the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...

Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...

‎linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎in this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎by a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎then‎, ‎we use...

This document deals with a design of a physical and a logical topology of communication networks that are applied in the control engineering. The design of the physical topology works with aspects of demands for redundant links between nodes. Thanks to knowledge of the physical topology, we can design the logical topology according to permitted delays of delivered communication frames. The whol...

the spatial distribution of petrophysical properties within the reservoirs is one of the most importantfactors in reservoir characterization. flow units are the continuous body over a specific reservoirvolume within which the geological and petrophysical properties are the same. accordingly, anaccurate prediction of flow units is a major task to achieve a reliable petrophysical description of a...

in static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. in this paper, the static scheduling problem of automated guided vehicles in container terminal is solved by the network simplex algorithm (nsa). the algorithm is based on graph model and their performances are at least 100 times faster than traditional si...

Transmission network expansion planning (TNEP) is an important component of power system planning. Itdetermines the characteristics and performance of the future electric power network and influences the powersystem operation directly. Different methods have been proposed for the solution of the static transmissionnetwork expansion planning (STNEP) problem till now. But in all of them, STNEP pr...