Energy Applications of Extreme Learning Machines

Donald C. Wunsch

Energy Applications of Extreme Learning Machines

Donald C. Wunsch

Research output: Contribution to journal › Article › peer-review

Abstract

Energy applications are a fascinating source of prediction and other problems that exhibit nonlinearities, time delays, and nonstationary statistics. This makes them an ideal testbed for Extreme Learning Machines approaches. Some illustrative examples are reviewed, and some novel regulation approaches to condition data for ELM are also discussed.

Original language	American English
Journal	Proceedings of The International Conference on Extreme Learning Machines, ELM2016 (2016: Dec. 13-15, Marina Bay Sands, Singapore)
State	Published - Dec 1 2016

Disciplines

Electrical and Computer Engineering
Numerical Analysis and Scientific Computing

Access to Document

http://www.ntu.edu.sg/home/egbhuang/elm2016/keynotes.html

Cite this

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title = "Energy Applications of Extreme Learning Machines",

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year = "2016",

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AU - Wunsch, Donald C.

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N2 - Energy applications are a fascinating source of prediction and other problems that exhibit nonlinearities, time delays, and nonstationary statistics. This makes them an ideal testbed for Extreme Learning Machines approaches. Some illustrative examples are reviewed, and some novel regulation approaches to condition data for ELM are also discussed.

AB - Energy applications are a fascinating source of prediction and other problems that exhibit nonlinearities, time delays, and nonstationary statistics. This makes them an ideal testbed for Extreme Learning Machines approaches. Some illustrative examples are reviewed, and some novel regulation approaches to condition data for ELM are also discussed.

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M3 - Article

JO - Proceedings of The International Conference on Extreme Learning Machines, ELM2016 (2016: Dec. 13-15, Marina Bay Sands, Singapore)

JF - Proceedings of The International Conference on Extreme Learning Machines, ELM2016 (2016: Dec. 13-15, Marina Bay Sands, Singapore)

ER -

Energy Applications of Extreme Learning Machines

Abstract

Disciplines

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