Artículos relacionados a Intelligent Energy Demand Forecasting: 10 (Lecture...
Sinopsis
As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand.
Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.
Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Wei-Chiang Samuelson Hong is an associate professor in the Department of Information Management at the Oriental Institute of Technology, Taiwan. His research interests mainly include computational intelligence (neural networks and evolutionary computation), and application of forecasting technology (ARIMA, support vector regression, and chaos theory), and tourism competitiveness evaluation and management. Dr. Hong’s articles have been published in Applied Mathematics and Computation, Applied Mathematical Modelling, Applied Soft Computing, Control and Cybernetics, Decision Support Systems, Electric Power Systems Research, Energy, Energies, Energy Conversion and Management, Energy Policy, IEEE Transactions on Fuzzy Systems, International Journal of Electrical Power & Energy Systems, Journal of Combinatorial Optimization, Journal of Systems and Software, Journal of Systems Engineering and Electronics, Mathematical Problems in Engineering, Neural Computing and Applications, and Neurocomputing, among others. Dr. Hong is currently on the editorial board of several journals, including International Journal of Applied Evolutionary Computation, Neurocomputing, Applied Soft Computing, Mathematical Problems in Engineering, and Energy Sources Part B: Economics, Planning, and Policy.
Dr. Hong serves as the program committee of various international conferences including premium ones such as IEEE CEC, IEEE CIS, IEEE ICNSC, IEEE SMC, IEEE CASE, and IEEE SMCia, etc.. In May 2012, his paper had been evaluated as “Top Cited Article 2007-2011” by Elsevier Publisher (Netherlands). In Sep. 2012, once again, his paper had been indexed in ISI Essential Science Indicator database as Highly Cited Papers, in the meanwhile, he also had been awarded as the Model Teacher Award by Taiwan PrivateEducation Association.
Dr. Hong is a senior member of IIE and IEEE. He is indexed in the list of Who's Who in the World (25th-30th Editions), Who's Who in Asia (2nd Edition), and Who's Who in Science and Engineering (10th and 11th Editions).
De la contraportada
As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand.
Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.
Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.
"Sobre este título" puede pertenecer a otra edición de este libro.
Comprar nuevo
Ver este artículo
EUR 92,27
EUR 19,49 gastos de envío desde Alemania a España
Destinos, gastos y plazos de envíoOtras ediciones populares con el mismo título
Resultados de la búsqueda para Intelligent Energy Demand Forecasting: 10 (Lecture...
Imagen de archivo
Intelligent Energy Demand Forecasting
Publicado por
Springer London, 2013
ISBN 10: 144714967X
ISBN 13: 9781447149675
Antiguo o usado
Tapa dura
Librería: Buchpark, Trebbin, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: Sehr gut. Zustand: Sehr gut | Seiten: 204 | Sprache: Englisch | Produktart: Sonstiges. Nº de ref. del artículo: 23479735/12
Cantidad disponible: 1 disponibles
Imagen del vendedor
Intelligent Energy Demand Forecasting
Impresión bajo demandaLibrería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools Illustrates how hybrid evolutionary algorithms and some new approaches are improving existing algorithms . Nº de ref. del artículo: 4185117
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Intelligent Energy Demand Forecasting
Publicado por
Springer London Mrz 2013, 2013
ISBN 10: 144714967X
ISBN 13: 9781447149675
Nuevo
Tapa dura
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools. 204 pp. Englisch. Nº de ref. del artículo: 9781447149675
Cantidad disponible: 2 disponibles
Imagen de archivo
Intelligent Energy Demand Forecasting (Lecture Notes in Energy, 10)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9781447149675_new
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Intelligent Energy Demand Forecasting
Publicado por
Springer London, Springer London, 2013
ISBN 10: 144714967X
ISBN 13: 9781447149675
Nuevo
Tapa dura
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools. Nº de ref. del artículo: 9781447149675
Cantidad disponible: 1 disponibles
Imagen del vendedor
Intelligent Energy Demand Forecasting
Publicado por
Springer London, Springer London Mär 2013, 2013
ISBN 10: 144714967X
ISBN 13: 9781447149675
Nuevo
Tapa dura
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand.Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methodsto provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 204 pp. Englisch. Nº de ref. del artículo: 9781447149675
Cantidad disponible: 2 disponibles
Imagen de archivo
Intelligent Energy Demand Forecasting
Impresión bajo demandaLibrería: THE SAINT BOOKSTORE, Southport, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 509. Nº de ref. del artículo: C9781447149675
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Intelligent Energy Demand Forecasting (Lecture Notes in Energy, 10)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: ABLIING23Mar2411530317079
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Intelligent Energy Demand Forecasting (Lecture Notes in Energy, 10)
Librería: Mispah books, Redhill, SURRE, Reino Unido
Calificación del vendedor: 4 de 5 estrellas
Hardcover. Condición: Like New. Like New. book. Nº de ref. del artículo: ERICA773144714967X6
Cantidad disponible: 1 disponibles