Modelling of the Slope Solute Loss Based on Fuzzy Neural Network Model  

作　　者：Xiaona Zhang Jie Feng Zhen Hong Xiaona Rui 

机构地区：[1]School of Hydrology and Water Resources,Nanjing University of Information Science&Technology,Nanjing,210044,China [2]Water Resources Research Institute,China Institute of Water Resources and Hydropower Research,Beijing,100044,China [3]Department of Geography and Environmental Sustainability,University of Oklahoma,Norman,73071,USA [4]Wuxi Research Institute,Nanjing University of Information Science&Technology,Wuxi,214100,China

出　　处：《Computer Systems Science & Engineering》2022年第8期677-688,共12页计算机系统科学与工程（英文）

基　　金：supported by the National Natural Science Foundation of China(No.41301037);the Natural Science Foundation of Jiangsu Province(BK20201136,BK20191401);the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.11KJB170008);Innovation and Entrepreneurship Training Program for College Students in Jiangsu Province(No.201910300106Y).

摘　　要：In regards to soil macropores,the solute loss carried by overland flow is a very complex process.In this study,a fuzzy neural network(FNN)model was used to analyze the solute loss on slopes,taking into account the soil macropores.An artificial rainfall simulation experiment was conducted in indoor experimental tanks,and the verification of the model was based on the results.The characteristic scale of the macropores,the rainfall intensity and duration,the slope and the adsorption coefficient of ions,were chosen as the input variables to the Sugeno FNN model.The cumulative solute loss quantity on the slope was adopted as the output variable of the Sugeno FNN model.There were three membership functions,and the type of membership function was gbellmf(generalized bell membership function).The hybrid learning algorithm,which combines the back propagation algorithm with a least square method,was applied to train and optimize the network parameters,and the optimal network parameters were determined.The simulation results showed that the simulated values were consistent with the measured values.

关 键 词：Slope solute loss soil macropores fuzzy neural network 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]