This paper proposes the neural network solution to the indirect vector control of three phase induction motor including an adaptive neuro fuzzy controller. The basic equations and elements of the indirect vector control scheme are given. The proposed control scheme is realized by an adaptive neuro-fuzzy controller and two feed forward neural network. The neuro-fuzzy controller incorporates fuzz...

The “fuzzy dot” (or fuzzy relation) representation of fuzzy rules in fuzzy rule based systems, in case of classical fuzzy reasoning methods (e.g. the Zadeh-MamdaniLarsen Compositional Rule of Inference (CRI) (Zadeh, 1973) (Mamdani, 1975) (Larsen, 1980) or the Takagi Sugeno fuzzy inference (Sugeno, 1985) (Takagi & Sugeno, 1985)), are assuming the completeness of the fuzzy rule base. If there are...

Employability is potential of a person for gaining and maintains employment. Employability is measure through the education, personal development and understanding power. Employability is not the similar as ahead a graduate job, moderately it implies something almost the capacity of the graduate to function in an employment and be capable to move between jobs, therefore remaining employable thr...

slope stability analysis is an enduring research topic in the engineering and academic sectors. accurate prediction of the factor of safety (fos) of slopes, their stability, and their performance is not an easy task. in this work, the adaptive neuro-fuzzy inference system (anfis) was utilized to build an estimation model for the prediction of fos. three anfis models were implemented including g...

grid computing is a term referring to the combination of computer resources from multiple administrative domains to reach a common computational platform. mobile computing is a generic word that introduces using of movable, handheld devices with wireless communication, for processing data. mobile computing focused on providing access to data, information, services and communications anywhere an...

The aim of this paper is to propose a criterion to estimate the design, from experimental data, of a fuzzy inference system, when data are sparse. This lack of data is important and may improve the generalisation ability of fuzzy systems (0). Several methods have been proposed to obtain automatic fuzzy rules from sparse training data. In (0), the authors first construct fuzzy rules from collect...

This paper proposs a systematic methodology of fuzzy logic modeling as a generic tool for modeling of complex systems. The methodology conveys three distinct features: 1) a unified parameterized reasoning formulation; 2) an improved fuzzy clustering algorithm; and 3) an efficient strategy of selecting significant system inputs and their membership functions. The reasoning mechanism introduces f...

Many studies on modeling of fuzzy inference systems have been made. The issue of these studies is to construct automatically fuzzy systems with interpretability and accuracy from learning data based on meta-heuristic methods. Since accuracy and interpretability are contradicting issues, there are some disadvantages for self-tuning method. Obvious drawbacks of the method are lack of interpretabi...

this paper describes the development of a fuzzy decision support system (fdss) for the assessment of risk in e-commerce (ec) development. a web-based prototype fdss is suggested to assist ec project managers in identifying potential ec risk factors and the corresponding project risks. a risk analysis model for ec development using a fuzzy set approach is proposed and incorporated into the fdss....