A Multi-series Grey Forecasting Model Based on Neural Network Improved by Genetic Algorithm

摘要：

Traditional Grey GM(1,1) Model had its defect when it was applied to forecast relative data series. The relationship between different data series can’t be reflected properly. In order to solve the problem, artificial neural network (ANN) is combined to forecast multi-series data. Then the network optimization is aided by improved genetic algorithm (GA). So the network weights and thresholds were self-adaptively evolved. Then a hybrid grey model combined with ANN and GA was put forward. Based on Matlab program, the simulation example shows that the hybrid algorithm improves the forecasting precision. It can provide effective help for forecasting work.

作者: LIU Jian-yong LI Ling ZHANG Yong-li LI Yan

作者单位: Engineering Institute of Engineering Corps, PLA Univ. of Science and Technology, Nanjing 210007, P.R Engineering Institute of Engineering Corps, PLA Univ. of Science and Technology, Nanjing 210007, P.R

会议类型: 国际会议

会议名称: 2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)

会议地点: 南京

会议语种:英文

在线出版日期: 2007-11-18（万方平台首次上网日期，不代表论文的发表时间）