Potential prediction method of sports tourism resource development based on Ga-Bp algorithm

At present, there are still weak links in the development process of sports tourism resources, which hinders its own development. The prediction of tourism resources development potential plays an important role in guiding tourism projects. Before the study, this paper first investigates the present situation of sports tourism resources, from the perspective of spatial analysis of regional distribution of sports tourism in China. Guided by the concept of sustainable development and regional economic theory of sports tourism resources development potential influencing factors analysis; Identify the main body of resource development and construct the work flow of sports tourism resource development. Based on the basic principles of genetic algorithm and BP neural network theory, the genetic algorithm is used to optimize the weight and threshold of BP neural network. Seven influencing factors, including Sports Policy Support Index, Traffic Access Index, Sports Tourism Eco-Environment Index, Regional Sports Online Tourism Development Index, Cultural and Historical Resources Index, Cultural and Tourism Industry Influence Index, and Characteristic Industry Output Value Scale Index, are selected as the nodes of the sports tourism resource development prediction model. Then, the sample data is sorted out and normalized. The hybrid genetic neural network is used for prediction and analysis. The results show that: This paper uses genetic algorithm to optimize the weight and threshold of BP neural network, It can effectively avoid BP neural network falling into local minimum and improve the classification processing ability of BP neural network, The genetic neural network prediction model constructed on this basis can accurately classify the development types of four sports tourism resources in the training samples, It provides a multi-dimensional objective decision-making reference method for the development and prediction of sports tourism resources in the future.