Applications of Fuzzy Sets in Industrial Engineering: A Topical Classification

Kahraman, Cengiz; Gülbay, Murat; Kabak, Özgür

doi:10.1007/3-540-33517-x_1

Cited by 49 publications

(35 citation statements)

References 140 publications

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“…The theory has been applied in a great variety of applications and reviewed by several authors (Kahraman et al, 2006;Klir and Yuan, 1995;Lootsma, 1997;Zimmermann, 1996).…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

A FSA based fuzzy DEMATEL approach for risk assessment of cargo ships at coasts and open seas of Turkey

et al. 2015

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“…The theory has been applied in a great variety of applications and reviewed by several authors (Kahraman et al, 2006;Klir and Yuan, 1995;Lootsma, 1997;Zimmermann, 1996).…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

A FSA based fuzzy DEMATEL approach for risk assessment of cargo ships at coasts and open seas of Turkey

et al. 2015

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“…Much work has been completed using the fuzzy linguistic approach and the 2-tuple model in many situations: distributed agents [16], genetic learning [17], industrial engineering [18], multicriteria decision-making [19], fuzzy decision tools [20], human resource management [21], and so forth.…”

Section: Computing With Words and Fuzzy Logicmentioning

confidence: 99%

Natural Language Processing and Fuzzy Tools for Business Processes in a Geolocation Context

Truck

Abchir

2017

Advances in Artificial Intelligence

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In the geolocation field where high-level programs and low-level devices coexist, it is often difficult to find a friendly user interface to configure all the parameters. The challenge addressed in this paper is to propose intuitive and simple, thus natural language interfaces to interact with low-level devices. Such interfaces contain natural language processing (NLP) and fuzzy representations of words that facilitate the elicitation of business-level objectives in our context. A complete methodology is proposed, from the lexicon construction to a dialogue software agent including a fuzzy linguistic representation, based on synonymy.

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“…1, traditional mathematical modelling techniques are expected to tackle the problems that contain crisp data. On the other hand, fuzzy models are more suitable for the systems where it is difficult to derive a crisp mathematical model [6]. The problems that contain words and/or perceptions cannot be easily tackled by using the traditional mathematical modelling techniques.…”

Section: Introductionmentioning

confidence: 99%