Particle swarm optimization is a popular method for solving difficult optimization problems. There have been attempts to formulate the method in formal probabilistic or stochastic terms (e.g. bare bones particle swarm) with the aim to achieve more generality and explain the practical behavior of the method. Here we present a Bayesian interpretation of the particle swarm optimization. This inter...

This paper presents the application of membrane algorithms to broadcasting problems, which are regarded as NP-hard combinatorial optimization problems. A membrane algorithm, called HPSOPS, is proposed by appropriately combining membrane systems and a hybrid particle swarm optimization with wavelet mutation (HPSOWM). HPSOPS is designed with the hierarchical membrane structure and transformation/...

This paper presents a dynamic particle swarm optimization based search for optimal fusion configuration of sensors in distributed detection network in presence of a nonstationary binary symmetric channel. The wireless channel in sensor networks is a non-stationary random process, which moves the optima of the original problem, otherwise static. The optimal fusion configuration minimizes the pro...

voltage profile and losses are important factors in a distribution network in which there arevariety of ways to improve them. in this paper, distributed generation (dg) is used as a solutionto improve the above characteristics. backward/forward sweep load flow algorithm is used dueto the inefficiency of usual load flow algorithms because of high r/x ratio and their lack ofconvergence in distrib...

For economic benefit of wind power generation, the equivalent conversion relationships and models between the different “quality” energy are studied deeply in the conversion processes of wind energy. Considering the effect of load demand characteristics and energy supply price on the wind energy utilization mode comprehensively, the multi-objective trans-utilization optimization model of wind e...

The swarm collective behaviors, such as birds flocking and fish schooling, are complex, dynamic and adaptive processes, in which the differences among individuals play an important role. As a new swarm intelligent technique, the standard particle swarm optimization only provides a simple uniform control, omitting the above mentioned phenomenon entirely. Thus, a new modified version: performance...

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, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...