Linguistic-Valued Approximate Reasoning With Lattice Ordered Linguistic-Valued Credibility

Linguistic terms are often used to represent the truth degree or credibility degree to manage the uncertainty or imprecision as one of popular ways of knowledge representation in the perception-based decision making problem. This present work represents the credibility of uncertain knowledge using linguistic values. The linguistic-valued credibility is then modeled based on a lattice ordered logical algebra lattice implication algebra (LIA) and then used in the linguistic-valued based on approximated reasoning. This approach can better express both comparable and incomparable linguistic valued credibility information in knowledge base representation. And it can also fit to approximate reasoning under a fuzzy environment with both comparable and incomparable linguistic credibility. Examples illustrate that the proposed approach can retain the original information and can simulate people’s way of thinking through reasoning with words.