Recently the number of distance education platforms has been increased significantly. These platforms provide isolation between the student and teacher. Thus, there is a need for predicting the students who are possible to fail in a specific course and take the precautions like starting face-to-face on demand lectures for individual cases. Both of artificial intelligence and data mining techniq...

This paper proposes the application of Genetic Learning as a procedure for the optimal design and training of neuro-fuzzy systems. Once this learning procedure has been implemented, hybridization between Genetic Algorithms (GA) and the traditional local search technique is carried out to form a Hybrid Algorithm, in order to achieve the maximum possible efficiency in the search, and to be able t...

This paper describes a neuro-fuzzy modeling framework for predicting the properties of ashes originated from combustion processes for electric generation. The prediction problem is tackled by means of a neuro-fuzzy system in which a neural network and a fuzzy system are combined in a fused architecture, so that the structure and the parameters of the fuzzy rule base are determined via a two-pha...

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In this paper, we propose the use of a neuro-fuzzy strategy to develop a Web personalization framework for the dynamic suggestion of URLs retained interesting for the currently connected users. In particular, a hybrid strategy exploiting the combination of the fuzzy logic with the neural paradigm is proposed in order to discover useful knowledge from session data identified from the analysis of...

This paper addresses the problem of emotion recognition in faces through an intelligent neuro-fuzzy system, which is capable of analysing facial features extracted following the MPEG-4 standard and classifying facial images according to the underlying emotional states, following rules derived from expression profiles. Results are presented which illustrate the capability of the developed system...

Fuzzy Logic, introduced by Zadeh along with his introduction of fuzzy sets, is a continuous multi-valued logic system. Hence, it is a generalization of the classical logic and the classical discrete multi-valued logic (e.g. Łukasiewicz’ three/many-valued logic). Throughout the years Zadeh and other researches have introduced extensions to the theory of fuzzy setts and fuzzy logic. Notable exten...

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results sho...

A neuro fuzzy control algorithm for planar robotic manipulators is developed in this paper. This control algorithm is able to handle uncertainties, disturbances or unmodeled dynamics. Asymptotic stability of the equilibrium state of the control system is shown by use of direct Lyapunov method and Barbalat’s Lemma. A series of simulations confirms the algorithm goodness. Key-Words: fuzzy control...