期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 37, 期 2, 页码 1776-1783出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2009.07.054
关键词
Support vector machine; Chaos theory; Embedded; Genetic algorithm; Demand forecasting
类别
资金
- National Natural Science Foundation of China [60904043]
- China Postdoctoral Science Foundation [20090451152]
- Jiangsu Planned Projects for Post-doctoral Research Funds [0901023C]
Aiming at the complex system with multi-dimension, small samples, nonlinearity and multi-apex. and combining chaos theory. genetic algorithm with support vector machine (SVM), a kind of chaotic SVM named Cv-SVM short for chaotic v-support vector machine is proposed in this paper. Cv-SVM, whose constraint conditions are less than those of the standard v-SVM by one, is proved to satisfy the structure risk minimum rule under the condition of probability Moreover there is no parameter b in the regression function of Cv-SVM. And then, an intelligence-forecasting method is put forward. The results of application in car demand forecasting show that the forecasting method based on Cv-SVM is feasible and effective. (C) 2009 Elsevier Ltd. All rights reserved.
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