Fuzzy Reasoning Method By Optimizing The Similarity Of Truth-tables Based On Triangular Fuzzy

Since Zadeh first proposed CRI（Compositional Rule of Inference）Inference algorithm for solving FMP and FMT two kinds of fuzzy Inference models in 1973,fuzzy Inference has been widely used in fuzzy control,fuzzy data mining,artificial intelligence,image processing and other fields.And through the verification of time,it has achieved extraordinary success.Although Zadeh created a new era of fuzzy mathematics,his CRI algorithm lacks rigorous logic foundation.Professor Wang Guojun,a famous scholar in China,pointed out the shortcomings of CRI algorithm in logic and semantics,and then proposed a new fuzzy reasoning method called the all-inclusive triple I algorithm,which is abbreviated as triple I algorithm.Triple I algorithm is an improvement of CRI algorithm and is more reasonable than the classical CRI algorithm in fuzzy logic.In recent years,many scholars have carried out in-depth research on the triple I algorithm,and set off a hot wave of research on the solution form of triple I algorithm based on different implication operators and other fuzzy inference algorithms.Although three-i algorithm fuzzy reasoning has achieved good results in many fields,there are still many problems to be optimized.Especially in the case of input and output rules,it is difficult to get the optimal solution with the general three-i inference algorithm.Therefore,in this paper,based on the limited triangle fuzzy number as the input and output,the idea of true domain close to fuzzy reasoning is analyzed and studied,and the true domain close to fuzzy reasoning algorithm based on triangle fuzzy number is proposed.The main contents of this paper are as follows:Firstly,due to the close relationship between optimization problem and fuzzy closeness,this paper will analyze the optimization problem and fuzzy closeness,study the related properties of closeness,strictly monotonic closeness function and give the commonly used closeness formula.Secondly,the single point fuzzification,which is the most commonly used in fuzzy control,is studied and analyzed,and the reasoning results and proof of the single point fuzzification satisfying the true domain close to fuzzy reasoning algorithm are given.The common implication operators are analyzed and introduced,which lays a foundation for the construction of the algorithm later.Thirdly,the construction of shower proximity fuzzy reasoning algorithm based on triangular fuzzy number.The triangular fuzzy number used is a fuzzy set on the continuous universe.Therefore,firstly,the closeness degree on the continuous universe is constructed to measure the closeness degree of the two fuzzy sets,and the implication operator is used to construct the true domain.Then,it is given that the input variables are triangular fuzzy numbers,and the true domain proximity fuzzy reasoning algorithm formula based on Mamdani implication operator and proximity degree is used and proved.Fourthly,through simulation experiments,the reasoning ability of the true domain proximity fuzzy reasoning algorithm using Mamdani implication operator and proximity degree is analyzed.Through the experimental results,it is analyzed that Mamdani implication operator and the true domain proximity fuzzy reasoning algorithm of proximity degree have certain advantages.