in this paper, a connecting rod was modeled and analyzed by finite element method. byusing genetic algorithm (ga) and modified cuckoo optimization algorithm (mcoa), the materialproperties and some geometrical specifications were optimized. cost function was a combination ofweight and stress. the connecting rod was under a load of 21.8 kn which obtained 360o crank angleat 5700 rev/min. the reduc...

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...

background: rna molecules play many important regulatory, catalytic and structuralroles in the cell, and rna secondary structure prediction with pseudoknots is one themost important problems in biology. an rna pseudoknot is an element of the rna secondary structure in which bases of a single-stranded loop pair with complementary basesoutside the loop. modeling these nested structures (pseudokno...

this paper focuses upon the development of an efficient method for conceptual design optimization of a satellite. there are many option for a satellite subsystems that could be choice, as acceptable solution to implement of a space system mission. every option should be assessment based on the different criteria such as cost, mass, reliability and technology contraint (complexity). in this rese...

In this paper, a new approach is proposed for the optimum design of single-phase induction motor. By using the classical design equations and the evolutionary algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Modified Particle Swarm Optimization (MPSO), a Single Phase Induction Motor (SPIM) was designed with the maximum efficiency. The Finite Element Method (FEM)...

In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced‎. ‎In this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony s...

coverage improvement is one of the main problems in wireless sensor networks. given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. for achieving good coverage, the sensors should be placed in adequate places. this paper uses the genetic and learning automata as intelligent methods for...

wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. routing attacks on the networks, where a malicious node from sending data to the base station is perceived. in this article, a method that can be used to transfer the data securely to prevent attacks...