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基于改进RBF神经网络对股价的演变预测
引用本文:郭兰平,俞建宁,张建刚,张旭东,漆玉娟.基于改进RBF神经网络对股价的演变预测[J].兰州铁道学院学报,2010,29(1):141-145.
作者姓名:郭兰平  俞建宁  张建刚  张旭东  漆玉娟
作者单位:兰州交通大学数理与软件工程学院;
基金项目:甘肃省自然科学基金(0803RJZA012)
摘    要:对RBF神经网络进行了分析,建立了RBF神经网络模型,并对此模型进行了改进,使其具有更好的预测性能.把一类非线性较强的时间序列(万科A股2009年6月份股票价格)利用该模型进行了非线性逼近.用Matlab软件对网络的学习与训练过程进行了数值仿真.实验结果表明:利用改进后的网络模型对非线性时间序列进行短期预测是可行的,其预测精度高于改进前的预测精度,改进方法有效.

关 键 词:RBF神经网络  预测模型  数值仿真  股价  

Prediction of the Evolution of Stock Prices Based on Improved RBF Neural Network
GUO Lan-ping,YU Jian-ning,ZHANG Jian-gang,ZHANG Xu-dong,QI Yu-juan.Prediction of the Evolution of Stock Prices Based on Improved RBF Neural Network[J].Journal of Lanzhou Railway University,2010,29(1):141-145.
Authors:GUO Lan-ping  YU Jian-ning  ZHANG Jian-gang  ZHANG Xu-dong  QI Yu-juan
Institution:School of Mathematics/a>;Physics & Software Engineering/a>;Lanzhou Jiaotong University/a>;Lanzhou 730070/a>;China
Abstract:RBF neural network is analyzed in this paper,and RBF neural network model is established,too.The model is improved to have better prediction performance.A strong class of nonlinear time series(stock price of Wanke A in June of 2009)is approached by using the model.Matlab software is applied to carry out numerical simulation of the network's learning and training process.Simulation results show that the improved network model for short-term prediction of nonlinear the series is feasible,and its prediction ac...
Keywords:RBF neural network  prediction model  numerical simulation  stock prices  
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