A new attitude coupled with the basic thinking to ordering for ranking fuzzy ‎numbers‎

دراين مقاله، يك مدل براي پيش بيني غلظت ذرات معلق NO, CO, SO2 ,PM2.5 ,PM10 وO3 ارايه گرديده است. اين روش به داده هاي گذشته، بويژه اطلاعات پيش بيني آب و هوا، اطلاعات آب وهوا ي واقعي و داده هاي آلودگي ، براي تعداد زيادي از داده هاي زماني نياز دارد. ايده، تطبيق دادن داده هاي پيش بيني با داده هاي پيش بيني مشابه در مجموعه دادهاي گذشته و سپس با استفاده از داده هاي آب و هواي واقعي و داده هاي آلودگي است.به منظور متراكم ساختن نقاط زماني ، داده هاي پيش بيني مذكور با يك تابع فاصله محاسبه مي گردند وعدد فازي از دادها ، شامل دادهاي پيش بيني و داده هاي واقعي، ارايه مي گردد. بار دگر نيز، با يك تابع فاصله، داده هاي واقعي در مقايسه با عدد فازي براي تعيين درجه عضويت ، صورت مي پذيرد.اين مدل به گونه اي تهيه مي گردد كه تمام داده هاي معمولاَ پر هرج و مرج و نا مشخص ، مورد استفاده قرار مي گيرد.

‎Ranking fuzzy numbers is generalization of the concepts of order, and class, and so have fundamental applications. Moreover, deriving the final efficiency and powerful ranking are helpful to decision makers when solving fuzzy problems. Selecting a good ranking method can apply to choosing a desired criterion in a fuzzy environment. There are numerous methods proposed for the ranking of fuzzy numbers, some of them seem to be good in a particular context but not in general. In this paper, a new attitude coupled with the basic thinking of ordering for ranking of fuzzy numbers is proposed. The properties of the proposed method are discussed in detail. The ranking results show that the proposed method can overcome certain shortcomings that exist in the previous ranking methods.The method also has very easy and simple calculations compared to other methods. Finally, numerical examples are presented to illustrate the advantage of our proposed method, and compare them with other common ranking methods. The future prospect of this paper is a new attitude to fuzzy distance, which will be referred to in the ‎end.