Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

This paper presents the design and the development of an agentbased intelligent hybrid system. The system consists of a network of interacting intelligent agents aiming not only towards real-time air pollution monitoring but towards proposing proper corrective actions as well. In this manner, the concentration of air pollutants is managed in a real-time scale and as the system is informed conti...

The proposed type of hierarchical fuzzy systems is based on the rule base hierarchy. A quite new algorithm for designing a hierarchical fuzzy system from a conventional fuzzy system is developed and implemented. The important part is the unification procedure. Redundant intermediate labels are found and subsequently unified. Basic requirements are fulfilled – subsystems of a hierarchical system...

In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice in many real problems due to the easy understanding of the relationship between the output and input variables. In this paper we present FRULER, a new genetic fuzzy system for automatically learning accurate and simpl...

This paper uses a methodology based in fuzzy sets theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae) the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae). Economic thresholds were already developed for this pest. The aim of this investigation was to develop a simple and specific methodology by fuzzy rule-based system to...

We propose a flexible decision support scheme which could be used in managing the wage negotiation between employers and employees. This scheme uses fuzzy inference systems and game theory concepts in arriving at decisions on future wage increase which could be more mutually agreeable. For example, rather than specifying 5% yearly increase of wages, we propose that the uncertain factors which a...

This paper proposes a rule base simplification method for fuzzy systems. The method is based on aggregation of rules with different linguistic values of the output for identical permutations of linguistic values of the inputs which are known as inconsistent rules. The simplification removes the redundancy in the fuzzy rule base by replacing each group of inconsistent rules with a single equival...

In our previous work we showed that genetic algorithms (GAs) provide a powerful tool to increase the accuracy of fuzzy models for both systems modeling and classification. In addition to these results, we explore the GA to find redundancy in the fuzzy model for the purpose of model reduction. An aggregated similarity measure is applied to search for redundancy in the rule base description. As a...

A hybrid method combining an evolutionary search strategy, interval mathematics and pole assignment-based closed-loop control synthesis is proposed to design a robust TSK fuzzy controller. The design objective is to minimize the number of linear controllers associated with rule conclusions and tune the triangular-shaped membership function parameters of a fuzzy controller to satisfy stability a...