Forecasting

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Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. (Wikipedia.org)






Conferences related to Forecasting

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2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


Oceans 2020 MTS/IEEE GULF COAST

To promote awareness, understanding, advancement and application of ocean engineering and marine technology. This includes all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.

  • OCEANS 2018 MTS/IEEE Charleston

    Ocean, coastal, and atmospheric science and technology advances and applications

  • OCEANS 2017 - Anchorage

    Papers on ocean technology, exhibits from ocean equipment and service suppliers, student posters and student poster competition, tutorials on ocean technology, workshops and town meetings on policy and governmental process.

  • OCEANS 2016

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 500 technical papers and 150 -200 exhibits.

  • OCEANS 2015

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2014

    The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2013

    Three days of 8-10 tracks of technical sessions (400-450 papers) and concurent exhibition (150-250 exhibitors)

  • OCEANS 2012

    Ocean related technology. Tutorials and three days of technical sessions and exhibits. 8-12 parallel technical tracks.

  • OCEANS 2011

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2010

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2009

  • OCEANS 2008

    The Marine Technology Society (MTS) and the Oceanic Engineering Society (OES) of the Institute of Electrical and Electronic Engineers (IEEE) cosponsor a joint conference and exposition on ocean science, engineering, education, and policy. Held annually in the fall, it has become a focal point for the ocean and marine community to meet, learn, and exhibit products and services. The conference includes technical sessions, workshops, student poster sessions, job fairs, tutorials and a large exhibit.

  • OCEANS 2007

  • OCEANS 2006

  • OCEANS 2005

  • OCEANS 2004

  • OCEANS 2003

  • OCEANS 2002

  • OCEANS 2001

  • OCEANS 2000

  • OCEANS '99

  • OCEANS '98

  • OCEANS '97

  • OCEANS '96


2019 IEEE Industry Applications Society Annual Meeting

The Annual Meeting is a gathering of experts who work and conduct research in the industrial applications of electrical systems.


2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

International Geosicence and Remote Sensing Symposium (IGARSS) is the annual conference sponsored by the IEEE Geoscience and Remote Sensing Society (IEEE GRSS), which is also the flagship event of the society. The topics of IGARSS cover a wide variety of the research on the theory, techniques, and applications of remote sensing in geoscience, which includes: the fundamentals of the interactions electromagnetic waves with environment and target to be observed; the techniques and implementation of remote sensing for imaging and sounding; the analysis, processing and information technology of remote sensing data; the applications of remote sensing in different aspects of earth science; the missions and projects of earth observation satellites and airborne and ground based campaigns. The theme of IGARSS 2019 is “Enviroment and Disasters”, and some emphases will be given on related special topics.


2019 IEEE Milan PowerTech

PowerTech is the IEEE PES anchor conference in Europe and has been attended by hundreds of delegates from around the world. It will be an international forum with programme for individuals working in industry and academia, to network, exchange ideas, and discuss the results of their research and development work.

  • 2017 IEEE Manchester PowerTech

    this is IEEE PES anchor conference in Europe covering all areas of electrical power engineering

  • 2015 IEEE Eindhoven PowerTech

    This conference will continue the tradition of the PowerTech conferences held in odd years in Athens, Stockholm, Budapest, Porto, Bologna, St. Petersburg, Lausanne, Bucharest, Trondheim and Grenoble.PowerTech is the anchor conference of the IEEE Power Engineering Society in Europe. It is intended to provide a forum, in the European geographical area, for scientists and engineers interested in electric power engineering to exchange ideas, results of their scientific work, to learn from each other as well as to establish new friendships and rekindle existing ones. Student participation in Power Tech provides an important ingredient toward the event’s success: a special award, the Basil Papadias Award, is presented to the author of the best student paper at each edition. The Power Engineering Society of IEEE organized similar conferences in other parts of the world, such as PowerCon, in the Asia-Pacific region.

  • 2013 IEEE Grenoble PowerTech

    PowerTech is the anchor conference of the IEEE Power & Energy Society in Europe. It is intended to provide a forum for electric power engineering scientists and engineers to share ideas, results of their scientific work, to learn from each other as well as to establish new friendships and maintain existing ones.

  • 2011 IEEE Trondheim PowerTech

    PowerTech is the anchor conference of the IEEE Power & Energy Society in Europe. It is intended to provide a forum for electric power engineering scientists and engineers to share ideas, results of their scientific work and to learn from each other.

  • 2009 IEEE Bucharest Power Tech

    PowerTech is the anchor conference of the IEEE-PES in Europe. It is intended to provide a forum for scientists and engineers interested in electric power engineering to share ideas, results of their scientific work, to learn from each other as well as to establish new friendships and rekindle existing ones.

