Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKongliang Zhuen_US
dc.contributor.authorOlga Koshelevaen_US
dc.contributor.authorVladik Kreinovichen_US
dc.description.abstract© 2016 by the Mathematical Association of Thailand. All rights reserved. In many application areas including economics, experts describe their knowledge by using imprecise (“fuzzy”) words from natural language. To design an automatic control system, it is therefore necessary to translate this knowledge into precise computer-understandable terms. To perform such a translation, a special semi-heuristic fuzzy methodology was designed. This methodology has been successfully applied to many practical problem, but its semi-heuristic character is a big obstacle to its use: without a theoretical justification, we are never 100% sure that this methodology will be successful in other applications as well. It is therefore desirable to come up with either a theoretical justification of exactly this methodology, or with a theoretically justified modification of this methodology. In this paper, we apply the Bayesian techniques to the above translation problem, and we analyze when the resulting methodology is identical to fuzzy techniques – and when it is different.en_US
dc.titleBayesian approach to intelligent control and its relation to fuzzy controlen_US
article.title.sourcetitleThai Journal of Mathematicsen_US
article.volume14en_US Mai Universityen_US of Texas at El Pasoen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.

Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.