Method of Plant Growth Modeling Based on Genetic Algorithm and RBF Network

摘要：

The plant growth model is very difficult to be set up. Because the relations between the growth parameters and surround envelopment parameters are very complex. A new method that using artificial neural network for plant growth modeling is presented. For improving the algorithm convergence rate, the radial basis function (RBF) network is adopted. As an example of this method, the prediction of tomato stem daily growth and its surround relation is also presented. The experiment results show that the method is effective for plant growth modeling.

关键词： Plant modeling artificial neural network radial basis function genetic algorithm

作者: Cai Zhenjiang Hu Yihua Sun Yumei Hu Shunbin

作者单位: Institue of Mechanical and Electric Engineering,Agricultural University of Hebei,Baoding 071001,Chin Hebei Software Institute,Baoding 071000,China

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）