Paper Info
Title
An Ensemble Of Multi-Objective Optimized Fuzzy Regression Models For Short-Term Electric Load Forecasting
Abstract
Electric load forecasting plays an important role in areas like smart grid technologies, efficient energy management and the power system planning. The application of an artificial intelligence techniques (AI) in this field has been confirmed by several studies as vital due to its better performance compared to statistic based models.This paper proposes an innovative algorithm entitled as ensemble of fuzzy linear regression (EFLR) and it bases on fuzzy linear regression combined with boosting mechanism. The fuzzy linear regression is optimized making use of multi objective optimization. The original data of electric load patterns are involved in order to develop and evaluate a load forecasting model as an experimental application of EFLR. The comparison of EFLR with basic fuzzy linear regression revealed improvement of more than 2% in all measures which proves the necessity of ensemble based approach in the fuzzy linear regression.
Year
Venue
Keywords
2017
2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI)
Multi objective optimization, fuzzy linear regression, ensemble forecasting, electric load forecasting, boosted fuzzy regression
Field
DocType
Citations 
Mathematical optimization,Smart grid,Statistic,Ensemble forecasting,Electrical load,Efficient energy use,Computer science,Electric power system,Multi-objective optimization,Boosting (machine learning)
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
tomas vantuch103.38
Michal Prilepok2326.45