crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. in the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. then, the obtained results are validated usingthe results of experimental modal analysis tests. in the next part, a nove...

Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...

Recently, the scheduling problem in distributed data-intensive computing environments has been an active research topic. This Chapter models the scheduling problem for work-flow applications in distributed dataintensive computing environments (FDSP) and makes an attempt to formulate the problem. Several meta-heuristics inspired from particle swarm optimization algorithm are proposed to formulat...

Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization...

According to researches, activation was a minor strategy of improving Particle Swarm Algorithm. For proofing the possibility of activation strategy could be a main strategy for improving Particle Swarm Algorithm, this article adopt the concept of mutation in Genetic Algorithm to improve Particle Swarm Optimization. The experimental results show three advantages for the activation strategies. Fi...

The particle swarm algorithm contains elements which map fairly strongly to the foraging problem in behavioural ecology. In this paper, we show how some simple adaptions to the standard algorithm can make it well suited for the foraging problem. We propose two approaches to model foraging behaviour: the first uses a standard particle swarm algorithm, with the particles just slowing down in the ...

The problem of development of the SVM classifier based on the modified particle swarm optimization has been considered. This algorithm carries out the simultaneous search of the kernel function type, values of the kernel function parameters and value of the regularization parameter for the SVM classifier. Such SVM classifier provides the high quality of data classification. The idea of particle...

This paper proposes the use of a particle filter with embedded particle swarm optimization as an efficient and effective way of dealing with 3d model-based human body tracking. A particle swarm optimization algorithm is utilized in the particle filter to shift the particles toward more promising configurations of the human model. The algorithm is shown to be able of tracking full articulated bo...

In this paper we present and discuss the results of experimentally comparing the performance of several variants of the standard swarm particle optimiser and a new approach to swarm based optimisation. The new algorithm, which we call predator prey optimiser, combines the ideas of particle swarm optimisation with a predator prey inspired strategy, which is used to maintain diversity in the swar...