Radial Basis function Neural Networks forms a class of neural networks which is much more advantageous then other methods of neural networks such as faster learning, easy networks & structures & better approximations & classifications. The system consist of a multilayer perceptron (MLP)-like network that performs image segmentation by RBF technique of the input image using labels automatically ...

-Fuzzy theory is integrated with Artificial Neural Network to create a bridge safety assessment model, through which the Fuzzy-Neural Network is improved in the light of sample data simulation. First, determine network layers interms of the seven critiria for bridge safety assessment. Then enter sample data at the input layer; study sample at the fuzzy reasoning layer by BP calculation method; ...

Large-scale and complex mechanical equipments usually operate under complicated and terrible conditions, making them inevitable for faults with various modes and severity. As they can incur substantial production loss and recovery cost. It is therefore, extremely essential to prognose an incipient fault before it leads to serious damage. However, faults of large scale and complex mechanical equ...

This paper discusses the design of neural network and fuzzy logic controllers using genetic algorithms, for real-time control of flows in sewerage networks. The soft controllers operate in a critical control range, with a simple set-point strategy governing "easy" cases. The genetic algorithm designs controllers and set-points by repeated application of a simulator. A comparison between neural ...

In this paper, we propose two approach intelligent techniques of improvement of Direct Torque Control (DTC) of Induction motor such as fuzzy logic (FL) and artificial neural network (ANN), applied in switching select voltage vector .The comparison with conventional direct torque control (DTC), show that the use of the DTC_FL and DTC_ANN, reduced the torque, stator flux, and current ripples. The...

New approaches like neural networks and fuzzy sets have been used more and more in pattern recognition during recent years. In this article, neural network and fuzzy clustering algorithms are compared to the traditional clustering algorithm.

This paper presents a fuzzy perceptron as a generic model of multilayer fuzzy neural networks, or neural fuzzy systems, respectively. This model is suggested to ease the comparision of diierent neuro{fuzzy approaches that are known from the literature. A fuzzy perceptron is not a fuzziication of a common neural network architecture, and it is not our intention to enhance neural learning algorit...

In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and app...