Computing with words and its relationships with fuzzistics

By Jerry M. Mendel. Information Sciences, 2007

335 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/551d83ba2c2a7dedb200782885b80f10340c8660

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Citations in the corpus

Handbook of Granular Computing (2008, background): “New methods or even a new science should be developed for such modeling [123].”
Encoding Words Into Interval Type-2 Fuzzy Sets Using an Interval Approach (2008, background): “, [1], [4], [9], [12], [26], [27], [29], [30], and [34]–[38]; however, as claimed in [12]–[15] and [17], “Words mean different things to different people, and so are uncertain.”
Computing the Numerical Scale of the Linguistic Term Set for the 2-Tuple Fuzzy Linguistic Representation Model (2009, background): “2032172 1) the semantic model [11], [36]–[38], [49]–[52]; 2) the symbolic model [12], [21]; 3) the model based on linguistic 2-tuples [22], [43].”
Computing with words in decision making: foundations, trends and prospects (2009, methodology): “Linguistic variables and the CW methodology have been a great field of research since its foundations: Zadeh in [125, 126, 127, 129], Mendel in [83] and Trillas et al.”
Computing with Words in Decision support Systems: An overview on Models and Applications (2010, background): “• In 68 “Words mean different things to different people and so are uncertain.”
Advances in type-2 fuzzy sets and systems (2007, methodology): “In a second approach, called the interval end-points approach [ 53 ], we:”
A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets (2009, background): “For example, they can be utilized for extrapolating evidence, assessing the strength of relationship between given groups of variables, assessing the influence of given input variables on given output variables, measuring the loss of information when a system is simplified, and the like’’.”
A Historical Account of Types of Fuzzy Sets and Their Relationships (2016, methodology): “on computing with words and perceptual computing [95], [96], [98], [99], by Hagras [68], [69], by Castillo in control [35], and by Xia et al.”