Due to its high performance and comprehensibility, fuzzy modelling is becoming more and more popular in dealing with nonlinear, uncertain and complex systems for tasks such as signal processing, medical diagnosis and financial investment. However, there are no principal routine methods to obtain the optimum fuzzy rule base which is not only compact but also retains high prediction (or classific...

Association rules shows us interesting associations among data items. It means that an association rule clearly defines that how a data item is related or associated with another data item. That is why these types of rules are called Association rules. And the procedure by which these rules are extracted and managed is known as Association rule mining. Classical association rule mining had many...

This paper is concerned with scheduling robotic flexible assembly cells (RFACs) using fuzzy logic (FL) technique. A new scheduling rule is developed and evaluated called fuzzy sequencing rule (FSR). A simulation program is used to examine the performance of the existing scheduling rules and the proposed rule with respect to multiple performance measures. Four performance measures considered sim...

OBJECTIVE To test the effects of media violence exposure on blood pressure, negative affect, hostile social information processing, uncooperative behavior, and attitudes toward health risk behaviors among young men varying in lifetime violence exposure within the home and community. DESIGN Experimental laboratory study. SETTING University campus situated within an urban environment. PARTI...

In the 3eld of fuzzy modelling, the exclusive consideration of the modelling error leads to problems concerning the handling of high-dimensional applications and the interpretability of the resulting rule base. To solve those problems, a statistically motivated fuzzy rule test is proposed. It decides if a fuzzy IF=THEN statement is a relevant rule or not. In this way, the problem of 3nding a go...

The ‘hnique selling point” of fuzzy systems is usually the interpretability of its rule base. However, very often only the U C C U T U C ~ of the rule base is measured and used to compare a fuzzy system to other solutions. We have suggested an index to measurz the interpretability of fuzzy rule bases for classification problems. However, the index can be used to describe the interpretability of...

Fuzzy inference process usually involves the use of fuzzy rule base consisting in several fuzzy rules. Overall output can be obtained by aggregation of outputs of all rules. To obtain an output of individual rule the relevancy of this rule is calculated. Then the individual output is obtained from the relevancy and the consequent of the rule. Such process can be realised using an operator that ...

Data mining is the analysis step of the "Knowledge Discovery in Databases" process, or KDD. It is the process that results in the discovery of new patterns in large data sets. It utilizes methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract knowledge from an existing data set and tra...

Pascual Juli an a Gin es Moreno b Jaime Penabad c aDepartment of Computer Science ESI, Univ. of Castilla{La Mancha Paseo de la Universidad, 4; 13071 Ciudad Real, Spain bDepartment of Computer Science cDepartment of Mathematics EPSA, Univ. of Castilla{La Mancha Campus Universitario, s/n; 02071 Albacete, Spain Abstract In the context of (fuzzy) logic programs, `unfolding' means to transform a pro...