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any private publication or statement by any of its employees. The views expressed herein …

Neural networks are being used in areas of prediction and classification, the areas where
statistical methods have traditionally been used. Both the traditional statistical methods and …

Nowadays, many current real financial applications have nonlinear and uncertain behaviors
which change across the time. Therefore, the need to solve highly nonlinear, time variant …

The prediction of corporate bankruptcies is an important and widely studied topic since it can
have significant impact on bank lending decisions and profitability. This work presents two …

In this paper, we present a general framework for understanding the role of artificial neural
networks (ANNs) in bankruptcy prediction. We give a comprehensive review of neural …

Despite increasing applications of artificial neural networks (NNs) to forecasting over the
past decade, opinions regarding their contribution are mixed. Evaluating research in this …

During the last decade, neural networks have established themselves as a theoretically
sound alternative to traditional statistical models, and a large body of research on their …

Data mining with neural networks | Guide books skip to main content ACM Digital Library
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This paper presents an overview of the different types of neural network models which are
applicable when solving business problems. The history of neural networks in business is …

In this study, two learning paradigms of neural networks, supervised versus unsupervised,
are compared using their representative types. The back-propagation (BP) network and the …