This paper uses Þnancial structure data via internet network to enable the prediction of Þnancial distress. Financial distress is deÞned as a Þrm that has entered into liquidation, receivership or is declared as of negligible value by the Inland Revenue. A sample of distressed and nondistressed quoted companies listed on the London Stock Exchange for the last 20 years (1980 1999) was obtained f...

There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling. The first is the use of networks as preprocessors to reduce the dimensionality of chemical descriptors for use in statistical or network models. The second is to create classification models for predictive toxicology. This report discusses the use of ANNs as classifiers in SAR/QSAR modeling and...

This article describes an application of three well{known statistical methods in the eld of game{tree search: using a large number of classi ed Othello positions, feature weights for evaluation functions with a game{phase{independent meaning are estimated by means of logistic regression, Fisher's linear discriminant, and the quadratic discriminant function for normally distributed features. The...

One of the challenging issues for investors and professionals is appropriate models to evaluate financial situation of the firms. In this regard, many models have been extracted by researchers using different financial ratios to resolve these issues. However, choosing a model based on the conditions and users’ needs is complex. The main objective of this study is to identify the effect of conti...

Databases of species observations from surveys and ad hoc observations are frequently maintained by managers for a particular area. Obtaining information from this type of survey data about the habitat associations of species can be an efficient method of predicting habitat suitability across a landscape. Many multivariate statistical methods have been used to develop models of habitat associat...

Many accounting and finance problems require ordinal multi-state classification decisions, (e.g., control risk, bond rating, financial distress, etc.), yet few decision support systems are available to aid decision makers in such tasks. In this study, we develop a Neural Network based decision support system (NN-DSS) to classify firms in four ordinal states of financial condition namely healthy...

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper applies support vector machines (SVMs) to the bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purp...