Research on the Construction System of Geographic Information Model in Logistics Center Location Problem

In this paper, the geographic information model building system of logistics center location problem is studied. Firstly, the importance and challenge of logistics center location are introduced, and the shortcomings of traditional methods are pointed out. A solution based on Hopfield artificial neural network algorithm is proposed. This algorithm can effectively process large-scale and high-dimensional geographic information data, and provide fast and accurate location selection schemes. Then, the construction process of geographic information model is described in detail, including key steps such as data acquisition, preprocessing, feature extraction and model establishment. In the model building, the characteristics of Hopfield neural network are fully utilized, and the performance of the model is optimized by adjusting the weight and bias. Finally, the feasibility and effectiveness of the proposed method are verified by system model simulation experiments. The experimental results show that the system can significantly improve the accuracy and efficiency of logistics center location, and provide strong support for practical application.