svr with hybrid chaotic immune algorithm for seasonal load demand forecastingsvr与混合混沌免疫算法对季节性负荷需求预测.pdfVIP

Energies 2011, 4, 960-977; doi:10.3390/en4060960 OPEN ACCESS energies ISSN 1996-1073 /journal/energies Article SVR with Hybrid Chaotic Immune Algorithm for Seasonal Load Demand Forecasting Wei-Chiang Hong 1,*, Yucheng Dong 2, Chien-Yuan Lai 1, Li-Yueh Chen 3 and Shih-Yung Wei 4 1 Department of Information Management, Oriental Institute of Technology/58 Sec. 2, Sichuan Rd., Panchiao, Taipei 200, Taiwan; E-Mail: fi012@.tw 2 Department of Organization and Management, Xi’an Jiaotong University, Xi’an 710049, China; E-Mail: ycdong@ 3 Department of Global Marketing and Logistics, MingDao University/369 Wen-Hua Rd., Peetow, Changhua 52345, Taiwan; E-Mail: liyuchen@.tw 4 Department Graduate Institute of Finance, National Yunlin University of Science Technology/ 123 Sec. 3, University Rd., Douliou, Yunlin 640, Taiwan; E-Mail: noahsywei@ * Author to whom correspondence should be addressed; E-Mail: samuelsonhong@; Tel.: +886-2-7738-0145 ext. 5316; Fax: +886-2-7738-6310. Received: 24 March 2011; in revised form: 7 June 2011 / Accepted: 14 June 2011 / Published: 17 June 2011 Abstract: Accurate electric load forecasting has become the most important issue in energy management; however, electric load demonstrates a seasonal/cyclic tendency from economic activities or the cyclic nature of climate. The applications of the support vector regression (SVR) model to deal with seasonal/cyclic electric load forecasting have not been widely explored. The purpose of this paper is to present a SVR model which combines the