计算机与现代化Issue(7)：51-55,5.DOI:10.3969/j.issn.1006-2475.2013.07.013
基于混合优化的RBF神经网络模型研究
Research on an Optimized RBF Neural Network Model Applied to CPI Forecast
摘要
Abstract
This paper,aiming at the nonlinear characteristics of CPI and the parameters of being difficult to be objectively determined in RBF neural network,puts forward a kind of optimization of RBF neural network method which combines orthogonal least squares (OLS),K-means clustering and gradient descent algorithm,computing activation function with the linear combinations of Gauss,reflected sigmoidal and inverse multiquadrics radial basis functions,then builds a model for CPI to fit and forecast by using the optimization algorithm of RBF neural network.Experimental results show that the model is of a good convergence and generalization ability,the model has a certain universal applicability in the prediction performance which is obviously superior to the single method forecast and the hybrid network on Gauss kernel function.关键词
径向基神经网络/优化混合算法/居民消费价格指数预测Key words
RBF neural network/optimized hybrid algorithm/CPI forecasting分类
信息技术与安全科学引用本文复制引用
罗芳琼..基于混合优化的RBF神经网络模型研究[J].计算机与现代化,2013,(7):51-55,5.基金项目
广西教育厅科研基金资助项目(201204LX506) （201204LX506）
柳州师范高等专科学校科研基金资助项目(LSZ2011B007) （LSZ2011B007）
