In this paper we present a new class of neuro-fuzzy systems designed for system modelling and pattern classification. Our approach is characterized by automatic determination of fuzzy inference in the process of learning. Moreover, we introduce several flexibility concepts in the design of neuro-fuzzy systems. The method presented in the paper is characterized by high accuracy which outperforms...

This paper focuses on hardware implementations of fuzzy inference systems which provide low silicon cost, high operational speed and adaptability to different application domains. The architecture and basic building blocks of two fuzzy logic controllers are described and their functionality is illustrated with experimental results showing the capability of these systems to be applied as functio...

The aim of the paper is to demonstrate the neuro-fuzzy support of knowledge management in social regulation. Knowledge, defined as human capability of making data and information useful for decision making processes, could be understood for social regulation purposes as explicit and tacit. Explicit knowledge relates to the community culture indicating how things work in the community based on s...

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Trans...

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Trans...

In this chapter a new method of hierarchical genetic algorithm for fuzzy inference systems optimization is proposed. This method was used in two applications, the first was to perform the combination of responses of modular neural networks for human recognition based on face, iris, ear and voice, and the second one for fuzzy control of temperature in the shower benchmark problem. The results ob...

This study describes a distributed attack detection approach for a tactical MANET using intelligent agents equipped with inference systems based on fuzzy logic. The results produce a prototype intrusion detection system capable of effectively detecting attacks in a tactical MANET with accuracy approaching 95%. The attack recognition system is implemented using stationary intelligent fuzzy agent...

Competition is the driving force of today's economy and it is vital for organizations to gain competitive advantages. In recent years, outsourcing has been the focus of managers as a tool for developing organizations and improving productivity. This study deals to analyze the outsourcing risks of the supply chain in the automotive industry using fuzzy inference systems. For this purpose, in the...

Fuzzy Logic has found popularity in the academic community and widespread use in the industry due to ever increasing complexities in systems, at the core of which lies vagueness, uncertainty and imprecision in information. The proposition of fuzzy set theory, specifically Fuzzy Inference Systems (FIS) led to an explosion of its application in diverse fields including manufacturing especially ma...

System modelling based on conventional mathematical tools like differential equations is not well suited for dealing with ill-defined and uncertain systems. By contrast, a fuzzy inference system, employing fuzzy if–then rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. This fuzzy modeling or fuzzy identification e...