In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

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 ...

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...