a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...

in this paper, an algorithm , based on genetics and auxiliary nodes, to reduce energy consumption in wireless sensor networks has been presented. in this research, by considering some parameters as energy and distance, a target function has been created, which is more optimum comparing to other methods. in this research cluster head is selected by genetic algorithm. in rawsn algorithm a new tec...

Optimal multistage expansion of medium-voltage power network because of load growth is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints, make it a combinatorial problem which should be solved by optimization algorithms. In this paper, a new improved hybrid Tabu Search/ Particle Swarm Optimization algorithm is proposed...

We develop methodology for a multistage-decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages. We provide finite sample bounds on the generalization error of the policy learned by the algorithm, and show that when the ...

Abstract To implement energy savings in multistage centrifugal pumps, a return channel is utilized to replace the origin inter-stage flow structure, and then single-objective optimization work containing high-precision numerical simulation, design variable dimensionality reduction, machine learning conducted obtain optimal geometric parameters. The reduction process based on Spearman correlatio...

the jamor purpose of the present research is to predict the total stock market index of tehran stock exchange, using a combined method of wavelet transforms, fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.to do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

In this paper, the transportation problem under the carbon emission trading program ismodelled by mathematical programming and genetic algorithm. Since green supply chain issuesbecome important and new legislations are taken into account, carbon emissions costs are included inthe total costs of the supply chain. The optimisation model has the ability to minimise the total costsand provides the ...