  • 2007 IEEE Power Tech

  • 2005 IEEE Russia Power Tech

  • 2003 Bologna Power Tech


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Periodicals related to Forecasting

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computers, IEEE Transactions on

Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...


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Most published Xplore authors for Forecasting

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Xplore Articles related to Forecasting

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Density Forecasting for Long-Term Peak Electricity Demand

IEEE Transactions on Power Systems, 2010

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for ...


Wind Speed Forecasting Based on Support Vector Machine with Forecasting Error Estimation

2007 International Conference on Machine Learning and Cybernetics, 2007

An approach of a mean hourly wind speed forecasting in wind farm is proposed in this paper. It applies support vector regression as well as forecasting error estimation. Firstly, support vector regression is applied to the mean hourly wind speed forecasting. Secondly, a support vector classifier is trained to estimate the forecasting error. Finally, the forecasting results can tailor themselves ...


The short-term electric load forecasting grid model based on MDRBR algorithm

2006 IEEE Power Engineering Society General Meeting, 2006

In load forecasting of a bulk power system, the geographical scope of forecasting region is large, the main electrical load effecting factors in sub districts are different greatly. So it is very significance to establish different load forecasting model according to self-feature of each sub district of a large area, by which the forecasting load is closer to the fact ...


Secondary Forecasting Based on Deviation Analysis for Short-Term Load Forecasting

IEEE Transactions on Power Systems, 2011

Short-term load forecasting (STLF) is the basis of power system planning and operation. With regard to the fast-growing load in China, a novel two-stage hybrid forecasting method is proposed in this paper. In the first stage, daily load is forecasted by time-series methods; in the second stage, the deviation caused by time-series methods is forecasted considering the impact of relative ...


Development of 24-hour optimal scheduling algorithm for energy storage system using load forecasting and renewable energy forecasting

2017 IEEE Power & Energy Society General Meeting, 2017

This paper presents the 24-hour optimal scheduling algorithm for Energy Storage System (ESS) using load forecasting and renewable energy forecasting in South Korea electricity tariff structure. For load forecasting and renewable energy forecasting, 24-hour multivariate forecasting model combining very-short-term and short-term forecasting models is developed. Then, load and renewable forecasts are input to the optimal ESS scheduling algorithm. The objective ...


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Educational Resources on Forecasting

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IEEE-USA E-Books

  • Density Forecasting for Long-Term Peak Electricity Demand

    Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007-2008.

  • Wind Speed Forecasting Based on Support Vector Machine with Forecasting Error Estimation

    An approach of a mean hourly wind speed forecasting in wind farm is proposed in this paper. It applies support vector regression as well as forecasting error estimation. Firstly, support vector regression is applied to the mean hourly wind speed forecasting. Secondly, a support vector classifier is trained to estimate the forecasting error. Finally, the forecasting results can tailor themselves to the estimated forecasting error, and thus improve the forecasting precision. To test the approach, three-year data from a wind farm is given as a support vector regression process, and a support vector classifier is trained in addition to estimate the forecasting error. Experimental results show that the proposed approach can achieve higher quality of mean hourly wind speed forecasting; also it has lower mean square error compared with the traditional support vector regression forecasting.

  • The short-term electric load forecasting grid model based on MDRBR algorithm

    In load forecasting of a bulk power system, the geographical scope of forecasting region is large, the main electrical load effecting factors in sub districts are different greatly. So it is very significance to establish different load forecasting model according to self-feature of each sub district of a large area, by which the forecasting load is closer to the fact load than establishing one model in whole to forecast electrical load. This paper presents a grid model in terms of geographical division for short-term load forecasting in a bulk power system. The subset model in each geographical grid, considering its own historical loads and meteorological conditions, is more effective and could lead to more accurate results. Therefore, every subnet model is established based on the mining default rules on rough sets (MDRBR) algorithm. First, the MDRBR algorithm is discussed, and the constructing process of the multi-layered rule-network of daily load forecasting is then analyzed in detail. Furthermore, the whole process of load forecasting based on the MDRBR algorithm is presented. Finally, an example using actual historical data shows that the grid forecasting model can yield high accurate results, reduce noises effectively, and is efficient in computation and rule searching

  • Secondary Forecasting Based on Deviation Analysis for Short-Term Load Forecasting

    Short-term load forecasting (STLF) is the basis of power system planning and operation. With regard to the fast-growing load in China, a novel two-stage hybrid forecasting method is proposed in this paper. In the first stage, daily load is forecasted by time-series methods; in the second stage, the deviation caused by time-series methods is forecasted considering the impact of relative factors, and then is added to the result of the first stage. Different from other conventional methods, this paper does an in-depth analysis on the impact of relative factors on the deviation between actual load and the forecasting result of traditional time-series methods. On the basis of this analysis, an adaptive algorithm is proposed to perform the second stage which can be used to choose the most appropriate algorithm among linear regression, quadratic programming, and support vector machine (SVM) according to the characteristic of historical data. These ideas make the forecasting procedure more accurate, adaptive, and effective, comparing with SVM and other prevalent methods. The effectiveness has been demonstrated by the experiments and practical application in China.

