The spatial distribution of petrophysical properties within the reservoirs is one of the most important factors in reservoir characterization. Flow units are the continuous body over a specific reservoir volume within which the geological and petrophysical properties are the same. Accordingly, an accurate prediction of flow units is a major task to achieve a reliable petrophysical description o...

This paper describes a usual application of back-propagation neural networks for synthesis and optimization of antenna array. The neural network is able to model and to optimize the antennas arrays, by acting on radioelectric or geometric parameters and by taking into account predetermined general criteria. The neural network allows not only establishing important analytical equations for the o...

semiarid regions with their exceptional weather conditions, low precipitation, and high evapotranspiration pose a great challenge to water resources managers. one possible way to face this challenge is the conjunctive use of both surface water and groundwater resources in these regions. this paper proposes a conjunctive use model which has been implemented in najafabad plain in central iran. th...

the main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. the optimization is carried out by charged system search algorithm and its enhanced version. computing the natural frequencies by finite element analysis (fea) during the optimization process is time consuming. in order to reduce the computa...

quantitative prediction of municipal solid waste generation has an important role in the optimization and programming of municipal solid waste management system. but, this concept was companied with many problems, because of the non homogenous nature and the effect of various factors out of the control on solid waste generation. in this study, the combination of artificial neural network and wa...

In this paper, artificial neural networks for solving multiobjective optimization problems have been considered. The Tank-Hopfield model for linear programming has been extended, and then the neural model for finding Pareto-optimal solutions in the linear multi-criterion optimization problem with continuous decision variables has been discussed. Furthermore, the model for solving quasi-quadrati...

because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...

handwritten digit recognition can be categorized as a classification problem. probabilistic neural network (pnn) is one of the most effective and useful classifiers, which works based on bayesian rule. in this paper, in order to recognize persian (farsi) handwritten digit recognition, a combination of intelligent clustering method and pnn has been utilized. hoda database, which includes 80000 p...