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《Journal of Southwest China Normal University(Natural Science Edition)》 2014-01
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On a Forecasting Model of Grey Neural Network Based on Improved Cuckoo Search Optimal Algorithm

QU Chi-wen;FU Yan-ming;DAI Jun;Department of Mathematics& Computer Information Engineering,Baise University;Computer and Electronic Information College,Guangxi University;Department of Economics& Management,Baise University;  
In order to improve the prediction accuracy of the Gray Neural Network(GNN)in the field of artificial intelligence prediction,the GNN based on the Improved Cuckoo Search Algorithm(CS-GNN)has been proposed in this paper.To find out the optimal initialization parameters,the conventional GNN whitening parameters have been optimized by the improved cuckoo search algorithm,and the results been used as the input of the GNN.A Grey Neural Network model based on improved cuckoo search optimization has been built and used to predict coal and gas outburst.The simulation experiment result indicates that the prediction accuracy of the model is higher than that of the conventional GNN and the GNN based on Particle swarm algorithm(PSO-GNN).
【Fund】: 国家自然科学基金项目(61063046/F020805)资助;; 广西高校科研项目(2013YB247);; 百色学院一般科技项目(No.2010KB16)
【CateGory Index】: TP183;N941.5
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