The paper is continuing a work for a velocity controller synthesis by neuro-fuzzy techniques in a vector control with an asynchronous motor structure. The input – output data prepared in the previous paper are applied to a program in order to train a neural network able to generate a file for the speed fuzzy controller. The fuzzy solution is analyzed comparatively with the standard structure th...

The necessity to use various tools – instructional media and technology for effective teaching using combined overlap block fuzzy cognitive maps (COBFCMS) defined by W.B. Vasantha Kandaswamy is analyzed in this paper. The combined overlap block FCM’s defined in this method become effective when the number of concepts can be grouped and are large in numbrs. In this paper we have analyzed the var...

Soft computing is a part of an artificial intelligence, and fuzzy logic is the study of fuzziness on data. The combination of these two techniques can provide an intelligent system with more ability and flexibility. The nature of data in the stock/capital market is more complex and challenging to predict the movement of the price of the stock. The study has combined both fuzzy c-means and neura...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

Fuzzy quasi-interpolations help to reduce the complexity of solving a linear system of equations compared with fuzzy interpolations. Almost all fuzzy quasi-interpolations are focused on the form of $widetilde{f}^{*}:mathbb{R}rightarrow F(mathbb{R})$ or $widetilde{f}^{*}:F(mathbb{R})rightarrow mathbb{R}$.  In this paper, we intend to offer a novel fuzzy radial basis function by the concept of so...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

This report presents a fuzzy multi-sensor data fusion process for combining heading estimates from three separate Kalman filters with the aim of constructing a fault tolerant navigation system for the Springer Uninhabited Surface Vehicle (USV). A single gyroscopic unit and three independent compasses are used to acquire data onboard the vessel. The inertial data from the gyroscope is combined i...

Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decompo...