Research on Dynamic Risk Evaluation Model for Family Farm Entrepreneurship Based on BP Neural Network

Family farm entrepreneurship is a high-risk activity. Identifying and evaluating family farm entrepreneurial risks through scientific and effective methods plays an important role in preventing and controlling the uncertainty of the family farm entrepreneurial process and ensuring the healthy and sustainable development of family farm entrepreneurship. BP neural network has the advantages of strong learning ability, high fault tolerance, and wide adaptability. It is suitable for dealing with information problems that require simultaneous consideration of multiple conditions and ambiguity. In this paper, the BP neural network was applied to the evaluation of family farm entrepreneurial risks. Firstly, the traditional BP neural network was introduced, and the self-adaptive learning algorithm of BP neural network was proposed. Then, the construction principles of the evaluation index system of family farm entrepreneurial risk were expounded. On this basis, the evaluation index system of family farm entrepreneurial risk was designed, and the comment rating and assignment method of the evaluation index were determined. Finally, based on the self-adaptive learning algorithm of BP neural network, the dynamic evaluation model of family farm entrepreneurial risk was constructed. The empirical results show that this BP neural network model can not only autonomously optimize the network topology structure and improve the network learning efficiency, but also accurately and dynamically evaluate the risks of family farm entrepreneurship, thus helping family farmer to discover the risk factors in the entrepreneurial process in a timely manner, take preventive and pre-control measures as early as possible, minimize or avoid risk losses, and improve the performance of family farm entrepreneurship.