An Algorithm of Fertilization Model Fitting Based On Mixed Intelligent Computation

During the process of pluralistic fertilization model construction, the unreasonable ratio of nitrogen, phosphorus and kalium easily results in the deviation of fertilizing model. This paper has proposed an adaptive algorithm of fertilization model fitting based mixed intelligent computing of GP/GA, and solved the issue of structure and parameters optimization of adaptive fertilization model. This algorithm has carried out the research of applying control factors to adjust the parameters of fitting function, the appropriate ratio of nitrogen, phosphorus and kalium is regarded as control factors of heuristic search to adjust models, on the basis of history test data dynamical models are generated, and the optimization and correction of models based appropriate ratio of nutrients are achieved.