In this paper, we propose a novel fuzzy expert system for detection of Coronary Artery Disease, using cuckoo search algorithm. This system includes three phases: firstly, at the stage of fuzzy system design, a decision tree is used to extract if-then rules which provide the crisp rules required for Coronary Artery Disease detection. Secondly, the fuzzy system is formed by setting the intervals ...

This paper presents a layer-structured fuzzy neural network (FNN) for learning rules of fuzzy-logic control systems. Initially, FNN is constructed to contain all the possible fuzzy rules. We propose a two-phase learning procedure for this network. The first phase is a error-backprop (EBP) training, and the second phase is a rule pruning. Since some functions of the nodes in the FNN have the com...

in this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. in this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. to formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision vari...

In the article the possibility of applying one of the methods of data mining – fuzzy association rules to model fuzzy systems is presented. The algorithm of automatic extracting knowledge base is a modification of the Apriori algorithm. The obtained rules of the model contain weights, that are calculated on the basis of measures of fuzzy association rules and constitute probability of fuzzy eve...

In this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. In this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. To formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision vari...

In fuzzy rule-based models acquired from numerical data, redundancy may be present in the form of similar fuzzy sets that represent compatible concepts. This results in an unnecessarily complex and less transparent linguistic description of the system. By using a measure of similarity, a rule base simplification method is proposed that reduces the number of fuzzy sets in the model. Similar fuzz...

The maximization of the performance of the most if not all the fuzzy identification techniques is usually expressed in terms of the generalization performance of the derived neuro-fuzzy construction. Support Vector algorithms are adapted for the identification of a Support Vector Fuzzy Inference (SVFI) system that obtains robust generalization performance. However, these SVFI rules usually lack...

This study seeks to develop a fuzzy expert system to help managers in assessing their effectiveness and position of their business on the manufacturing excellence track. Assessment process is multi-dimensional in nature and there is a relationship between the different variables of the system. In addition, both quantitative and qualitative variables as well as the uncertainty in the statements ...