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Hybrid Intelligent Technologies in Energy Demand Forecasting

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Hybrid Intelligent Technologies in Energy Demand Forecasting/ by Wei-Chiang Hong.
作者:	Hong, Wei-Chiang.
面頁冊數:	XII, 179 p. 60 illus., 51 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Renewable and Green Energy. -
電子資源:	https://doi.org/10.1007/978-3-030-36529-5
ISBN:	9783030365295

Hybrid Intelligent Technologies in Energy Demand Forecasting
Hong, Wei-Chiang.

Hybrid Intelligent Technologies in Energy Demand Forecasting[electronic resource] /by Wei-Chiang Hong. - 1st ed. 2020. - XII, 179 p. 60 illus., 51 illus. in color.online resource.

Introduction -- Modeling for Energy Demand Forecasting -- Data Pre-processing Methods -- Hybridizing Meta-heuristic Algorithms with CMM and QCM for SVR’s Parameters Determination -- Hybridizing QCM with Dragonfly algorithm to Enrich the Solution Searching Be-haviors -- Phase Space Reconstruction and Recurrence Plot Theory .

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.

ISBN: 9783030365295

Standard No.: 10.1007/978-3-030-36529-5doiSubjects--Topical Terms:

683875
Renewable and Green Energy.

LC Class. No.: HD9502-9502.5

Dewey Class. No.: 333.79

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