Abstract
Aiming at the problem of credit evaluation of science and technology-based small and medium-sized enterprises in China, a credit evaluation system based on machine learning is proposed. A total of 17 indicators are selected from five aspects of solvency, profitability, operation ability, growth ability and R & D ability. Finally, 11 representative indicators are selected. Then through BP neural network algorithm to build a credit evaluation model, training and Simulation of the credit rating of science and technology-based SMEs. The results show that the evaluation model has good generalization ability, and can effectively evaluate the credit of science and technology-based SMEs.
Highlights
With the rapid development of information technology and the arrival of the era of big data, small and medium-sized enterprises, especially technological small and medium-sized enterprises, as the micro carrier of innovation and the pillar of the real economy, play an increasingly important role, and have become an important part of China's economic system
This paper is based on this problem, using the method of machine learning to build a credit evaluation model suitable for China's small and medium-sized enterprises, and bring the actual data into it for calculation and training,So as to ensure the effectiveness and practicability
The real reason is that the information of small and medium-sized scientific and technological enterprises and financial institutions is not equal
Summary
With the rapid development of information technology and the arrival of the era of big data, small and medium-sized enterprises, especially technological small and medium-sized enterprises, as the micro carrier of innovation and the pillar of the real economy, play an increasingly important role, and have become an important part of China's economic system. They pay 50% of the national tax, and provide labor employment rate of 80%. This paper is based on this problem, using the method of machine learning to build a credit evaluation model suitable for China's small and medium-sized enterprises, and bring the actual data into it for calculation and training,So as to ensure the effectiveness and practicability
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