Hybrid Intelligent Technologies in Energy Demand Forecasting (Hardcover, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	2020
First published:	2020
Authors:	Wei-Chiang Hong
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	179
Edition:	1st ed. 2020
ISBN-13:	978-3-03-036528-8
Categories:	Books > Professional & Technical > Energy technology & engineering > Alternative & renewable energy sources & technology Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Non-linear science Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-036528-X
Barcode:	9783030365288

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