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Intelligent energy demand forecasting / / Wei-Chiang Hong



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Autore: Hong Wei-Chiang Visualizza persona
Titolo: Intelligent energy demand forecasting / / Wei-Chiang Hong Visualizza cluster
Pubblicazione: London : , : Springer, , 2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (xiii, 189 pages) : illustrations (some color)
Disciplina: 333.7913
Soggetto topico: Power resources - Forecasting
Note generali: "ISSN: 2195-1284."
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: 1.Introduction -- 2.Modeling for Energy Demand Forecasting -- 3.Evolutionary Algorithms in SVR’s Parameters Determination -- 4.Chaos/Cloud Theories to Avoid Trapping into Local Optimum -- 5.Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting.
Sommario/riassunto: 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.
Titolo autorizzato: Intelligent Energy Demand Forecasting  Visualizza cluster
ISBN: 1-4471-4968-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910437776603321
Lo trovi qui: Univ. Federico II
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Serie: Lecture notes in energy ; ; 10.