Title :
An Intelligent Power Factor Correction Approach Based on Linear Regression and Ridge Regression Methods
Author :
Bayindir, Ramazan ; Gok, Murat ; Kabalci, Ersan ; Kaplan, Orhan
Author_Institution :
Electr. Educ. Dept., Gazi Univ., Ankara, Turkey
Abstract :
This study introduces an intelligent power factor correction approach based on Linear Regression (LR) and Ridge Regression (RR) methods. The 10-fold Cross Validation (CV) test protocol has been used to evaluate the performance. The best test performance has been obtained from the LR in comparison with RR. The empirical results have evaluated that the selected intelligent compensators developed in this work might overcome the problems met in the literature providing accurate, simple and low-cost solution for compensation.
Keywords :
power factor correction; regression analysis; 10-fold cross validation test protocol; intelligent power factor correction; linear regression methods; ridge regression methods; Capacitors; Fuzzy logic; Linear regression; Mathematical model; Power factor correction; Reactive power; Synchronous motors; Intelligent Power Factor Correction; Linear Regression Method; Ridge Regression Method;
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
DOI :
10.1109/ICMLA.2011.34