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Author Jih-Chang Hsieh ♦ Shih-Hsin Chen ♦ Pei-Chann Chang
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2007
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Statistical analysis ♦ Artificial immune systems ♦ Neural networks ♦ Banking ♦ Alarm systems ♦ Financial management ♦ Hazards ♦ Regression analysis ♦ Network address translation ♦ Logistics
Abstract In recent decades, soft computing techniques have broadly applied to solve complex problems. Among the soft computing techniques, artificial immune system (AIS) have appeared as a new approach dealing with classification problems. In this paper, an AIS algorithm is developed and applied to a two-group classification problem. An example of Taiwanese banking industry is discussed and the financial ratios of each bank from 1998 to 2002 were collected. This system has to distinguish the operational performance (good or bad) of each bank to offer a reference material for the managers or investors. The performance of AIS is compared with other five early warning systems, namely, genetic neural networks (GNN), case-based reasoning (CBR), backpropagation neural network (BPN), logistic regression analysis (LR), and quadratic discriminant analysis (QDA). The result indicates that the proposed AIS is over 10% better than the three soft computing early warning systems (GNN, CBR and BPN). The AIS outperforms the statistical early warning systems (LR and QDA) at least 24%.
Description Author affiliation: Vanung Univ., Taoyuan (Jih-Chang Hsieh)
ISBN 0769528821
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2007-09-05
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 185.30 kB
Page Count 1
Starting Page 183
Ending Page 183

Source: IEEE Xplore Digital Library