کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4942698 | 1437417 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hesitant distance set on hesitant fuzzy sets and its application in urban road traffic state identification
ترجمه فارسی عنوان
فاصله فشرده بر روی مجموعه های فازی تنگ و کاربرد آن در شناسایی وضعیت ترافیک شهری
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کلمات کلیدی
مجموعه های فازی ناخواسته، فاصله حیرت انگیز، درجه اطمینان، روش آماری، تشخیص الگو، جبر فضا، شناسایی وضعیت ترافیک،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Since fuzziness lacks the distinction between a set and its complement, it is difficult to measure the distance between different hesitant fuzzy sets (HFSs) by a single value. In this study, a new concept “hesitant distance set (HDS)” is proposed, where the distance between different HFSs can be characterized by a series of different values. This study has three primary contributions. Firstly, most of the existing distance measures on HFSs are based on vector operation, while the novel proposed HDSs are based on set operation. Secondly, a statistical method is proposed to compare different HDSs, and some important properties of the comparison method are introduced. Thirdly, the characteristics of the novel HDSs and the classical hesitant distances are studied comparatively. Finally, the practicality and validity of the HDSs on HFSs are illustrated through an urban road traffic state identification example.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 61, May 2017, Pages 57-64
Journal: Engineering Applications of Artificial Intelligence - Volume 61, May 2017, Pages 57-64
نویسندگان
Fangwei Zhang, Jianbo Li, Jihong Chen, Jing Sun, Augustine Attey,