On the problem of retranslation in computing with perceptions

Martin, Olga; Klir, George J.

doi:10.1080/03081070600861123

Cited by 37 publications

(21 citation statements)

References 11 publications

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“…This process is called linguistic approximation by Zadeh [136], retranslation by some other authors [61,124], and decoding in Perceptual Computing. Subsethood and similarity measures [60,68,113] are often used to do this.…”

Section: Translating the Solution Back Into Wordsmentioning

confidence: 99%

Advanced Computing with Words: Status and Challenges

Mendel

Rajati

2015

Towards the Future of Fuzzy Logic

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In this chapter, we focus on the status of Advanced Computing with Words (ACWW) and the challenges that it may encounter in the future. First, we elaborate on the notion of Computing with Words (CWW) and its various subareas. Then we present some non-engineering ACWW problems and connect them to more realistic engineering problems, after which we provide a roadmap for solving ACWW problems, and show how the Generalized Extension Principle (GEP) can be used to formulate their solutions. We also propose a syllogistic approach to solving ACWW problems that also uses the Extension Principle but in a different way. Finally, we discuss present and future challenges to ACWW, i.e. we explain what challenges ACWW encounters given the current trend of data abundance and widespread use of Internet for dealing with questions posed in natural languages. Introduction: Computing with Words and Advanced Computing with WordsComputing with Words (CWW or CW) [11,29,34,66,69,70,75,91,104,109,142,144,147,154] was probably conceived as the main area of application of fuzzy logic [132] when the field was originated. It is a methodology of computation whose objects are words rather than numbers, although those words are linked to numbers and classical calculations that can be carried out by computing machinery, via membership functions of fuzzy sets associated with words. To do that, a process called precisiation of meaning [152] is essential, which, in a nutshell, is determining membership functions of the fuzzy sets that model the words. Zadeh distinguishes two subareas for CWW:1. Basic Computing with Words (BCWW), which mainly deals with descriptions of complex systems in terms of fuzzy IF-THEN rules [134]. Soft constraints are generally possibilistic, i.e. they describe (physical) attributes like speed, temperature,

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Section: Translating the Solution Back Into Wordsmentioning

confidence: 99%

Advanced Computing with Words: Status and Challenges

Mendel

Rajati

2015

Towards the Future of Fuzzy Logic

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“…(Mendel 2008) Another important concept is the retranslation process in CW, that is, to approximately describe a given fuzzy set in natural language. Yager (2004) studied this problem and Martin and Klir (2006) presented two new different approaches to deal with this retranslation problem in the computing with perceptions field.…”

Section: A Bird's Eye View On Cwmentioning

confidence: 99%

“…Therefore, it is necessary to apply an approximation function app 1 (·) to associate it to a particular label on T (L)-the retranslation problem (Martin and Klir 2006;Yager 2004)-or to use fuzzy ranking procedures to obtain a final order of the alternatives: …”

Section: Linguistic Computational Model Based On Membership Functionsmentioning

confidence: 99%

Computing with words in decision making: foundations, trends and prospects

Herrera

Alonso

Chiclana

et al. 2009

Fuzzy Optim Decis Making

457

187

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Computing with Words (CW) methodology has been used in several different environments to narrow the differences between human reasoning and computing. As Decision Making is a typical human mental process, it seems natural to apply the CW methodology in order to create and enrich decision models in which the information that is provided and manipulated has a qualitative nature. In this paper we make a review of the developments of CW in decision making. We begin with an overview of the CW methodology and we explore different linguistic computational models that have been applied to the decision making field. Then we present an historical perspective of CW in decision making by examining the pioneer papers in the field along with its most recent applications. Finally, some current trends, open questions and prospects in the topic are pointed out.

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“…With this in mind one can consider the introduction of a process of retranslation [25,13]. Here starting with the aggregated ranges, .…”

Section: General Approach To Aggregation Of Imprecise Uncertainty Meamentioning

confidence: 99%