Hybrid Intelligent Technologies in Energy Demand Forecasting e-bog
875,33 DKK
(inkl. moms 1094,16 DKK)
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 b...
E-bog
875,33 DKK
Forlag
Springer
Udgivet
1 januar 2020
Genrer
PHJ
Sprog
English
Format
pdf
Beskyttelse
LCP
ISBN
9783030365295
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.