In this paper a new technique for eliciting a fuzzy inference system (FIS) from data for nonlinear systems is proposed. The strategy is conducted in two phases: in the first one, subtractive clustering is applied to extract a set of fuzzy rules, in the second phase, the generated fuzzy rule base is refined and redundant rules are removed on the basis of an interpretability measure. Finally, cen...

An adaptive Fuzzy Inference Perceptual model has been proposed for watermarking of digital images. The model depends on the human visual characteristics of image sub-regions in the frequency multi-resolution wavelet domain. In the proposed model, a multi-variable fuzzy based architecture has been designed to produce a perceptual membership degree for both candidate embedding sub-regions and str...

Sensor failure detection and identification has been considered as an important issue, particularly when the measurements from sensors are used in the feedback loop of a control law. Kalman filters and Luenberger observers have been widely used to generate signal redundancy by means of state estimation. Dedicated observer scheme and generalized observer scheme are the older methods available fo...

Hybrid fuzzy expert systems are one of the most practical intelligent paradigm of soft computing techniques with the high potential for managing uncertainty associated to the medical diagnosis. The potential of genetic algorithm (GA) by inspiring from natural evolution as a learning and optimization technique has been vastly concentrated for improving fuzzy expert systems. In this paper, the GA...

A great deal of interest has been shown in the literature in the development of new Non-Destructive Techniques (NDT). In particular, there is increasing interest in detecting, evaluating and locating cracks as well as the source of the impact causing these cracks. Fuzzy logic was shown to be useful in crack detection, and severity of crack in materials. In this paper Fuzzy logic has been used i...

A methodology for the development of a fuzzy expert system (FES) with application to earthquake prediction is presented. The idea is to reproduce the performance of a human expert in earthquake prediction. To do this, at the first step, rules provided by the human expert are used to generate a fuzzy rule base. These rules are then fed into an inference engine to produce a fuzzy inference system...

Emotion recognition plays an effective and important role in Human–Computer Interaction (HCI). Recently, various approaches to emotion recognition have been proposed in the literature, but they do not provide a powerful approach to recognize emotions from Partially Occluded Facial Images. In this paper, we propose a new method for Emotion Recognition from Facial Expression using Fuzzy Inference...

Unmanned Aerial Vehicle (UAV) is inherently an unstable system and this necessitated the need of an external controller to stabilize and to control it. In this paper presents the exploration into the simulation, design and analysis of two autopilot schemes: (1) a fuzzy-PID controller and, (2) hybrid PID-Fuzzy controller for controlling pitch plane dynamics of an aircraft. The modeled fuzzy logi...

This work presents an approximation to the modeling and identification tasks using Fuzzy Inference Systems (FIS) applied to the Benchmark Problem: pH neutralization control in industrial processes. The statement of this problem is taken from a paper that postulates the waste water pH neutralization process as a benchmark approach. The proposed model uses the Takagi-Sugeno FIS type, aiming at fu...