系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2010年
6期
1027~1033
,共null页
经验模态分解 股市预测 混沌分析 神经网络
經驗模態分解 股市預測 混沌分析 神經網絡
경험모태분해 고시예측 혼돈분석 신경망락
empirical mode decomposition; stock market prediction; chaos analysis; neural network
应用EMD分解算法、混沌分析和神经网络理论提出了一种中国股票市场建模及预测的EMD神经网络模型.首先应用EMD分解算法把原始股市时间序列分解成不同尺度的基本模态分量,并在此基础上进一步分析,表明中国股市存在混沌特性;再经混沌分析和神经网络进行组合预测,提高了模型对多种目标函数的学习能力,有效提高了预测精度.实验表明：与现有方法相比,该方法具有较高的精度.
應用EMD分解算法、混沌分析和神經網絡理論提齣瞭一種中國股票市場建模及預測的EMD神經網絡模型.首先應用EMD分解算法把原始股市時間序列分解成不同呎度的基本模態分量,併在此基礎上進一步分析,錶明中國股市存在混沌特性;再經混沌分析和神經網絡進行組閤預測,提高瞭模型對多種目標函數的學習能力,有效提高瞭預測精度.實驗錶明：與現有方法相比,該方法具有較高的精度.
응용EMD분해산법、혼돈분석화신경망락이론제출료일충중국고표시장건모급예측적EMD신경망락모형.수선응용EMD분해산법파원시고시시간서렬분해성불동척도적기본모태분량,병재차기출상진일보분석,표명중국고시존재혼돈특성;재경혼돈분석화신경망락진행조합예측,제고료모형대다충목표함수적학습능력,유효제고료예측정도.실험표명：여현유방법상비,해방법구유교고적정도.
Following empirical mode decomposition（EMD）,chaos analysis and neural network theory,a method is presented to model and forecast stock market.First,using EMD theory,the stock market time serial is decomposed into many intrinsic modal functions（IMF） which can significantly represent potential information of original time serial,and the further analysis of IMF indicates that China stock market exists a chaos feature.Then,by using chaos theory and neural network,the forecasting models are established to forecast the IMF respectively.By these means,the model can be improved to learn various objective function and more precious prediction can be obtained.The experiments show that the presented method can effectively improve the prediction accuracy.
