The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many association rules are obtained, the usefulness of them will be reduced. In this paper, we introduce an approach to reduce and summarize the extracted fuzzy association rules after fuzzy data mining. In our approach, in...

In this article, a fuzzy rule based model is developed for the operation of a single purpose reservoir. The model operates on an ‘if – then’ principle, where the ‘if’ is a vector of fuzzy premises and the ‘then’ is a vector of fuzzy consequences. The steps involved in the development of the model include, construction of membership functions for the inflow, storage, demand and the release, form...

In order to overcome weaknesses of the conventional crisp neural network and the fuzzy-operation-oriented neural network, we have developed a general fuzzy-reasoning-oriented fuzzy neural network called a Crisp-Fuzzy Neural Network (CFNN) which is capable of extracting high-level knowledge such as fuzzy IF-THEN rules from either crisp data or fuzzy data. A CFNN can eeectively compress a 5 5 fuz...

The purpose of this paper is to present a genetic learning process for learning fuzzy control rules from examples. It is developed in three stages: the rst one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two kinds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuzzy...

—Clinical practice guidelines are expected to promote more consistent, effective, and efficient medical practices and improve health outcomes, especially if provided in the form of clinical decision support. However, most clinical guidelines, especially when expressed in the form of condition-action recommendations, embody different kinds of structural errors that compromise their practical val...

sustainable development is very important especially in environment. in this paper, the value of sustainable development in environment of iran for iron and steel making in comparison with global, determined by fuzzy logic and expressed by continuous value between zero and one. the following steps were taken in turn: 1- obtaining the related data from internal resources. 2- defining membership ...

this paper develops an automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering angle for the output. in this way some feasible reference trajectory path have been introduced according to geometric and kinematic constraints and nonholonomic constraints to simulate motion path of car. also a novel method is used for parking space detectio...

This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. In a genetic tuning process an evolutionary algorithm adjusts the membership functions or scaling factors of a predefined fuzzy controller based on a performance index that specifies the desired control behavior. Genetic learning processes are concerned with the...

We introduce in this paper a quantitative preference based argumentation system relying on ASPIC argumentation framework and fuzzy set theory. The knowledge base is fuzzified to allow the experts to express their expertise (premises and rules) attached with grades of importance in the unit interval. Arguments are attached with a score aggregating the importance expressed on their premises and r...

Fuzzy rules are usually generated by experts in the area, especially for control problems with only a few inputs. With an increasing number of variables, the number of rules is increasing exponentially, which makes more difficult for experts to define the rule set for good system performance. In solving this, researchers have looked into hybrid the fuzzy based to enhance or reduce complexity. W...