区域经济预测的GPCA和优化小波网络组合模型研究

Study on Prediction Model for Regional Economy Based on GPCA and Optimized WNN

构建全局主成分分析(GPCA)和优化小波神经网络的组合模型,对中国区域经济发展水平进行预测.首先借助GPCA获得区域经济发展水平的全局主成分分值、综合评价值,作为优化小波网络的输入、目标输出;然后构建遗传-粒子群算法优化的小波网络预测模型.通过仿真,得到较满意的结果,表明区域经济水平预测的组合模型是有效和实用的.

The model of Global Principal Component Analysis （ GPCA ） and optimized Wavelet Neural Network （ WNN） was suggested to predict the regional economic development level in China .First, the global principal component scores and the comprehensive evaluation value were obtained by means of GPCA , as the in-put of optimized WNN.Then, the prediction model of GAPSO -WNN was constructed.The result of simulation test proved the validity and practicability of the model .