Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM) with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK)-based ELM to develop a systematic approach to generating if-then rules,...

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Bibliographic Details
Main Authors: Chan-Uk Yeom, Keun-Chang Kwak
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Energies
Subjects:
short-term electricity-load forecasting
extreme learning machine
knowledge representation
TSK fuzzy type
hybrid learning
Online Access:https://www.mdpi.com/1996-1073/10/10/1613

Internet

https://www.mdpi.com/1996-1073/10/10/1613

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