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Information Journal Paper

Title

A META-HEURISTIC MULTI-OBJECTIVE FUZZY SIMPLEX-GENETIC ALGORITHM FOR CREDIT RATING PREDICTION OF BANKS CUSTOMERS

Pages

  80-91

Abstract

 This study examines a multi-objective fuzzy simplex-genetic algorithm which was developed to predict bank legal customers financial performance. Prediction performance of the model was examined based on its ability to accurately identify credit default. Using available data from KESHVARZI bank over 2001-2006, debt ratio, operational ratio, and return on equity are selected as descriptive variables, and on the other side dependent variable was considered as a dummy variable. To training and validating the model, data were divided in to model (in-sample) and test (out-of-sample) sets. After running the algorithm, besides the sensitivity and specificity ratios, the key variable was specified.

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    Cite

    APA: Copy

    AKHBARI, M., & MOKHATAB RAFIEI, FARIMAH. (2012). A META-HEURISTIC MULTI-OBJECTIVE FUZZY SIMPLEX-GENETIC ALGORITHM FOR CREDIT RATING PREDICTION OF BANKS CUSTOMERS. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN), 23(1), 80-91. SID. https://sid.ir/paper/65652/en

    Vancouver: Copy

    AKHBARI M., MOKHATAB RAFIEI FARIMAH. A META-HEURISTIC MULTI-OBJECTIVE FUZZY SIMPLEX-GENETIC ALGORITHM FOR CREDIT RATING PREDICTION OF BANKS CUSTOMERS. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)[Internet]. 2012;23(1):80-91. Available from: https://sid.ir/paper/65652/en

    IEEE: Copy

    M. AKHBARI, and FARIMAH MOKHATAB RAFIEI, “A META-HEURISTIC MULTI-OBJECTIVE FUZZY SIMPLEX-GENETIC ALGORITHM FOR CREDIT RATING PREDICTION OF BANKS CUSTOMERS,” INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN), vol. 23, no. 1, pp. 80–91, 2012, [Online]. Available: https://sid.ir/paper/65652/en

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