The subject of this work is to establish a mathematical framework that provide the basis and tool for uncertainty reasoning based on linguistic information. This paper focuses on a flexible and realistic approach, i.e., the use of linguistic terms, specially, the symbolic approach acts by direct computation on linguistic terms. An algebra model with linguistic terms, which is based on a logical algebraic structure, i.e., lattice implication algebra, is applied to represent imprecise information and deals with both comparable and incomparable linguistic terms (i.e., non-ordered linguistic terms). Within this framework, some inferential rules are analyzed and extended to deal with these kinds of lattice-valued linguistic information. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Chen, S., Xu, Y., & Ma, J. (2005). A linguistic truth-valued uncertainty reasoning model based on lattice-valued logic. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3613, pp. 276–284). Springer Verlag. https://doi.org/10.1007/11539506_35
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