Bankruptcy Prediction Based on Limited Data of Artificial Neural Network - in Textiles and Colthing Industries -

한정된 데이터 하에서 인공신경망을 이용한 기업도산예측 - 섬유 및 의류산업을 중심으로 -

  • 피종호 (고려대학교 산업대학원 석사과정) ;
  • 김승권 (고려대학교 공과대학 산업공학과 교수)
  • Published : 1989.12.01

Abstract

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bandkruptcy prediction on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediction. Therefore, We have decided to focus on textile and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

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