کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386881 660892 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Feature selection to diagnose a business crisis by using a real GA-based support vector machine: An empirical study
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Feature selection to diagnose a business crisis by using a real GA-based support vector machine: An empirical study
چکیده انگلیسی

This research is aimed at establishing the diagnosis models for business crises through integrating a real-valued genetic algorithm to determine the optimum parameters and SVM to perform learning and classification on data. After finishing the training processes, the proposed GA-SVM can reach a prediction accuracy of up to 95.56% for all the tested business data. Particularly, only six influential features are included in the proposed model with intellectual capital and financial features after the 2-phase selecting process; the six features are ordinary and widely available from public business reports. The proposed GA-SVM is available for business managers to conduct self-diagnosis in order to realize whether business units are really facing a crisis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 35, Issue 3, October 2008, Pages 1145–1155
نویسندگان
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