Hybrid Intelligent Technologies in Energy Demand Forecasting
Release time:2026-06-09
Hits:
- Electronic link:
- https://link.springer.com/book/10.1007/978-3-030-36529-5
- Faculty/School:
- College of Shipbuilding Engineering
- Publisher:
- Springer
- Place of Publication:
- Switzerland
- Description of Publication:
- 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.
- School Sign:
- Harbin Engineering University
- The First Author:
- Wei-Chiang Hong
- Type of Works:
- Monograph
- Publication Design:
- Foreign (overseas) publishing house
- Classification of Disciplines:
- Engineering
- ISBN No.:
- 978-3-030-36528-8
- Translated or Not:
- no
- Date of Publication:
- 2020
