investigation of Digital Payment Platform Designs

    DEFF Research Database (Denmark)

    Kazan, Erol; Damsgaard, Jan

    2014-01-01

    This paper focuses on the triumph march of mobile phones that currently are annexing music players, navigation devices, and cameras as separate physical objects. The next target is set on payment. Through synthesizing available literature, we construct a framework for studying digital payment...... platforms that combines platform, technology and business design aspects. The framework is applied to conduct a comparative case study of digital payment platforms. Four types of market actors are considered: banks, mobile network operators, merchants, and startups, which are incumbents and disrupters....... By hosting third-party services, payment instruments are evolving from single-purpose to multi-functional ones. Our research extends existing payment literature from the MSP perspective to emphasize certain digital payment platform components, which impact strategies and complementary products....

  10. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  11. Black Sea coastal forecasting system

    Directory of Open Access Journals (Sweden)

    A. I. Kubryakov

    2012-03-01

    Full Text Available The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

  12. NSTL全国服务体系监测平台的构建策略和关键技术*%The Construction Strategy and Key Technologies of NSTL Monitoring Platform

    Institute of Scientific and Technical Information of China (English)

    王莉; 郝春云; 刘玉海

    2013-01-01

    This paper proposes the strategy of NSLT Monitoring Platform, including monitoring indicators, three-level framework, and the core business logic of data col ection, tracking, alarm and storage, and describes key technologies such as Shel programming, JMX framework, data storage and alarm mechanisms.%  文章提出NSTL全国服务体系监测平台的构建策略,包括监测指标、三级监测体系,以及从数据收集、跟踪、告警到存储的核心业务逻辑分析,对Shell编程、JMX框架、数据存储和报警机制等关键技术进行了描述。

  13. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  14. Basin Assessment Spatial Planning Platform

    Energy Technology Data Exchange (ETDEWEB)

    2017-07-26

    The tool is intended to facilitate hydropower development and water resource planning by improving synthesis and interpretation of disparate spatial datasets that are considered in development actions (e.g., hydrological characteristics, environmentally and culturally sensitive areas, existing or proposed water power resources, climate-informed forecasts). The tool enables this capability by providing a unique framework for assimilating, relating, summarizing, and visualizing disparate spatial data through the use of spatial aggregation techniques, relational geodatabase platforms, and an interactive web-based Geographic Information Systems (GIS). Data are aggregated and related based on shared intersections with a common spatial unit; in this case, industry-standard hydrologic drainage areas for the U.S. (National Hydrography Dataset) are used as the spatial unit to associate planning data. This process is performed using all available scalar delineations of drainage areas (i.e., region, sub-region, basin, sub-basin, watershed, sub-watershed, catchment) to create spatially hierarchical relationships among planning data and drainages. These entity-relationships are stored in a relational geodatabase that provides back-end structure to the web GIS and its widgets. The full technology stack was built using all open-source software in modern programming languages. Interactive widgets that function within the viewport are also compatible with all modern browsers.

  15. Flow Forecasting in Drainage Systems with Extrapolated Radar Rainfall Data and Auto Calibration on Flow Observations

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Grum, M.; Rasmussen, Michael R.

    2011-01-01

    Forecasting of flows, overflow volumes, water levels, etc. in drainage systems can be applied in real time control of drainage systems in the future climate in order to fully utilize system capacity and thus save possible construction costs. An online system for forecasting flows and water levels......-calibrated on flow measurements in order to produce the best possible forecast for the drainage system at all times. The system shows great potential for the implementation of real time control in drainage systems and forecasting flows and water levels.......Forecasting of flows, overflow volumes, water levels, etc. in drainage systems can be applied in real time control of drainage systems in the future climate in order to fully utilize system capacity and thus save possible construction costs. An online system for forecasting flows and water levels...... in a small urban catchment has been developed. The forecast is based on application of radar rainfall data, which by a correlation based technique, is extrapolated with a lead time up to two hours. The runoff forecast in the drainage system is based on a fully distributed MOUSE model which is auto...

  16. Incorporating operational experience and design changes in availability forecasts

    International Nuclear Information System (INIS)

    Norman, D.

    1988-01-01

    Reliability or availability forecasts which are based solely on past operating experience will be precise if the sample is large enough, and unbiased if nothing in the future design, environment, operating region or anything else changes. Unfortunately, life is never like that. This paper considers the methodology and philosophy of modifying forecasts based on past experience to take account also of changes in design, construction methods, operating philosophy, environments, operator training and so on, between the plants which provided the operating experience and the plant for which the forecast is being made. This emphasises the importance of collecting, assessing, and learning from past data and of a thorough knowledge of future designs, and procurement, operation, and maintenance policies. The difference between targets and central estimates is also discussed. The paper concludes that improvements in future availability can be made by learning from past experience, but that certain conditions must be fulfilled in order to do so. (author)

