基于AIW-PSO小波神经网络的上证指数预测  

Shanghai Stock Index Prediction Based on AIW-PSO Wavelet Neural Network

作　　者：郝杰[1] 苏越良[1] 

机构地区：[1]华南理工大学工商管理学院,广州510641

出　　处：《价值工程》2014年第8期6-8,共3页Value Engineering

基　　金：国家自然科学基金资助项目(71071057)

摘　　要：针对小波神经网络(Wavelet Neural Network,WNN)的学习算法的不足,采用一种自适应惯性权重粒子群优化算法(Adaptive Inertia Weight Particle Swarm Optimization,AIW-PSO)作为小波神经网络的学习算法,建立AIW-PSO小波神经网络模型对上证指数进行预测,并将预测结果传统小波神经网络模型比较。结果表明,AIW-PSO小波神经网络模型对上证指数具有更好的预测效果。In the view of the shortage of the Wavelet Neural Network Algorithm, adapt Adaptive Inertia Weight Particle Swarm Optimization Algorithm （AIW-PSO） as a study algorithm, build the AIW-PSO Wavelet Neural Network Model to predict the Shanghai stock Index., and make a comparison between the results of improved algorithm prediction model with results of traditional Wavelet Neural Network Model. The results show that the AIW-PSO Wavelet Neural Network Prediction Model has better prediction results on the Shanghai Stock Index.

关 键 词：自适应惯性权重粒子群优化算法 小波神经网络 上证指数预测 

分 类 号：F832.5[经济管理—金融学] F224