%0 Journal Article
%T Study on chaotic time series prediction based on genetic algorithm<br>遗传算法在混沌时间序列预测中的应用研究*
%A XIANG Chang-sheng
%A ZHOU Zi-ying
%A YU Xi-lin
%A ZHANG Lin-fengc
%A <br>向昌盛
%A 周子英
%A 余喜林
%A 张林峰c
%J 计算机应用研究
%D 2011
%I 
%X In chaotic time series prediction, phase space reconstruction and prediction model parameters optimization were two key steps, used the relationship between phase space reconstruction and prediction model parameters to improve the model performance, proposed a synchronous optimization method of chaotic time series parameters based on genetic algorithm. In the synchronous optimization method, used PSR and least square support vector machine parameters as genetic algorithm chromosomes while used prediction accuracy as the evaluation function of genetic algorithm, solved the synchronous optimization problem by genetic algorithm. Tested the proposed method by the chaotic time series. The experiment results show that the proposed algorithm improves the prediction accurate and reduces the computational complexity compared with the separate optimization methods.
%K chaotic time series
%K phase space reconstruction
%K least square support vector machine(LSSVM)
%K genetic algorithm<br>混沌时间序列
%K 相空间重构
%K 最小二乘支持向量机
%K 遗传算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F32C7DEF351C88CCB997E792E2EBDB3B&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=5D311CA918CA9A03&sid=03BD78E6C243EDEA&eid=D28BA532798ECC49&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=26