Support Vector Regression and Immune Clone Selection Algorithm for Predicting Financial Distress

被引：0
|
作者：
Tian, WenJie [1 ]
Wang, ManYi [2 ]
机构：
[1] BEIJING Union Univ, Automat Inst, Beijing, Peoples R China
[2] Capital Univ Econ & Business, Finance Inst, Beijing, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON BUSINESS INTELLIGENCE AND FINANCIAL ENGINEERING, PROCEEDINGS | 2009年
关键词：
financial distress; rough set; immune clone selection algorithm; support vector regression; prediction; NETWORKS; FAILURE;
D O I：
10.1109/BIFE.2009.39
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
In the analysis of predicting financial distress based on support vector regression (SVR), irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper used rough sets as a preprocessor of SVR to select a subset of input variables and employed the immune clone selection algorithm (ICSA) to optimize the parameters of SVR. Additionally, the proposed ICSA-SVR model that can automatically determine the optimal parameters was tested on the prediction of financial distress. Then, we compared the proposed ICSA-SVR model with other artificial intelligence models of (BPN and fix-SVR). The experiment indicates that the proposed method is quite effective and ubiquitous.
引用
收藏
页码：130 / 133
页数：4
相关论文
共 50 条
  • [21] Predicting Corporate Financial Distress using KPCA and GA-based Support Vector Machine
    Zhou, Jianguo
    Bai, Tao
    2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8, 2008, : 909 - 913
  • [22] Financial Forecasting With Multivariate Adaptive Regression Splines and Queen Genetic Algorithm-Support Vector Regression
    Chen, Yuh-Jen
    Lin, Jou-An
    Chen, Yuh-Min
    Wu, Jyun-Han
    IEEE ACCESS, 2019, 7 : 112931 - 112938
  • [23] Model selection of support vector regression using particle swarm optimization algorithm
    Yang, HZ
    Shao, XG
    Chen, G
    Ding, F
    DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES A-MATHEMATICAL ANALYSIS, 2006, 13 : 1417 - 1425
  • [24] A stock selection algorithm hybridizing grey wolf optimizer and support vector regression
    Liu, Meng
    Luo, Kaiping
    Zhang, Junhuan
    Chen, Shengli
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 179
  • [25] The potentiality of support vector regression with immune algorithm for regional electric load forecasting
    Hong, Wei-Chiang
    Lee, Shao-Lun
    Lai, Chien-Yuan
    Wu, Yi-Hsien
    Wang, Kuo-Liang
    2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 2475 - +
  • [26] System reliability prediction by support vector regression with analytic selection and genetic algorithm parameters selection
    Zhao, Wei
    Tao, Tao
    Zio, Enrico
    APPLIED SOFT COMPUTING, 2015, 30 : 792 - 802
  • [27] Research on Parameters Optimization Algorithm in Support Vector Machine Based on Immune Memory Clone Strategy
    Zhu, Fang
    Wei, Junfang
    INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4, 2013, 241-244 : 1618 - +
  • [28] Using genetic algorithms for feature selection in predicting financial distresses with support vector machines
    Huang, Pei-Wen
    Liu, Chao-Lin
    2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, : 4892 - +
  • [29] Application of immune clone selection algorithm to image segmentation
    Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, China
    Dianzi Yu Xinxi Xuebao, 2006, 7 (1169-1173):
  • [30] Training Subset Selection for Support Vector Regression
    Liu, Cenru
    Cen, Jiahao
    PROCEEDINGS OF THE 2019 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 2019, : 11 - 14
12345