PCNN Forecasting Model Based on Wavelet Transform and Its Application

摘要：

Pulse Coupled Neural Network (PCNN) is widely used in image processing for its basic characteristics of coupling mechanism and achieved some results. PCNN model has been improved as follows: Firstly,correlation coefficient is used to control the bonding strength. Secondly, the threshold setting is adjusted by the least error. Thirdly, A Trous transform is combined with PCNN model to form the combination forecasting model. The improved combination model was implemented in annual rainfall forecasting to check its feasibility.

关键词： Pulse coupled neural network A Trous wavelet transform Forecasting Correlation analysis

作者: Qiang Fu Yan Feng Dengchao Feng

作者单位: College of Water Conservancy & Architecture, Northeast Agricultural University, Harbin 150030, P. R. College of Electronics & Information Engineering, Tianjin University, Tianjin 300072, P. R. China

会议类型: 国际会议

会议名称: The 2007 International Conference on Intelligent Systems and Knowledge Engineering(第二届智能系统与知识工程国际会议)

会议地点: 成都

会议语种:英文

页码: 1169-1175

在线出版日期: 2007-10-15（万方平台首次上网日期，不代表论文的发表时间）