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https://doi.org/10.2498/cit.2002.04.02

Reasoning with Non-Numeric Linguistic Variables

Nigel Steele
Helen Robinson
Jon Williams

Puni tekst: engleski, pdf (409 KB) str. 261-281 preuzimanja: 1.051* citiraj
APA 6th Edition
Steele, N., Robinson, H. i Williams, J. (2002). Reasoning with Non-Numeric Linguistic Variables. Journal of computing and information technology, 10 (4), 261-281. https://doi.org/10.2498/cit.2002.04.02
MLA 8th Edition
Steele, Nigel, et al. "Reasoning with Non-Numeric Linguistic Variables." Journal of computing and information technology, vol. 10, br. 4, 2002, str. 261-281. https://doi.org/10.2498/cit.2002.04.02. Citirano 25.10.2020.
Chicago 17th Edition
Steele, Nigel, Helen Robinson i Jon Williams. "Reasoning with Non-Numeric Linguistic Variables." Journal of computing and information technology 10, br. 4 (2002): 261-281. https://doi.org/10.2498/cit.2002.04.02
Harvard
Steele, N., Robinson, H., i Williams, J. (2002). 'Reasoning with Non-Numeric Linguistic Variables', Journal of computing and information technology, 10(4), str. 261-281. https://doi.org/10.2498/cit.2002.04.02
Vancouver
Steele N, Robinson H, Williams J. Reasoning with Non-Numeric Linguistic Variables. Journal of computing and information technology [Internet]. 2002 [pristupljeno 25.10.2020.];10(4):261-281. https://doi.org/10.2498/cit.2002.04.02
IEEE
N. Steele, H. Robinson i J. Williams, "Reasoning with Non-Numeric Linguistic Variables", Journal of computing and information technology, vol.10, br. 4, str. 261-281, 2002. [Online]. https://doi.org/10.2498/cit.2002.04.02

Sažetak
Where decisions are based on imprecise numeric data and linguistic variables, the development of automated decision aids presents particular difficulties. In such applications, linguistic variables often take their values from a pre-ordered set of vaguely defined linguistic terms. The mathematical structures that arise from the assumption that sets of linguistic terms are pair-wise tolerant are considered. A homomorphism between tolerance spaces, filter bases and fuzzy numbers is shown. A proposal for modeling linguistic terms with an ordered set of fuzzy numbers is introduced. A procedure for structured knowledge acquisition based on the topology of the term sets and the cognitive theory of prototypes is shown to give rise to sparse rule bases. Similarity as a function of “distance” between fuzzy numbers treated as tolerance mappings is used as an inference mechanism in sparse rule bases to give linguistically valued outputs. Measuring the “distance” between fuzzy sets to correspond to intuitive notions of nearness is not straightforward, since the usual metric axioms are not adequate. An alternative way of measuring “distance” between fuzzy numbers is introduced, which reduces to the usual one when applied to crisp numbers.

Hrčak ID: 44769

URI
https://hrcak.srce.hr/44769

Posjeta: 1.194 *