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Industrial applications of type-2 fuzzy sets and systems: A concise review

机译:类型2模糊集和系统的工业应用:简明回顾

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Data, as being the vital input of systemmodelling, contain dissimilar level of imprecision that necessitates differentmodelling approaches for proper analysis of the systems. Numbers, words and perceptions are the forms of data that has varying levels of imprecision. Existing approaches in the literature indicate that, computation of different data forms are closely linked with the level of imprecision, which the data already have. Traditional mathematical modelling techniques have been used to compute the numbers that have the least imprecision. Type-1 fuzzy setshave beenusedforwords and type-2 fuzzy setshave beenemployed for perceptionswhere the level of imprecision is relatively high.However, inmanycases ithas not been easy to decide whether a solution requires a traditional approach, i.e., type-1 fuzzy approach or type-2 fuzzy approach. It has been a difficult matter to decide what types of problems really require modelling and solution either with type-1 or type-2 fuzzy approach. It is certain that, without properly distinguishing differences between the two approaches, application of type-1 and type-2 fuzzy sets and systems would probably fail to develop robust and reliable solutions for the problems of industry. In this respect, a reviewof the industrial applications of type-2 fuzzy sets, which are relatively novel to model imprecision has been considered in thiswork. The fundamental focus of thework has been based on the basic reasons of the need for type-2 fuzzy sets for the existing studies.With this purpose inmind, type-2 fuzzy sets articles have been selected from the literature using the online databases of ISI-Web of Science, ScienceDirect, SpringerLink, Informaworld, Engineering Village, Emerald and IEEE Xplore. Both the terms “type-2 fuzzy” and “application” have been searched as the main keywords in the topics of the studies to retrieve the relevant works. The analysis on the industrial applications of type-2 fuzzy sets/systems (FSs) in different topics allowed us tosummarize the existing researchareas andtherefore it isexpectedbe useful toprioritize future research topics. This review shows that there are still many opportunities for application of type-2 FSs for several different problemdomains. Shortcomings of type-1 FSs can also be considered as an opportunity for the application of type-2 FSs in order to provide a better solution approach for industrial problems.
机译:数据作为系统建模的重要输入,包含不同程度的不精确度,因此需要不同的建模方法来对系统进行正确的分析。数字,单词和感知是不精确程度各异的数据形式。文献中的现有方法表明,不同数据形式的计算与数据已经具有的不精确度紧密相关。传统的数学建模技术已用于计算不精确度最小的数字。对于不精确度较高的感知,使用了1型模糊集和2型模糊集。但是,在许多情况下,很难确定解决方案是否需要传统方法,例如1型模糊方法或2模糊方法。很难确定哪种类型的问题真正需要使用类型1或类型2模糊方法进行建模和解决。可以肯定的是,如果没有适当地区分这两种方法之间的差异,则类型1和类型2模糊集和系统的应用可能无法为工业问题开发健壮而可靠的解决方案。在这方面,在这项工作中考虑了对类型2模糊集的工业应用的回顾,该模型对于模型的不精确性相对较新。这项工作的基本重点是基于现有研究需要2型模糊集的基本原因。为此目的,我们使用ISI-的在线数据库从文献中选择了2型模糊集的文章。 Web of Science,ScienceDirect,SpringerLink,Informaworld,Engineering Village,Emerald和IEEE Xplore。在研究主题中搜索了“ 2型模糊”和“应用”这两个词作为主要关键词,以检索相关作品。对不同主题的2型模糊集/系统(FSs)的工业应用的分析使我们能够总结现有的研究领域,因此有望将其用于未来的研究领域。这次审查表明,在几个不同的问题域中,仍然有很多机会使用2型FS。为了为工业问题提供更好的解决方案,类型1 FS的缺点也可以视为应用类型2 FS的机会。

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