Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate courses. The model uses clustering to identify students with similar interests and skills...

In this paper, the so-called Wang–Mendel (WM) method for generating fuzzy rules from data is enhanced to make it a comprehensive and flexible fuzzy system approach to data description and prediction. In the description part, the core ideas of the WM method are used to develop three methods to extract fuzzy IF–THEN rules from data. The first method shows how to extract rules for the user-specife...

The aim of the paper is to demonstrate the neuro-fuzzy support of knowledge management in social regulation. Knowledge, defined as human capability of making data and information useful for decision making processes, could be understood for social regulation purposes as explicit and tacit. Explicit knowledge relates to the community culture indicating how things work in the community based on s...

A neural fuzzy system learning with linguistic teaching signals is proposed in this paper. This system is able to process and learn numerical information as well as linguistic information. It can be used either as an adaptive fuzzy expert system or as an adaptive fuzzy controller. At first, we propose a fivelayered neural network for the connectionist realization of a fuzzy inference system. Th...

Fuzzy logic has proven to be a promising method for developing simple, robust controllers for uncertain or nonlinear systems. One problem with fuzzy controllers, however, is that they are difficult to apply to higher-order systems. The reason for this is that the number of rules required for the rule base increases geometrically with the number of states. For example, if a system was fourth-ord...

This paper investigates the implementation and design of a fuzzy system on an industrial controller. Programmable Logic Controllers (PLCs) are key devices used in many industrial processes. Most of the time they implement discrete control functions involving sequential control, but the availability of basic features like arithmetic operations, floating point units etc. allow for more complex al...

This paper is focused on the evolution of the theory of fuzzy IF-THEN rules and its contribution to the establishment of fuzzy logic. I advocate that Hájek’s fuzzy logic is a right methodology for development of special logical theories. A theory of fuzzy IF-THEN rules (as a special theory in this sense) is proposed. This theory is for all practitioners who want to create a system of fuzzy IF-T...

This paper proposes a fuzzy classifier system (FCS) using fuzzy rules given by hyper-cone membership functions. The hyper-cone membership function is expressed by a kind of radial basis function, and its fuzzy rules can be flexibly located in input and output spaces. Therefore, The FCS can generate excellent rules which have the best location and shape of membership functions. We apply the FCS ...

A fuzzy neural network, Falcon-MART, is proposed in this paper. This is a modi®cation of the original Falcon-ART architecture. Both Falcon-ART and Falcon-MART are fuzzy neural networks that can be used as fuzzy controllers or applied to areas such as forgery detection, pattern recognition and data analysis. They constitute a group of hybrid systems that incorporate fuzzy logic into neural netwo...

Existing neural fuzzy (neuro-fuzzy) networks proposed in the literature can be broadly classified into two groups. The first group is essentially fuzzy systems with self-tuning capabilities and requires an initial rule base to be specified prior to training. The second group of neural fuzzy networks, on the other hand, is able to automatically formulate the fuzzy rules from the numerical traini...