An Evaluation Model of an Urban Green Finance Development Level Based on the GA-Optimized Neural Network

Abstract

The construction of a green financial system can promote economic transformation and development, scientifically and effectively evaluate the green environmental protection level of finance in different cities, and provide a strong impetus for its future promotion. This paper introduces a BP neural network into the evaluation system of urban green finance progress and optimizes the model through GA. According to the constructed evaluation index system, this paper makes empirical analysis of the experimental city. The optimization results show that GA can improve the training error range of the BP neural network and increase the stability of evaluation model performance and the accuracy of evaluation results. Through empirical analysis, it is concluded that the development status of the urban economy, the mode and efficiency of capital distribution, and the degree of support for the environmental protection industry in terms of policy and capital will have a great impact on the development of its environmental protection finance. The support attitude of the local government and society in energy conservation, environmental protection, and green city construction provides a broad development space for green finance to a great extent. Cities should broaden the development channels of green finance and build a sound and scientific green financial service system.