基于遗传神经网络的企业信用评级模型研究

Research on enterprise credit assessment model based on genetic-neural network

提出了一种基于遗传算法改进的神经网络企业信用评级模型.利用BP神经网络自适应和自学习的特点,通过遗传算法实现对神经网络连接权重和阈值的修正与优化,在一定程度上解决了BP神经网络存在收敛速度较慢和可能落入局部最小点的问题.实验表明,该模型在企业信用评级上有着较高的准确率,具有很好的应用价值.

In order to meet the requirements of the corporate credit rating, based on neural networks and enterprise credit management research,corporate credit rating model based on BP neural networks is proposed. Using the BP neural network adaptive and self-learning characteristics, by using genetic algorithm of neural network connection weights and thresholds correction and optimization, solve the artificial neural network convergence speed and might fall into the local minimum points. Proved by experiments,the model has a higher accuracy rate on corporate credit rating.