Energy Applications of Extreme Learning Machines

Alternative Title

Extreme Learning Machines for Energy Applications

Author

Donald C. Wunsch, Missouri University of Science and TechnologyFollow

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.

Recommended Citation

D. C. Wunsch, "Energy Applications of Extreme Learning Machines," Proceedings of The International Conference on Extreme Learning Machines, ELM2016 (2016: Dec. 13-15, Marina Bay Sands, Singapore), Dec 2016.

Meeting Name

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

Department(s)

Electrical and Computer Engineering

Research Center/Lab(s)

Center for High Performance Computing Research

Comments

Keynote Presentation

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Publication Date

01 Dec 2016