Fuzzy Systems Based on Universal Triple I Method and Their Response Functions

2017 ◽  
Vol 16 (02) ◽  
pp. 443-471 ◽  
Author(s):  
Yiming Tang ◽  
Fuji Ren
Keyword(s):  
Fuzzy Systems ◽  
Rule Base ◽  
Response Functions ◽  
Cri Method ◽  
Special Cases ◽  
Reasoning Mechanism ◽  
Interpolation Functions ◽  
Triple I Method

The fuzzy systems based on the universal triple I method are investigated, and then their response functions are analyzed. First, the conclusions show that 100 fuzzy systems via the universal triple I method are approximately interpolation functions, which can be used in practical systems, and that 90 ones are approximately fitted functions, which may be usable. Second, as its special cases, the Compositional Rule of Inference (CRI) method and the triple I method are discussed, with the results that 19 fuzzy systems via the CRI method and 2 ones via the triple I method are practicable. Therefore, the universal triple I method has larger effective choosing space, which can obtain more usable fuzzy systems than the others. Lastly, it is found that the first implication and second implication, respectively, embody the function of rule base and reasoning mechanism, further demonstrating the reasonability of the universal triple I method.

scholarly journals THE REAL-WORLD-SEMANTICS INTERPRETABILITY OF LINGUISTIC RULE BASES AND THE APPROXIMATE REASONING METHOD OF FUZZY SYSTEMS

2019 ◽  
Vol 57 (2) ◽  
pp. 233
Author(s):  
Nguyen Thu Anh ◽  
Tran Thai Son
Keyword(s):  
Real World ◽  
Fuzzy Systems ◽  
Graphical Representation ◽  
Approximate Reasoning ◽  
Rule Base ◽  
Computational Semantics ◽  
Mathematical Basis ◽  
The Real ◽  
Computational Structure ◽  
Application Problem

The real-world-semantics interpretability concept of fuzzy systems introduced in [1] is new for the both methodology and application and is necessary to meet the demand of establishing a mathematical basis to construct computational semantics of linguistic words so that a method developed based on handling the computational semantics of linguistic terms to simulate a human method immediately handling words can produce outputs similar to the one produced by the human method. As the real world of each application problem having its own structure which is described by certain linguistic expressions, this requirement can be ensured by imposing constraints on the interpretation assigning computational objects in the appropriate computational structure to the words so that the relationships between the computational semantics in the computational structure is the image of relationships between the real-world objects described by the word-expressions. This study will discuss more clearly the concept of real-world-semantics interpretability and point out that such requirement is a challenge to the study of the interpretability of fuzzy systems, especially for approaches within the fuzzy set framework. A methodological challenge is that it requires both the computational expression representing a given linguistic fuzzy rule base and an approximate reasoning method working on this computation expression must also preserve the real-world semantics of the application problem. Fortunately, the hedge algebra (HA) based approach demonstrates the expectation that the graphical representation of the rule of fuzzy systems and the interpolation reasoning method on them are able to preserve the real-world semantics of the real-world counterpart of the given application problem.

Research on Rule-Based Reasoning Intelligent Selection System of Injection Mold Standard Parts

2010 ◽  
Vol 102-104 ◽  
pp. 432-435 ◽  
Author(s):  
Bai Zhong Wu ◽  
Bin Gao ◽  
Rong Song
Keyword(s):  
Rule Base ◽  
Injection Mold ◽  
Selection System ◽  
Rule Based ◽  
Standard Parts Library ◽  
Parts Library ◽  
Reasoning Mechanism ◽  
Selection Of

The use of rule-based reasoning technology can realize the intelligent selection of mold standard parts when designing injection mold. In this paper, the selection experience of mold standard parts are stored to databases for scientifically choosing mold base, sprue bushings, ejector pins, and other standard parts. And through the establishment of a rule base, reasoning mechanism, standard parts library, a rule-based reasoning intelligent selection system of injection mold standard parts is proposed and details of the proposed approach are presented.

Advanced Techniques for Measuring Structural Mobilities

1988 ◽  
Vol 110 (3) ◽  
pp. 345-349 ◽  
Author(s):  
J. A. Fabunmi ◽  
F. A. Tasker
Keyword(s):  
Frequency Response ◽  
General Equation ◽  
Theoretical Basis ◽  
Weighting Function ◽  
Experimental Results ◽  
Expected Improvement ◽  
Response Functions ◽  
Proper Selection ◽  
Special Cases ◽  
Selection Of

A unified formulation of the equations for estimating structural frequency response functions is presented. The more popular approaches are shown to be special cases of a general equation which involves a weighting function, the proper selection of which can yield substantial improvements in the accuracy and efficiency of the measurement process. The theoretical basis for selecting the weighting function is also presented, along with experimental results which confirm the expected improvement in accuracy of the advanced formulations over existing methods.

Rule Base Reduction and Genetic Tuning of Fuzzy Systems Based on the Linguistic 3-tuples Representation

2006 ◽  
Vol 11 (5) ◽  
pp. 401-419 ◽  
Author(s):  
Rafael Alcalá ◽  
Jesús Alcalá-Fdez ◽  
María José Gacto ◽  
Francisco Herrera
Keyword(s):  
Fuzzy Systems ◽  
Rule Base ◽  
Genetic Tuning

scholarly journals Information Aggregation in Intelligent Systems Using Generalized Operators

2006 ◽  
Vol 1 (1) ◽  
pp. 47 ◽  
Author(s):  
Imre J. Rudas ◽  
János Fodor
Keyword(s):  
Intelligent Systems ◽  
Fuzzy Rule ◽  
Information Aggregation ◽  
Rule Base ◽  
Membership Functions ◽  
Fuzzy Rule Base ◽  
Aggregation Of Information ◽  
Control Decision ◽  
Reasoning Mechanism ◽  
Fuzzy Connectives

Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy control, decision support and expert systems. Since the advent of fuzzy sets a great number of fuzzy connectives, aggregation operators have been introduced. Some families of such operators (like t-norms) have become standard in the field. Nevertheless, it also became clear that these operators do not always follow the real phenomena. Therefore, there is a natural need for finding new operators to develop more sophisticated intelligent systems. This paper summarizes the research results of the authors that have been carried out in recent years on generalization of conventional operators.

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