Diagnosis is a very important aspect of medical care. Expert systems are developed to make the skills of specialists available for non-specialists. These systems simulate human thinking and performance and approach the performance of expert systems to the performance of a human expert. The purpose of this study is to develop a fuzzy expert system for diagnosis and treatment of musculoskeletal d...

Fuzzy rule systems are an important element in the arsenal of automated control, as they are able to process the input provided by sensors and provide their output in very small times. Lately, there has been augmented interest in utilizing fuzzy rule systems in a wider range of applications, due to the intuitive way in which they represent and utilize knowledge. In these contexts, input is not ...

Researchers at the Mississippi State University Diagnostic and Instrumentation Laboratory (DIAL) are collaborating with scientists at the Idaho National Engineering Laboratory (INEL) to develop an expert system that analyzes and characterizes containerized radiological waste. The DIAL researchers are making use of various artificial intelligence (AI) techniques to develop different versions of ...

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...

In most Fuzzy System applications the structure of the system is chosen non-systematically by an expert according to his knowledge. Nevertheless the system parameters are rich enough to ensure the desired behavior. In the following, we introduce an automatic learning algorithm by de nition of a 1) well behaved and 2) minimal Fuzzy System. A Genetic Algorithm is used to estimate the Fuzzy System...

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...