A communication procedure for communicating scheduling expert systems based on fuzzy set theory is proposed. Fuzzy sets are used to express and to exchange constraints and their possible relaxations with other scheduling systems that can interpret these constraints. The procedure is intended to optimize the global evaluation among the communicating systems. An example from steel industry is tak...

Due to high nonlinearities and time-varying dynamics of today’s control systems fuzzy learning controllers find appliance in practice. The present paper proposes a method for the synthesis of the learning fuzzy controllers where an expert knowledge about a process is applied to form a learning mechanism that is used to acquire information for the knowledge base of the main fuzzy controller. Acc...

In this paper, we present the design, implementation and evaluation of FESMI, a fuzzy expert system that deals with diagnosis and treatment of male impotence. The diagnosis process, linguistic variables and their values were modeled based on expert’s knowledge the statistical analysis of the records of 70 patients from a hospital database and existing literature. The expert system has been impl...

The last stage of any type of automatic surveillance system is the interpretation of the acquired information from its sensors. This work focuses on the interpretation of motion pictures taken from a surveillance camera, i.e.; image understanding. A prototype of a fuzzy expert system is presented which can describe in a natural language like manner, simple human activity in the field of view of...

Both crisp and fuzzy rule-based expert systems are increasingly used in the real-time environments. For both types of systems the stability and nite response time are required. It is therefore crucial for both to provide tools that perform stability analysis. This paper shows how the analysis tools built for crisp real-time rule-based system might be used for fuzzy systems as well. Major diiere...

Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy control, decision support and expert systems. Since the advent of fuzzy sets a great number of fuzzy connectives, aggregation operators have been introduced. Som...

This paper presents two new intelligent systems for power quality assessment applications. One is for automated power quality disturbance detection and classification, and the other is for power system model validation. Seeking improved performance over existing approaches for power quality disturbance detection and classification, a novel fuzzy-expert system utilizing fuzzy logic and expert sy...

In the paper basic defuzzification techniques are considered. The defuzzification process is present at a fuzzy system when an output fuzzy set should be mapped to a crisped value. Features are given which are the base for a defuzzification techniques comparison. Techniques are classified into several groups. The overview of defuzzification techniques is given, as well as their comparison on th...

This paper summarizes some results of the authors’ research that have been carried out in recent years on generalization of conventional aggregation operators. Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy c...

This paper presents the development of a hybrid neural network to model a fuzzy expert system for time series forecasting of electricc load. The hybrid neural network is trained to develop fuzzy logic rules andjind optimal inputloutput membership values of load and weather parameters. A hybrid learning algorithm consisting of unsupervised and supervised learning phases is used for training the ...