An efficient methodology is proposed to find optimal shape of arch dams on the basis of constrained natural frequencies. The optimization is carried out by virtual sub population (VSP) evolutionary algorithm employing real values of design variables. In order to reduce the computational cost of the optimization process, the arch dam natural frequencies are predicted by properly trained back pro...

A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (SVR) in particular, have been shown to outperform many traditional color constancy algorithms. However, neither neural networks nor SVR were compared to simpler regression tools in those studies. In this article, we pr...

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...

this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays.  an optimization procedure for a neural mpc algorithm based on this model is then developed. the p...

This paper describes an application of Artificial Neural Networks (ANN) to Load Frequency Control (LFC) of nonlinear power systems. Power systems, such as other industrial processes, have parametric uncertainties that for controller design had to take the uncertainties in to account. For this reason, in the design of LFC controller the idea of robust control theories are being used. To improve ...

The current paper presents a robust optimum design of friction stir welding (FSW) lap joint AA1100 aluminum alloy sheets using Monte Carlo simulation, NSGA-II and neural network. First, to find the relation between the inputs and outputs a perceptron neural network model was obtained. In this way, results of thirty friction stir welding tests are used for training and testing the neural network...

the network design problem (ndp) is one of the important problems in combinatorial optimization. among the network design problems, the multicommodity capacitated network design (mcnd) problem has numerous applications in transportation, logistics, telecommunication, and production systems. the mcnd problems with splittable flow variables are np-hard, which means they require exponential time t...