کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
473031 698762 2006 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Financial distress prediction by a radial basis function network with logit analysis learning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Financial distress prediction by a radial basis function network with logit analysis learning
چکیده انگلیسی

This paper presents a financial distress prediction model that combines the approaches of neural network learning and logit analysis. This combination can retain the advantages and avoid the disadvantages of the two kinds of approaches in solving such a problem. The radial basis function network (RBFN) is adopted to construct the prediction model. The architecture of RBFN allows the grouping of similar firms in the hidden layer of the network and then performs a logit analysis on these groups instead of directly on the firms. Such a manner can remedy the problem of nominal variables in the input space. The performance of the proposed RBFN is compared to the traditional logit analysis and a backpropagation neural network and demonstrates superior results to both the counterparts in predictive accuracy for unseen data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Mathematics with Applications - Volume 51, Issues 3–4, February 2006, Pages 579-588