A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The consolidation of neural networks and fuzzy logic in neurofuzzy models provides learning as well as readability. This paper aims at modeling the input-output relationship with fuzzy IF-THEN rules by using fuzzy clustering technique. The main difference between fuzzy cluster...

A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The consolidation of neural networks and fuzzy logic in neurofuzzy models provides learning as well as readability. This paper aims at modeling the input-output relationship with fuzzy IF-THEN rules by using fuzzy clustering technique. The main difference between fuzzy cluster...

Fuzzy set theory, originally developed by Lotfi Zadeh in the 1960’s, has become a popular tool for control applications in recent years (Zadeh, 1965). Fuzzy control has been used extensively in applications such as servomotor and process control. One of its main benefits is that it can incorporate a human being’s expert knowledge about how to control a system, without that a person need to have...

Elkan’s paper consists of two almost unrelated parts. In the first section, Elkan arrives at the conclusion that an apparently reasonable version of fuzzy logic collapses mathematically to two-valued logic. In the second section, he questions the value of fuzzy logic in control applications and concludes that fuzzy logic does not provide an effective tool for dealing with the problem of uncerta...

Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...

this research presents a dynamic mathematical system for modeling and simulating the quality management process in construction projects. through sets of cause and effect feedback loops, all factors that internally and externally affect the quality management process are addressed. the proposed system integrates fuzzy logic with system dynamics simulation scheme to consider the uncertainties as...

One of the essential formulas classical mathematical logic is (A → B) ((¬A B). In present paper, its intuitionistic fuzzy interpretation introduced, and lists all defined implications that satisfy it as a tautology an are given.

This paper discusses the issue of how to solve multi-criteria decision making (MCDM) problems by applying fuzzy logic. Multicriteria decision-making problems often involve a complex decision process in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. Fuzzy set theory provides the mathematical technique for the systematic handling of imprecise ...

In a global market, companies must deal with a high rate of changes in business environment. Most manufacturing systems fail to sustain productivity when process disturbances occur. Therefore, it is necessary to create resilient production systems with the ability to return, rapidly, to the initial stage or to an improved one. The parameters, variables and restrictions of the production system ...

It is well known that fuzzy logic can be used in the control of complex systems described by highly nonlinear mathematical models. However, the main difficulty in the design of a fuzzy controller comes with the adjustment of the controller’s parameters that are usually determined by human experts’ knowledge or trial and error methods. In this paper, we describe an implementation of fuzzy logic ...