Optimal sensor distribution in explosion testing is important in saving test costs and improving experiment efficiency. Aiming at travel time tomography in an explosion, an optimizing method in sensor distribution is proposed to improve the inversion stability. The influence factors of inversion stability are analyzed and the evaluating function on optimizing sensor distribution is proposed. Th...

Meta-heuristic algorithms inspired by the natural processes are part of the optimization algorithms that they have been considered in recent years, such as genetic algorithm, particle swarm optimization, ant colony optimization, Firefly algorithm. Recently, a new kind of evolutionary algorithm has been proposed that it is inspired by the human sociopolitical evolution process. This new algorith...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

One of the main challenges of wireless sensor network is how to improve its life time. The limited energy of nodes is the main obstacle. We may overcome this problem by optimizing the nodes' power consumption. A solution is clustering, but optimum clustering of wireless sensor network is an NP-Hard problem. This paper proposes a hybrid algorithm based on Genetic Algorithm and Particle Swarm Opt...

voltage stability issues are growing challenges in many modern power systems. this paper proposes optimizing the size and location of static var compensator (svc) devices using a fuzzy weighted seeker optimization algorithm (fwsoa), as an effective solution to overcome such issues. although the primary purpose of svc is bus voltage regulation, it can also be useful for voltage stability enhance...

Iztok Fister and Iztok Fister Jr. Abstract This paper introduces a novel idea for representation of individuals using quaternions in swarm intelligence and evolutionary algorithms. Quaternions are a number system, which extends complex numbers. They are successfully applied to problems of theoretical physics and to those areas needing fast rotation calculations. We propose the application of qu...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

Adapting a niching algorithm for dynamic environments is described. The Vector-Based Particle Swarm Optimizer locates multiple optima by identifying niches and optimizing them in parallel. To track optima effectively, information from previous results should be utilized in order to find optima after an environment change, with less effort than complete re-optimization would entail. The Vector-B...