Title :
Application of RBF Neural Network to Enterprise Credit Comprehensive Evaluation
Author :
Lou, Wengao ; Kuang, Luoping
Author_Institution :
Coll. of Manage., Shanghai Univ. of Sci. & Technol.
Abstract :
Radial basis function (RBF) neural network possesses the characteristics of fast training speed, reaching the global minimum and escaping from local minimum, et al. Under fewer samples, the RBF neural network model (RBFNN-based model) for credit comprehensive evaluation is established according to actual enterprise´s credit state. For the 6 non-training enterprises, the comparison of the calculated results of several models shows that the accuracy of the RBFNN-based model established in this paper is the highest. It is effective and suitable to apply RBFNN to enterprise credit comprehensive evaluation
Keywords :
business data processing; credit transactions; radial basis function networks; RBF neural network; enterprise credit comprehensive evaluation; radial basis function neural network; Artificial neural networks; Educational institutions; Management training; Modeling; Neural networks; Pattern recognition; Profitability; Radial basis function networks; Technology management; Testing;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614879
