Paper Title:
Bankruptcy Prediction by Genetic Ant Colony Algorithm
  Abstract

Corporate bankruptcy is a hot topic in economical research. Traditional methods cannot reach satisfying classification accuracy due to the high dimensional features. In this study, we proposed a novel method based on wrapper-based feature selection. Moreover, a novel genetic ant colony algorithm (GACA) was proposed as the search method, and the rule-based model was employed as the classifier. Stratified K-fold cross validation method was taken as the statistical resampling to reduce overfitting. Simulations take 1,000 runs of each algorithm on the dataset of 800 corporations during the period 2006-2008. The results of the training subset show that the GACA obtains 84.3% success rate, while GA obtains only 48.8% and ACA obtains 22.1% success rate. The results on test subset demonstrate that the mean misclassification error of GACA is only 7.79%, less than those of GA (19.31%) and ACA (23.89%). The average computation time of GACA is only 0.564s compared to the GA (1.203s) and ACA (1.109s).

  Info
Periodical
Edited by
Wenya Tian and Linli Xu
Pages
459-463
DOI
10.4028/www.scientific.net/AMR.186.459
Citation
Y. D. Zhang, L. N. Wu, "Bankruptcy Prediction by Genetic Ant Colony Algorithm", Advanced Materials Research, Vol. 186, pp. 459-463, 2011
Online since
January 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Zhan Wei Du, Yong Jian Yang, Yong Xiong Sun, Chi Jun Zhang, Tuan Liang Li
Abstract:This paper presents a modified Ant Colony Algorithm(ACA) called route-update ant colony algorithm(RUACA). The research attention is focused...
620
Authors: Li Xun Zhang, Yin Xue Wang, Bing Bing Wang, Qian Deng, Hao Chen
Chapter 6: Energy & Electronic
Abstract:Path planning for mobile robot is a kernel problem in the robot technology area, with the characteristics of complexity, binding and...
673
Authors: Bang Long Pan, Wei Ning Yi, Xian Hua Wang
Chapter 5: Information Processing and Computational Science
Abstract:Low-altitude unmanned airship remote sensing is attractive to various applications. However, at present, since the airship is bulky, weak to...
924
Authors: De Wen Cai, Chen Fei Shao, Di Kai Wang, Er Feng Zhao, Meng Yang
Chapter 5: Sensors, Measurements and Monitoring
Abstract:Back Propagation (BP) neural network can learn and store a large number of input-output model nonlinear relationships with simple structure....
257