福建师范大学学报（自然科学版）2011，Vol.27Issue(5)：29-33,5.
基于优化GA属性约简的上证指数预测
Shanghai Composite Index Forecasting Based on Optimized GA Attribute Reduction
摘要
Abstract
An optimized genetic algorithm tor attribute conduction which was based on rough set theories was proposed. Initial population and fitness function of the genetic algorithm were improved according to situation of Shanghai Composite Index forecasting. It performs application of attribute reduction with training set which retrieve 58 attributes data from Shanghai Composite Index in recent ten years. Then, it conducts regression prediction by using parameters optimized SVM to predict stock index on the original dataset and the simplified dataset. Emulation experiment results show that it has better predict precision and time consuming performance by using simplified dataset.关键词
遗传算法/属性约简/上证指数/SVMKey words
genetic algorithm/ attribute reduction/ Shanghai composite index/ SVM分类
信息技术与安全科学引用本文复制引用
严晓明..基于优化GA属性约简的上证指数预测[J].福建师范大学学报（自然科学版）,2011,27(5):29-33,5.基金项目
福建省自然科学基金资助项目(2009J01273) （2009J01273）
