A STUDY ON THE DECISION-MAKING MODEL FOR PRECISE ENVIRONMENTAL GOVERNANCE IN RURAL REGIONS

In order to solve the problem of sparse data samples in dealing with multiple dimensions such as farmland environment, crop growth status, and meteorological conditions, which affects the accuracy of decision-making models in existing research, an agricultural governance decision-making model under the rural revitalization strategy is constructed.Based on the stock and emission rate of pollutants in the agricultural environment, a net present value function for agricultural governance is constructed to search for the governance investment decision that maximizes the function.Evolutionary factors are used to learn factor optimization particle swarm optimization algorithm to solve complex multidimensional data samples and output the optimal agricultural governance decision results.The experimental results show that the model can formulate optimal agricultural environment precise governance decisions based on the actual situation of the agricultural environment, and improve the economic and environmental development level of the research area.It also provides strong decision support for agricultural environmental governance under the rural revitalization strategy, and has important theoretical and practical significance.