Abstract
Small and medium-sized enterprises are an important part of China’s economy. At the same time, under the background of public entrepreneurship, innovation is also the engine and growth point of China’s economic development. Therefore, we should do a good job in supporting and subsidizing small and medium-sized enterprises, so that the stronger the small and medium-sized enterprises are, the bigger they are. Let the first step go back and let SMEs be everywhere. It is an important work of the government and society. In this paper, Bayesian regularization algorithm is used to improve the generalization ability of BP network, improve BP neural network model, and use neural network to study the historical information of SMEs in government information system to predict the future development and growth of new business and investment, so as to improve the evaluation index. It is compared with historical data. Finally, the evaluation method that can reasonably predict the growth of SMEs is put forward. It is validated by enterprise data in the next few years.
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