A Reasoning Method Based on the Linguistic-Valued Layered Aggregation

摘要

Uncertainty reasoning is playing an increasingly significant role in artificial intelligence which will help people infer the result or predict the tendency they need. In people’s common sense, reasoning problems are always in the context with precise numbers, while it cannot as intelligent as linguistic-valued information. Although some methods have obtained successful results using positive evidence, some still need to be addressed both positive and negative evidence. Based on the layered linguistic-valued intuitionistic fuzzy lattice (LV-IFL), we realize that aggregate the linguistic-valued information through the layered average aggregation (LAA) operator presented by in this paper. Combining the multiple multi-dimensional fuzzy reasoning model, a reasoning evaluation model on the basis of linguistic-valued layered intuitionistic fuzzy lattice which simulates the reasoning of human language is submitted and the practical examples are given to illustrate the rationality and validity of the method.