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Hybrid Intelligent Technologies in Energy Demand Forecasting
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Hybrid Intelligent Technologies in Energy Demand Forecasting

2020 ed.

Book Details

Format Paperback / Softback
ISBN-10 303036531X
ISBN-13 9783030365318
Edition 2020 ed.
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Jan 2nd, 2021
Print length 179 Pages
Weight 308 grams
Dimensions 23.50 x 15.50 x 1.50 cms
Ksh 16,200.00
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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.

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.



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