کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
397844 1438430 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Extended rough set model based on known same probability dominant valued tolerance relation
ترجمه فارسی عنوان
مدل تقریبی خالص بر مبنای رابطه ی تحمل گرانقیمت غالب با احتمال مشابه شناخته شده است
کلمات کلیدی
مجموعه خشن، سیستم اطلاعاتی ناقص، ارزش تحمل رابطه، احتمالا شناخته شده غالب، عملکرد تابع رده
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A non-equivalence relation (KPDVT) for incomplete information system is proposed.
• Extended rough set model based on KPDVT is presented.
• A performance index (ICU) for generalized indiscernibility relations is proposed.

Classical rough set theory is based on the conventional indiscernibility relation. It is not suitable for analyzing incomplete information. Some successful extended rough set models based on different non-equivalence relations have been proposed. The data-driven valued tolerance relation is such a non-equivalence relation. However, the calculation method of tolerance degree has some limitations. In this paper, known same probability dominant valued tolerance relation is proposed to solve this problem. On this basis, an extended rough set model based on known same probability dominant valued tolerance relation is presented. Some properties of the new model are analyzed. In order to compare the classification performance of different generalized indiscernibility relations, based on the category utility function in cluster analysis, an incomplete category utility function is proposed, which can measure the classification performance of different generalized indiscernibility relations effectively. Experimental results show that the known same probability dominant valued tolerance relation can get better classification results than other generalized indiscernibility relations.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Approximate Reasoning - Volume 74, July 2016, Pages 108–119
نویسندگان
, ,