Research On Fuzzy Information Processing Based On Medium Logic

Fuzzy information processing is widely involved in the production and lives in the modern society. Medium logic, established by Chinese scholars, is a formal logic system for differentiating contradictory negation from opposite negation and implies that there exist some medium objects between some opposite concepts, which realize the extention from exact objects to fuzzy objects. Therefor it is a useful work that how to put the medium logic theoery into fuzzy information prosessing.In chapter 1, the paper mainly introduces the research results about negative relation of fuzzy information currently. In chapter 2, it makes an introduction of concept essence of negative knowledge, as consideres that negations in distinct knowledge includes two kinds and there are three kinds of negative relations about fuzzy knowledge, namely Contradictory negation, Opposite negation and Medium negation. In chapter 3, firstly it introduces the basic theoery and background of medium logic, then provides its interpretation of infinite-valued modle and gives both semantic and logic description. In the last part of the chapter, we also present the disadvantages of the current logic for processing the negative relations.Based on medium logic and distance measure, fuzzy evalution matrix is established with medium truth rade function in chapter 4, and the index of fuzzy evalution is educed by considering positive information and negative information of fuzzy evalution factors. Then the evaluation objects are compared by the evaluation index which is regarded as the basis of comprehensive evaluation. Therefore a new kind of fuzzy comprehensive evaluation model is constructed, the application of which is discussed by an example in the end of the paper.Whether the quantization of fuzzy linguistic variables is reasonable is directly associate with rationality of fuzzy reasoning results. Chapter 5 firstly gives individual truth grade function adopting distance ration function based on the semanic of fuzzy linguistic variables and the background of medium logic, then proposes a new fuzzy tone operator in virtue of the notion of infinite valued semanic model for medium predicate logic, which is put into a special example for discussing finally.Medium logic completely reflects both opposite relation and contradictory relation. Chapter 6 first improves the infinite-valued semantic model of medium logic and then puts a semantic interpretation. After that it expands the CRI algorithm bought forward by Zadeh, and obtains another algorithm based on the notion of medium logic. Meanwhile the semantic match degree including semantic similarity and semantic distance are put forward.A special example validates the rationality of the extended algorithm at last.