an artificial neural network has been used to determine the volume flux and rejections of ca2+ , na+ and cl¯, as a function of transmembrane pressure and concentrations of ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. the feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidden la...

in order to determine hydrological behavior and water management of sepidroud river (north of iran-guilan) the present study has focused on stream flow prediction by using artificial neural network. ten years observed inflow data (2000-2009) of sepidroud river were selected; then these data have been forecasted by using neural network. finally, predicted results are compared to the observed dat...

Nowadays, firms apply the merger and acquisition strategy for gaining synergy, increasing the wealth of stockholders, economics of scales, enhancing efficiency, increasing the ability to research and develop, developing the firm and decreasing the risk. Developing an optimized model with the ability to identify the effective variables on the merger and acquisition process has a significant ...

For decades, perception was considered a unique ability of biological systems, little understood in its inner workings, and virtually impossible to match in artificial systems. But this status quo was upturned in recent years, with dramatic improvements in computer models of perception brought about by “deep learning” approaches. What does all the ruckus about a “new dawn of artificial intellig...

Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...

in this paper we propose a method for solving some well-known classes of lane-emden type equations which are nonlinear ordinary differential equations on the semi-innite domain. the proposed approach is based on an unsupervised combined articial neural networks (ucann) method. firstly, the trial solutions of the differential equations are written in the form of feed-forward neural networks co...

In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

Abstract: In this research, at first, the natural frequencies of a cracked beam are obtained analytically, then, location and depth of a crack in beam is identified by neural network method. The research is applied on a beam with an open crack for three different boundary conditions. For this purpose, at first, the natural frequencies of the cracked beam are obtained analytically, to get the ex...

the hybrid fuzzy differential equations have a wide range of applications in science and engineering. we consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. here neural network is considered as a part of large eld called neural computing or soft computing. the proposed algorithm is illustrated by numerical examples and the resu...