Discrete Dynamic Modeling Analysis of Rural Revitalization and Ecotourism Sustainable Prediction Based on Big Data

With the development of modern rural tourism, it has become people’s spiritual demand to deeply tap the characteristic rural culture and continuously enhance the attraction of rural tourism. However, due to the complex tourism market environment, small changes in factors will affect the final result. Therefore, traditional methods cannot accurately predict the future tourism market. In view of this situation, this paper uses the mathematical algorithm of BP neural network to simulate the structure of brain neural network to deal with this kind of nonlinear relationship problem. Through the classification of complex and changeable factors, the modeling is completed systematically, and finally the effective prediction results are obtained. For the analysis of the time evolution of tourism resources development, it can be found from the policy development theory that the innovative development presents the characteristics of S-shaped curve in time; that is, the number adopted in the initial stage of development is less, then enters the rapid development period, and finally develops slowly. This study will help to solve the primary problem of balancing the positive and negative effects of rural tourism development and realizing the sustainable development of coastal villages.