| 書目名稱 | Intelligent Energy Demand Forecasting |
| 編輯 | Wei-Chiang Hong |
| 視頻video | http://file.papertrans.cn/470/469655/469655.mp4 |
| 概述 | Provides more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.Illustrates how hybrid evolutionary algorithms and some new appr |
| 叢書名稱 | Lecture Notes in Energy |
| 圖書封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2013 |
| 關(guān)鍵詞 | Chaos theory; Energy forecasting; Evolutionary algorithms; Short term forecasting; Support vector regres |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4471-4968-2 |
| isbn_softcover | 978-1-4471-5930-8 |
| isbn_ebook | 978-1-4471-4968-2Series ISSN 2195-1284 Series E-ISSN 2195-1292 |
| issn_series | 2195-1284 |
| copyright | Springer-Verlag London 2013 |
|Archiver|手機版|小黑屋|
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