  • Development of 24-hour optimal scheduling algorithm for energy storage system using load forecasting and renewable energy forecasting

    This paper presents the 24-hour optimal scheduling algorithm for Energy Storage System (ESS) using load forecasting and renewable energy forecasting in South Korea electricity tariff structure. For load forecasting and renewable energy forecasting, 24-hour multivariate forecasting model combining very-short-term and short-term forecasting models is developed. Then, load and renewable forecasts are input to the optimal ESS scheduling algorithm. The objective of this algorithm is to maximize the customer's profit by energy arbitrage, minimize the peak load to reduce the contract power, and minimize the charging/discharging cycles to lengthen the expected life of ESS. The effectiveness of this algorithm is validated in case study.

  • GP-based temperature forecasting for electric load forecasting

    This paper proposes a new probabilistic method for maximum temperature forecasting in short-term electrical load forecasting. The proposed method makes use of Gaussian process (GP)of the kernel machine to evaluate the predicted temperature. In recent years, electric power markets become more deregulated and competitive. The power system players are concerned with maximizing a profit while minimizing a risk in the power markets. To improve the accuracy of load forecasting model, it is a key to predict the weather conditions of input variables precisely. In other words, it is meaningful to consider the uncertainty of the predicted temperature in short-term load forecasting. The proposed method aims at extending temperature forecasting for the average point into that for the posterior distribution to handle the uncertainty of temperature forecasting. The proposed method is successfully applied to real data of temperature in Tokyo. A comparison is made between the proposed and the conventional methods such as MLP (multi-layered perceptron), RBFN (radial basis function network) and SVR (support vector regression).

  • Mechanism for a New Demand Forecasting Paradigm 'Individual Demand Forecasting'

    Traditional opinions suggested that it is impossible to forecast individual demand. A mechanism for individual demand forecasting to improve forecasting accuracy is elicited and described based on tenets, tactics, and tools of individual demand forecasting, The mechanism consists of three sub-mechanisms (1) sub-mechanism via extending information base, (2) sub-mechanism via information processing, and (3) sub-mechanism via providing forecasts and other information to customers.

  • Notice of Retraction<br>Research on comparison and application of forecasting methods in the communications and transportation

    Forecasting is inferring its future according to evolution law of the things and it can offer scientific basis for decision-making. This paper first introduces four popular forecasting methods, that is time series forecasting, grey forecasting, regression forecasting and combined forecasting, then applies them to the traffic volume and freight volume in Tianjin's transportation, at last, compares of the four methods and give an appraisement for their application.

  • A hybrid handover forecasting mechanism based on fuzzy forecasting model in cellular networks

    As the increasing demand for mobile communications and the shrinking of the coverage of cells, handover mechanism will play an important role in future wireless networks to provide users with seamless mobile communication services. In order to guarantee the user experience, the handover decision should be made timely and reasonably. To achieve this goal, this paper presents a hybrid handover forecasting mechanism, which contains long-term and short-term forecasting models. The proposed mechanism could cooperate with the standard mechanisms, and improve the performance of standard handover decision mechanisms. Since most of the parameters involved are imprecise, fuzzy forecasting model is applied for dealing with predictions of them. The numerical results indicate that the mechanism could significantly decrease the rate of ping-pong handover and the rate of handover failure.

  • On accuracy of demand forecasting and its extension to demand composition forecasting using artificial intelligence based methods

    Accurate prediction of the load plays an indispensable role in power system planning and electricity market analysis. Load forecasting based on artificial intelligence (AI) techniques received a significant attention in the past and it is rapidly developing because of its high accuracy. Some of the AI based methodologies for load forecasting have already been adopted and widely used by the industry. This paper presents for the first time comparative analysis of the state of the art artificial neural network (ANN) based and adaptive neuro-based fuzzy inference system (ANFIS) based load forecasting methodologies in the same operation environment. Furthermore, the paper implements the extension of forecasting tools to forecast hourly load composition in addition to overall load at a bus. It is confirmed that either approach is very effective in load forecasting and that they have comparable performance providing appropriate setting of relevant parameters. It also proves that the approach can be successfully extended to hourly load composition forecasting and the load composition forecasting error is less than 10% at most of the time during the day.



Standards related to Forecasting

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No standards are currently tagged "Forecasting"