A Study for a Soil Balanceable Fertilizer Model System Based on Fuzzy Logic and Neural Networks
XU Xiao-qiang · Journal of Agricultural Mechanization Research · 2007
A study on a soil balanceable fertilizer model system is made with the combination of fuzzy logic and neural networks, the fuzzy model architecture of based on the method of artificial neural networks and the hybrid learning scheme are also proposed. By repetition experiment of planting soy in the same farmland with soil nutrients and yield as inputs, with fertilizer application rate of nitrogen, phosphorus and potassium as outputs, the artificial neural networks is trained through adoption of hybrid learning scheme. The soil balanceable fertilizer model system of Fuzzy-Neuro networks is established .By practice verific action, applying this model system in agricultural product can provide optimum scheme of fertilization.