Design of Decision Algorithm for Urban Land Functional Allocation Planning Based on Artificial Neural Network

At present, the contradiction between land supply and demand in China has become increasingly obvious. Various economic constructions occupy a large number of high-quality cultivated land, and the land use structure is unbalanced and the land use efficiency is low, which has posed a serious threat to the national resource security. The rational allocation of urban land is the core of urban land use. Based on the theory of land functional allocation planning in eco-city, this paper analyzes the correlation between ANN (artificial neural network) and land functional allocation planning, and puts forward the decision algorithm of urban land functional allocation planning based on ANN. By using BPNN (BP neural network), the original land use types in the current urban land use map are optimized and reorganized. Make it meet the three objective functions of the lowest land conversion cost, the highest spatial coordination and the largest suitability value, and make the land optimization more in line with the actual situation. The research results show that the compactness of the proposed method is higher than that of the literature method when planning land in multiple regions, which shows that the land planning effect of the proposed method is good. It shows that the decision-making model of ANN land function allocation planning has high feasibility and verifies the planning performance of the proposed method.