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Intelligent Energy Demand Forecasting [Paperback]

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  • Category: Books (Business & Economics)
  • Author:  Hong, Wei-Chiang
  • Author:  Hong, Wei-Chiang
  • ISBN-10:  1447159306
  • ISBN-10:  1447159306
  • ISBN-13:  9781447159308
  • ISBN-13:  9781447159308
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2015
  • Pub Date:  01-Mar-2015
  • SKU:  1447159306-11-SPRI
  • SKU:  1447159306-11-SPRI
  • Item ID: 100807035
  • List Price: $109.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jul 08 to Jul 10
  • Notes: Brand New Book. Order Now.

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.

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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.

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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.

This book offers approaches and methods to calculate optimal electric energy allocation, using evolutionary algorithms and intelligent analytical tools to improve the accuracy of demand forecasting. Focuses on improving the drawbacks of existing algorithms.

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.

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Evolutionary algorithms and intelligent analyticall3%

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