Study on Prediction Method for Chinese Regional Economy Based on GPCA and GAPSO-NN
FU Chuan-xiu
Abstract：A research model combining the Global Principal Component Analysis (GPCA) with GA (ge-netic algorithm) -PSO (particle swarm optimization) Neural Network in this paper has been suggested to predict the regional economic development level in China .First, the index system to evaluate the regional economic development level is established .Then, the global principal component scores and the compre-hensive evaluation value are obtained by means of GPCA , as the input of GA-PSO Neural Network . Last, the prediction model of GAPSO-NN is constructed.The result of simulation test proves the validity of this method .
Keywords：regional economyglobal principal component analysisGAPSO neural networkprediction method
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 71-74 )