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Received:February 27, 2015 Revised:April 02, 2015
Received:February 27, 2015 Revised:April 02, 2015
中文摘要: 针对股票价格的动态性及非线性等特点, 提出了基于改进遗传算法(Genetic Algorithm, GA)优化参数的支持向量回归机(Support Vector Regression, SVR)股价预测模型. 首先将选取的股票价格样本进行小波去噪处理, 然后将经过改进GA优化参数的SVR模型对去噪后的数据进行预测及评价. 结果证明, 改进小波-GA-SVR模型具有良好的预测效果, 对股票价格的预测研究具有一定的意义.
Abstract:Aiming to the dynamics and nonlinearities of stock price, a stock price prediction model that based on support vector regression (SVR) with parameters optimized by improved genetic algorithm (GA) was proposed. First, the wavelet was used to de-noise the samples of stock price. Then the SVR model whose parameters were optimized by improved GA was utilized to predict and assess the data de-noised by wavelet. The result demonstrated that the improved wavelet-GA-SVR model has good prediction effect, and it is significant to the study of the prediction of stock price.
keywords: wavelet denoising genetic algorithm (GA) support vector regression(SVR) stock price prediction
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基金项目:国家自然科学基金(61179011);福建自然科学基金(2010J01327)
引用文本：
孙秋韵,刘金清,刘引,吴庆祥.基于改进GA参数优化的SVR股价预测模型.计算机系统应用,2015,24(9):29-34
QIU Yun-Sun,LIU Jin-Qing,LIU Yin,WU Qing-Xiang.Stock Price Prediction Model Based on SVR with Parameters Optimized by Improved GA.COMPUTER SYSTEMS APPLICATIONS,2015,24(9):29-34
孙秋韵,刘金清,刘引,吴庆祥.基于改进GA参数优化的SVR股价预测模型.计算机系统应用,2015,24(9):29-34
QIU Yun-Sun,LIU Jin-Qing,LIU Yin,WU Qing-Xiang.Stock Price Prediction Model Based on SVR with Parameters Optimized by Improved GA.COMPUTER SYSTEMS APPLICATIONS,2015,24(9):29-34
