Xiaona Zhang^1,*, Jie Feng², Zhen Hong³, Xiaona Rui⁴

Computer Systems Science and Engineering, Vol.42, No.2, pp. 677-688, 2022, DOI:10.32604/csse.2022.023136

Abstract 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… More >

Xiaona Zhang^1,*, Jie Feng², Zhiguo Yu¹, Zhen Hong³, Xinge Yun¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3871-3888, 2021, DOI:10.32604/cmc.2021.020057

Abstract The existence of soil macropores is a common phenomenon. Due to the existence of soil macropores, the amount of solute loss carried by water is deeply modified, which affects watershed hydrologic response. In this study, a new improved BP (Back Propagation) neural network method, using Levenberg–Marquand training algorithm, was used to analyze the solute loss on slopes taking into account the soil macropores. The rainfall intensity, duration, the slope, the characteristic scale of macropores and the adsorption coefficient of ions, are used as the variables of network input layer. The network middle layer is used as hidden layer, the number… More >