Spatial Distribution of Water Quality Based on Generalized Regression Neural Network
The paper proposes a new model for analyzing spatial distribution of water quality. The model is based on statistics and generalized regression neural network. The model is based on statistic theories and easy to approximate a nonlinear function. The advantages of the model include simple net structure, few artificial parameters, and high accuracy calculation. The developed approach is successfully applied to the water quality assessment of the Taihu Lake of China P.R, which includes the dissolved oxygen concentration of water-quality index and the spatial distribution of the water-quality level. The results show that the model can generate a credible spatial distribution of the water quality.
Water-quality assessment Generalized regression neutral network.
Huibin Wang Lizhong Xu Shaohua Sun Simon X.Yang
College of Computer and Information Engineering Hohai University Nanjing, 210098,China Advanced Robotics and Intelligent Systems (ARIS) Lab,School of Engineering University of Guelph Guel
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
1086-1090
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）