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An Analysis on Qualitative Bankruptcy Models to Frame Bankruptcy Prediction Rules Using Ant Colony Algorithm

A. Martin, V. Aswathy, S. Balaji, V. Prasanna Venkatesan


Many Qualitative Bankruptcy Prediction models are available. These models use non-financial information as Qualitative factors and from which Bankruptcy is predicted. In the prior researches Genetic Algorithm was applied to generate Qualitative Bankruptcy Prediction Rules. However this Model uses only very less number of Qualitative factors and the generated rules has Repetitions and overlapping. To improve the Prediction accuracy we have proposed a model which applies more number of Qualitative factors and Prediction Rules are generated using Ant Colony Optimization Algorithm (ACO). The concept pheromone depositing and updating in Ant Colony Algorithm reduce the false negative rules in the bankruptcy prediction. The heuristic and probabilistic features of Ant Colony Algorithm increase the prediction accuracy of Bankruptcy.


Ant Colony Algorithm, Genetic Algorithm, Qualitative Bankruptcy Prediction, Repetitions and Overlapping, Qualitative Factors, Pheromone Deposit and Update, Heuristic and Probabilistic Features, Prediction Accuracy.

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