Rice Blast Prediction Based on Gray Ant Colony And RBF Neural Network Combination Model

摘要：

For rice blast gray system with complex nonlinearity, utilizing of gray ant colony GM(1, 1,θ) model and RBF neural network model characteristics, gray ant colony and RBF neural network combination model is presented in this paper. After 10 years (2002-2011) prediction analysis of rice blast, the prediction accuracy of this project is up to 97.84％, and verifies the validity of the prediction model.

关键词： rice blast gray system gray ant colony prediction RBF neural network prediction combination model

作者: Liu Kun Wang Zhiqiang

作者单位: College of Information Technology Heilongjiang Bayi Agricultural University Daqing, China

会议类型: 国际会议

会议名称: 2012 Fifth International Symposium on Computational Intelligence and Design 第五届计算智能与设计国际会议 ISCID 2012

会议地点: 杭州

会议语种:英文

页码: 144-147

在线出版日期: 2012-10-28（万方平台首次上网日期，不代表论文的发表时间）