  17. Reference Scenario Forecasting: A New Approach to Transport Project Assessment

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen; Skougaard, Britt Zoëga

    2010-01-01

    This paper presents a new approach to transport project assessment in terms of feasibility risk assessment and reference class forecasting. Normally, transport project assessment is based upon a cost-benefit approach where evaluation criteria such as net present values are obtained. Recent research...... construction cost estimates. Hereafter, a quantitative risk analysis is provided making use of Monte Carlo simulation. This stochastic approach facilitates random input parameters based upon reference class forecasting, hence, a parameter data fit has been performed in order to obtain validated probability...... forecasting (RSF) frame. The RSF is anchored in the cost-benefit analysis (CBA), thus, it provides decision-makers with a quantitative mean of assessing the transport infrastructure project. First, the RSF method introduces uncertainties within the CBA by applying Optimism Bias uplifts on the preliminary...

  18. Transport project evaluation: feasibility risk assessment and scenario forecasting

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2017-01-01

    This paper presents a new approach to transport project assessment in terms of feasibility risk assessment and reference class forecasting. Conventionally, transport project assessment is based upon a Cost-Benefit Analysis (CBA) where evaluation criteria such as Benefit Cost Ratios (BCR...... on the preliminary construction cost estimates. Hereafter, a quantitative risk analysis is provided making use of Monte Carlo simulation. This approach facilitates random input parameters based upon reference class forecasting, hence, a parameter data fit has been performed in order to obtain validated probability...... Scenario Forecasting (RSF) frame. The RSF is anchored in the cost-benefit analysis; thus, it provides decision-makers with a quantitative mean of assessing the transport infrastructure project. First, the RSF method introduces uncertainties within the CBA by applying Optimism Bias uplifts...

  19. Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wan, Can; Song, Yonghua; Xu, Zhao

    2016-01-01

    probabilities of prediction errors provide an alternative yet effective solution. This article proposes a hybrid artificial neural network approach to generate prediction intervals of wind power. An extreme learning machine is applied to conduct point prediction of wind power and estimate model uncertainties...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

  20. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

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

  1. 25 years of time series forecasting

    NARCIS (Netherlands)

    de Gooijer, J.G.; Hyndman, R.J.

    2006-01-01

    We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985 and International Journal of Forecasting 1985-2005). During

  2. Groundwater Assessment Platform

    OpenAIRE

    Podgorski, Joel; Berg, Michael

    2018-01-01

    The Groundwater Assessment Platform is a free, interactive online GIS platform for the mapping, sharing and statistical modeling of groundwater quality data. The modeling allows users to take advantage of publicly available global datasets of various environmental parameters to produce prediction maps of their contaminant of interest.

  3. EURESCOM Services Platform

    NARCIS (Netherlands)

    Nieuwenhuis, Lambertus Johannes Maria; van Halteren, Aart

    1999-01-01

    This paper presents the results of the EURESCOM Project 715. In February 1999, a large team of researchers from six European public network operators completed a two year period of cooperative experiments on a TINA-based environment, called the EURESCOM Services Platform (ESP). This platform

  4. Combining 2-m temperature nowcasting and short range ensemble forecasting

    Directory of Open Access Journals (Sweden)

    A. Kann

    2011-12-01

    Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous

  5. Product Platform Modeling

    DEFF Research Database (Denmark)

    Pedersen, Rasmus

    for customisation of products. In many companies these changes in the business environment have created a controversy between the need for a wide variety of products offered to the marketplace and a desire to reduce variation within the company in order to increase efficiency. Many companies use the concept...... other. These groups can be varied and combined to form different product variants without increasing the internal variety in the company. Based on the Theory of Domains, the concept of encapsulation in the organ domain is introduced, and organs are formulated as platform elements. Included......This PhD thesis has the title Product Platform Modelling. The thesis is about product platforms and visual product platform modelling. Product platforms have gained an increasing attention in industry and academia in the past decade. The reasons are many, yet the increasing globalisation...

  6. Product Platform Replacements

    DEFF Research Database (Denmark)

    Sköld, Martin; Karlsson, Christer

    2012-01-01

    . To shed light on this unexplored and growing managerial concern, the purpose of this explorative study is to identify operational challenges to management when product platforms are replaced. Design/methodology/approach – The study uses a longitudinal field-study approach. Two companies, Gamma and Omega...... replacement was chosen in each company. Findings – The study shows that platform replacements primarily challenge managers' existing knowledge about platform architectures. A distinction can be made between “width” and “height” in platform replacements, and it is crucial that managers observe this in order...... to challenge their existing knowledge about platform architectures. Issues on technologies, architectures, components and processes as well as on segments, applications and functions are identified. Practical implications – Practical implications are summarized and discussed in relation to a framework...

  7. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  8. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    .... The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting...

  9. Central American and Caribbean Citizen Security Platform | IDRC ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Collaborative research platform This initiative will establish a real and virtual space known as the Central American and Caribbean Security Platform. It will bring together the region's scholars, practitioners, attorneys, journalists, and other stakeholders into regular, constructive dialogue with specialists dedicated to finding ...

