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The Resource Intelligent Energy Demand Forecasting, by Wei-Chiang Hong, (electronic resource)

Intelligent Energy Demand Forecasting, by Wei-Chiang Hong, (electronic resource)

Label
Intelligent Energy Demand Forecasting
Title
Intelligent Energy Demand Forecasting
Statement of responsibility
by Wei-Chiang Hong
Creator
Contributor
Subject
Language
eng
Summary
As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.  Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools
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Image bit depth
0
Literary form
non fiction
Series statement
Lecture Notes in Energy,
Series volume
10
Intelligent Energy Demand Forecasting, by Wei-Chiang Hong, (electronic resource)
Label
Intelligent Energy Demand Forecasting, by Wei-Chiang Hong, (electronic resource)
Link
http://libproxy.rpi.edu/login?url=http://dx.doi.org/10.1007/978-1-4471-4968-2
Publication
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Antecedent source
mixed
Color
not applicable
Contents
1.Introduction -- 2.Modeling for Energy Demand Forecasting -- 3.Evolutionary Algorithms in SVR{u2019}s Parameters Determination -- 4.Chaos/Cloud Theories to Avoid Trapping into Local Optimum -- 5.Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting
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https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781447149682&userID=ebsco-test&password=ebsco-test
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unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3393529'}
Extent
XIII, 189 p. 70 illus.
File format
multiple file formats
Form of item
electronic
Isbn
9781447149682
Level of compression
uncompressed
Other physical details
digital.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote

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