Hybrid Intelligent Technologies in Energy Demand Forecasting

Hybrid Intelligent Technologies in Energy Demand Forecasting

1st Edition 2020

Hardback (02 Jan 2020)

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Publisher's Synopsis

This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. 

It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. 

The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.


Book information

ISBN: 9783030365288
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
Edition: 1st Edition 2020
Language: English
Number of pages: 179
Weight: 459g
Height: 235mm
Width: 155mm
Spine width: 13mm