  10. Forecasting Croatian inbound tourism demand

    OpenAIRE

    Tica, Josip; Kožić, Ivan

    2015-01-01

    The aim of this paper is to present a forecasting model for the overnight stays of foreign tourists in Croatia. Tourism is one of the most important parts of the Croatian economy. It is particularly important in the context of the services sector. Regular and significant surpluses and the consumption of foreign guests are an important element of budget revenues, especially VAT. The ability to forecast the development of inbound tourism demand in a timely manner is crucial for both business...

  11. Preparing for an Uncertain Forecast

    Science.gov (United States)

    Karolak, Eric

    2011-01-01

    Navigating the world of government relations and public policy can be a little like predicting the weather. One can't always be sure what's in store or how it will affect him/her down the road. But there are common patterns and a few basic steps that can help one best prepare for a change in the forecast. Though the forecast is uncertain, early…

  12. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  13. Forecasting market developments

    International Nuclear Information System (INIS)

    Weller, T.

    1997-01-01

    Traditional planning in essence consists of linear extrapolation of established facts and experience. This approach was good enough until recently, when progress would be relatively foreseeable within a stable system. The situation has been changing with developments and modifications in the global economic sector proceeding at accelerated pace, so that conventional planning methods become hopelessly inadequate. The past is of low significance to emerging markets; planners today have to keep abreast with and take into account the possible and emerging influencing factors. Experience is a factor to be replaced by intelligent analysis and conclusion within the framework of system networks. Modern scenario modelling methods are based on this approach: They are able to simulate and forecast a whole range of ''possible futures'', derived from perceivable trends. The article illustrates the novel planning methodology by assessing the future of the renewable energy sources, applying a computerized planning method (vision design) which is based on intelligent comparative analysis of all relevant trends. (Orig./RHM) [de

  14. The development of the Australian Space Forecast Centre (ASFC)

    Science.gov (United States)

    Wilkinson, Phil; Kennewell, John A.; Cole, David

    2018-05-01

    The Ionospheric Prediction Service (IPS) was formed in 1947 to provide monthly prediction services for high frequency (HF) radio, in particular to support HF communications with the United Kingdom. It was quickly recognized that to be effective such a service also had to provide advice when ionospheric storms prevented HF communications from taking place. With the advent of the International Geophysical Year (IGY), short-term forecasts were also required for research programmes and the task of supplying the Australian input to these was given to Frank Cook, of the IPS, while Jack Turner, also of the IPS, supervised the generation of ionospheric maps to support high latitude HF communications. These two important IGY activities formed the platform on which all future IPS services would be built. This paper reviews the development of the Australian Space Forecast Centre (ASFC), which arose from these early origins.

  15. Quantile forecast discrimination ability and value

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Pinson, Pierre; Friederichs, Petra

    2015-01-01

    While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are ...... is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service....

  16. Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

    Science.gov (United States)

    Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

    2017-09-01

    This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

  17. A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

    Science.gov (United States)

    Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

    2010-09-01

    Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

  18. Perfect discipline platform and Promote interactive development

    Directory of Open Access Journals (Sweden)

    Xiang-ming ZENG

    2014-11-01

    Full Text Available Through the questionnaire survey of Marxism’s course construction and Ideological and Political Theory Course in 45 universities, the paper tries to discuss how to enhance the effectiveness of ideological and political theory course by platform of Marxism’s course construction. Research shows that it can enhance the effectiveness of Ideological and Political Theory Course as long as we make full use of platform construction of Marxism’s course, fully display the Marxism’s spirit with the times and the latest achievements in Ideological and political theory course, and Strengthen academic ideological and Political Theory Education. We believe that it can better cultivate socialist builders to achieve the Chinese dream by playing the educational function of Ideological and Political Theory Course.

  19. Effects of Forecasts on the Revisions of Concurrent Seasonally Adjusted Data Using the X-11 Seasonal Adjustment Procedure.

    Science.gov (United States)

    Bobbitt, Larry; Otto, Mark

    Three Autoregressive Integrated Moving Averages (ARIMA) forecast procedures for Census Bureau X-11 concurrent seasonal adjustment were empirically tested. Forty time series from three Census Bureau economic divisions (business, construction, and industry) were analyzed. Forecasts were obtained from fitted seasonal ARIMA models augmented with…

  20. The vacuum platform

    Science.gov (United States)

    McNab, A.

    2017-10-01

    This paper describes GridPP’s Vacuum Platform for managing virtual machines (VMs), which has been used to run production workloads for WLCG and other HEP experiments. The platform provides a uniform interface between VMs and the sites they run at, whether the site is organised as an Infrastructure-as-a-Service cloud system such as OpenStack, or an Infrastructure-as-a-Client system such as Vac. The paper describes our experience in using this platform, in developing and operating VM lifecycle managers Vac and Vcycle, and in interacting with VMs provided by LHCb, ATLAS, ALICE, CMS, and the GridPP DIRAC service to run production workloads.