Due to lack of theory of elasticity, estimation of ultimate torsional strength of reinforcement concrete beams is a difficult task. Therefore, the finite element methods could be applied for determination of strength of concrete beams. Furthermore, for complicated, highly nonlinear and ambiguous status, artificial neural networks are appropriate tools for prediction of behavior of such states. ...

Wear monitoring systems often use neural networks for a sensor fusion with multiple input patterns. Systems for a continuous online supervision of wear have to process pattern sequences. Therefore recurrent neural networks have been investigated in the past. However, in most cases where only noisy input or even noisy output patterns are available for a supervised learning, success is not forthc...

This paper describes construction of multilayer perceptron by open source neural networks simulator Neuroph and Petri net. The described multilayer perceptron solves logical function "xor "exclusive or. The aim is to explore the possibilities of description of the neural networks by Petri Nets. The selected neural network (multilayer perceptron) allows to be seen clearly the advantages and disa...

Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosag...

A novel speech separation structure which simulates the cocktail party e ect using a modi ed iterative Wiener lter and a multi-layer perceptron neural network is presented. The neural network is used as a speaker recognition system to control the iterative Wiener lter. The neural network is a modi ed perceptron with a hidden layer using feature data extracted from LPC cepstral analysis. The pro...

This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classification accuracy of myoelectric signals using multi-layer perceptron with back-propagation algorithm, and the new fuzzy clustering neural network (FCNN) is presented. The myoelectri...