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Hybrid Intelligent Technologies in Energy Demand Forecasting

By (author) Wei-Chiang Hong

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normal price: R 4 534.95

Price: R 4 307.95


| book description |

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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Normally shipped | Available from overseas. Usually dispatched in 14 days
Publisher | Springer Nature Switzerland AG
Published date | 2 Jan 2020
Language |
Format | Hardback
Pages | 179
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-0303-6528-8
Readership Age |
BISAC | business & economics / industries / energy industries


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Normally shipped | Usually dispatched in 3 to 6 weeks as supplier is out of stock
Readership Age |
Normal Price | R 4 582.95
Price | R 4 353.95 | on special |



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