To use fuzzy controllers for automization tasks appropriate fuzzy sets and fuzzy rules have to be deened. This can be diicult in some domains, and the resulting controller has to be tuned. Neuro{fuzzy models can help in this tuning process by adapting fuzzy sets and creating fuzzy rules. Combinations of neural networks and fuzzy controllers are suitable if there is only partial knowledge in the...

Fuzzy rules optimization is a crucial step in the development of a fuzzy model. A simple two inputs fuzzy model will have more than ten thousand possible combinations of fuzzy rules. A fuzzy designer normally uses intuition and trial and error method for the rules assignment. This paper is devoted to the development and implementation of genetic optimization library (GOL) to obtain the optimum ...

The integration of association rules and correlation rules with fuzzy logic can produce more abstract and flexible patterns for many real life problems, since many quantitative features in real world, especially surveying the frequency of plant association in any region is fuzzy in nature. This paper presents a modification of a previously reported algorithm for mining fuzzy association and cor...

The monitoring and control of Road traffic is becoming a major problem in many countries. With the ever increasing number of vehicles on the road, the Monitoring authorities have to find new ways or measures of overcoming such a problem. In this paper we discuss the implementation of an intelligent traffic control system using fuzzy logic technology which has the capability of mimicking human i...

In this contribution, an implicative variant of the conjunctive normal form will be recalled and further studied. This normal form is an alternative to the Perfilieva’s conjunctive normal form. It will be shown that it is a suitable model for a particular case of graded fuzzy rules introduced as a generalization of classical fuzzy rules. Moreover, approximation properties of the implicative var...

In this document we carry out a comparative analysis of the application of Fuzzy Logic Controllers (hereinafter FLCs), Fuzzy Temporal Rules-Based Controllers (hereinafter FTRCs), Temporal Fuzzy Logic Controllers (hereinafter TFLCs) and Faded Temporal fuzzy Logic Controllers (hereinafter FTFLCs), to improve the adaptive distributed routing. To obtain a good knowledge base the controllers were ev...

in this project guidance and control of underwater robot, including three engines and propeller attached to it, by fuzzy control has been investigated. fuzzy control is done based on human experience and requiered laws. the robot can also be controlled and guided by the user. this robot may be used in sea or swimming pool environment for finding goal point and locate in desired direction. in ad...

In this study, we propose the method creating fuzzy control rules based on experiential knowledge. With the advent of data mining techniques, a new way is provided to create fuzzy control rules. With the introduction of incremental data mining techniques, fuzzy control rules can be updated dynamically in time on the condition that massive new data is producing.

Most fuzzy systems including fuzzy decision support and fuzzy control systems provide out­ puts in the form of fuzzy sets that represent the inferred conclusions. Linguistic interpretation of such outputs often involves the use of linguistic approximation that assigns a linguistic label to a fuzzy set based on the predefined primary terms, linguistic modifiers and linguistic connectives. More g...

In this paper, we study fuzzy calculus in two main branches differential and integral.  Some rules for finding limit and $gH$-derivative of $gH$-difference, constant multiple of two fuzzy-valued functions are obtained and we also present fuzzy chain rule for calculating  $gH$-derivative of a composite function.  Two techniques namely,  Leibniz's rule and integration by parts are introduced for ...