Ant colony algorithm used for bankruptcy prediction

摘要：

Bankruptcy prediction is a hot topic. Traditional methods consist of univariate model and multivariate model such as neural network. However, the NNs can not extract effective rules. Thus, a novel approach was proposed in this paper to extract rules. First, t-test method was used to select 5 features from 55 original features. Second, the rule encoding was constructed. Third, the ant colony algorithm was utilized to find the optimal rule. Experiments on 200 corporate demonstrate that this proposed algorithm is effective and rapid.

关键词： Bankruptcy prediction ant colony optimization

作者: Shuihua Wang Lenan Wu Yudong Zhang hengyu Zhou

作者单位: School of Information Science and Engineering, Southeast University, Nanjing China School of Information Science and Engineering, Southeast University, Nanjing China Brain Image Lab, Brain Image Lab, Division of Child Psychiatry, New York State Psychiatric Institute, New York USA Me

会议类型: 国际会议

会议名称: Second International Symposium on Information Science and Engineering(第二届信息科学与工程国际会议)

会议地点: 上海

会议语种:英文

页码: 137-139

在线出版日期: 2009-12-26（万方平台首次上网日期，不代表论文的发表时间）