Hybrid Intelligent Technologies in Energy Demand Forecasting

  • Wei-Chiang Hong

Table of contents

About this book


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.


Support Vector Regression Energy Demand Forecasting Meta-Heuristic Algorithms Chaotic Mapping Mechanism Quantum Computing Mechanism Recurrent Neural Network Mechanism Phase Space Reconstruction Recurrence Plot Theory

Authors and affiliations

  • Wei-Chiang Hong
    • 1
  1. 1.Department of Information ManagementOriental Institute of TechnologyNew TaipeiTaiwan

Bibliographic information

  • DOI
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Energy
  • Print ISBN 978-3-030-36528-8
  • Online ISBN 978-3-030-36529-5
  • Buy this book on publisher's site