Study on commercial bank risk early warning system based on UDM and self-adaptive RBFNN

By using scientific uniform design method, the representative and uniformity samples are designed. Thus the multi-factors' and multi-levels' self-learning training is arranged using limited experiments times, and the self-adaptive RBFNN are adopted to realize the bank risk early warning diagnosis. Experiments show the results between self-adaptive RBFNN evaluation and experts fuzzy comprehensive evaluation(FCE) are very close, The generalization ability of self-adaptive RBFNN with UDM is far better than that of traditional RBFNN with Monte-Carlo method The self-adaptive RBFNN with UDM realizes non-linear approaching ability of evaluation, meantime conquers the capability limitation of traditional RBFNN and BP neural network, and avoids the subjectivity and uncertainty of traditional FCE.