سال انتشار: ۱۳۸۶

محل انتشار: پنجمین کنفرانس ملی مهندسی صنایع

تعداد صفحات: ۷

نویسنده(ها):

Siamak Noori – Industrial Engineering Department of Iran University of Technology, Assistant Professor
Alireza Hajiakhoundi – Payamnoor University – Parand Branch
Mashall Aryan – Payamnoor University – Parand Branch

چکیده:

The XCS classifier system has shown to solve typical classification problems competitively to other machine learning algorithms. This paper is to introduce a flexible classifier selection method for generating match set, with respect to the system performance during the training. It also presents a complementary part for the Search Component of the classifier system in which new classifiers are created regarding the input message form the environment, and previous knowledge. The modified XCS learns more reliable and performs obviously better than traditional XCS.