این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Iranian Journal of Fuzzy Systems، جلد ۲۰، شماره ۵، صفحات ۱۸۹-۱۹۷

عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله

عنوان انگلیسی ( 2304-8012 ) Intuitionistic fuzzy type basic uncertain information
چکیده انگلیسی مقاله Recently, a new paradigm for uncertain information has been proposed that can effectively handle various types ofuncertainty in decision-making problems. This approach utilizes a certainty degree, which is represented by a realnumber indicating the level of certainty associated with input values. However, just like intuitionistic fuzzy informationcan handle more problems that cannot be well modeled by fuzzy information, the certainty degree in basic uncertaininformation can also be intuitionistic fuzzy granule, which allows it to handle more uncertainty involved decision makingsituations. In this paper, we introduce the concept of intuitionistic fuzzy type basic uncertain information and explainits parameters. We also define a weighted arithmetic mean for aggregating this type of information and discuss differentapproaches for allocating induced weights based on trust preferred preference from four perspectives: (i) preference forhigher certainty degrees; (ii) aversion to higher levels of uncertainty; (iii) preference for greater differences in certaintydegrees; and (iv) preference for intuitionistic fuzzy certainties. Additionally, we explore trichotomic rules-based decisionmaking using intuitionistic fuzzy type basic uncertain information. Finally, we present an objective-subjective evaluationnumerical example utilizing these methods.
کلیدواژه‌های انگلیسی مقاله Aggregation operator, basic uncertain information, Information fusion, intuitionistic fuzzy type basic uncertain information, preference involved evaluation, rules-based decision making

نویسندگان مقاله L. S. Jin |
School of Automobile and Traffic Engineering, Hubei University of Arts and Sciences, Xiangyang, 441053, China; School of Business, Nanjing Normal University, Nanjing, China

R. R. Yager |
Machine Intelligence Institute, Iona College, New Rochelle, NY

L. M. Lopez |
Department of Computer Science, University of Jaen, 23071-Jaen, Spain

L. M. Lopez |
Department of Computer Science, University of Jaen, 23071-Jaen, Spain

R. M. Rodrguez |
Department of Computer Science, University of Jaen, 23071-Jaen, Spain

T. Senapati |
Department of Mathematics, Padima Janakalyan Banipith, Kukrakhupi, Jhargram, 721517, India

R. Mesiar |
Faculty of Civil Engineering, Slovak University of Technology, Radlinskho 11, Sk-810 05 Bratislava, Slovakia; Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, CE IT4Innovations, 30. dubna 22, 701 03 Ostrava, Czech Republic


نشانی اینترنتی https://ijfs.usb.ac.ir/article_7840_33b71bee6e7ea2c73b1d6a73fca27ed7.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات