نتایج جستجو برای: interval type 2 fuzzy sets it2fss

تعداد نتایج: 3803887  

2015
Bo Yao Hani Hagras

I Acknowledgments IV List of Figures X List of Tables XIV List of Abbreviations XV Publications Arising from This Work XVIII Chapter 1: Introduction .................................................................................................. 1 1.1 Aims, Significance, Novelty ........................................................................... 6 1.1.1 Aims .............................

2006
Simon Coupland

Recently there has been significant growth in research interest in type-2 fuzzy logic. Type-2 fuzzy logic is extension of type-1 (regular) fuzzy logic where the membership grade in a fuzzy set is itself measured as a fuzzy number. Much of this growth has only been concerned with type-2 interval fuzzy systems, a subset of type-2 fuzzy systems, where the membership grade of a fuzzy set is given a...

Journal: :Information Sciences 2021

Electric vehicles are the key to facilitating transition low-carbon ‘green’ transport. However, there concerns with their range and location of charging stations which delay a full-fledged adoption use. Hence, electric infrastructure in given region is critical mitigating those concerns. In this study, an interval type-2 fuzzy set based multi-criteria decision-making method introduced for selec...

Journal: :Mathematical Problems in Engineering 2013

Journal: :INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS 2019

Journal: :Expert Syst. Appl. 2015
Lazim Abdullah Norsyahida Zulkifli

The fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy decision making trial and evaluation laboratory (fuzzy DEMATEL) have been used to obtain weights for criteria and relationships among dimensions and criteria respectively. The twomethods could be integrated since it serves different purposes. Previous research suggested that the weights of criteria and the relationships among dimensions...

2014
A. NIEWIADOMSKI M. KACPROWICZ

This paper presents research on applications of fuzzy logic and higher-order fuzzy logic systems to control filters reducing air pollution [1]. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert. The goal of the research is to control an SCR system responsible for emission of nitrogen oxide (NO) and nitrogen dioxide ...

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