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...

microgrids are small-scale, low voltage (lv) power networks which employ renewable distribution energy resources (ders) with power electronic interfaces (peis). microgrids as single controlled units and active distribution networks require flexible control systems to ensure reliable and secure operation in different modes. these various operations of microgrid cause variations in voltage and fr...

imperialist competitive algorithm (ica) is a new socio-politically motivated global search strategy. the ica is applied to hybrid composite laminates to obtain minimum weight and cost. the approach which is chosen for conducting the multi-objective optimization was the weighted sum method (wsm). the hybrid composite laminates are made of glass/epoxy and carbon/epoxy to combine the lightness and...

optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

in this paper, optimal design of hybrid solar-wind- diesel energy system with battery storage for reliable load in arsoon village in ardabil is presented. the village has 35 households that mean daily energy consumption is estimated 63.4 kwh. in this design optimization is implemented, considering loss of power supply probability (lpsp) index for reliable load providing, with minimum total cons...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...