نتایج جستجو برای: swarm optimization

تعداد نتایج: 325097  

2013
Rebika Rai Ratika Pradhan M. K. Ghose

-The social insect allegory for working out problems has become a promising area in the recent years emphasizing on stochastic construction practice building the key probabilistically. The approach focuses on direct or indirect communications among uncomplicated agents. Swarm Intelligence is the collective behavior of decentralized, self-organized system whereby the joint behavior of agent inte...

Journal: :International Journal of Electrical and Computer Engineering (IJECE) 2017

Journal: :IEEE Access 2022

Popular methods to deal with computation become strenuous due the optimization demands that develop more complex nowadays. This research aims propose a new optimal algorithm, Dove Swarm Optimization (DSO), adopts foraging behaviors of doves have six benchmark functions expressing DSO performance. By considering competition for forage, is designed ensure most satisfied dove as well optimization,...

Journal: :IJSIR 2016
Daniel Hein Alexander Hentschel Thomas A. Runkler Steffen Udluft

This article introduces a model-based reinforcement learning (RL) approach for continuous state and action spaces. While most RL methods try to find closed-form policies, the approach taken here employs numerical on-line optimization of control action sequences. First, a general method for reformulating RL problems as optimization tasks is provided. Subsequently, Particle Swarm Optimization (PS...

2003
Janos Madar Janos Abonyi Ferenc Szeifert

The aim of this paper is to present the historical background of artificial life based stochastic optimization algorithms from the viewpoint of Neumann’s Self-reproduction scheme. The theory of evolutionary and swarm optimization are overviewed and compared from this viewpoint. A detailed application example is given to demonstrate how these tools can be applied to solve process optimization pr...

2017
Xiaohua Nie Wei Wang Haoyao Nie

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In or...

2012
Xiaoyu Song

Particle swarm optimization (PSO) algorithm is a kind of random optimization algorithm based on swarm intelligence. Swarm intelligence of PSO is produced by cooperation and competition between particles, which is used for guiding optimization search. PSO has been studied widely in many applications due to its good global searching ability. Currently PSO has been widely used in function optimiza...

2010
Sabine Helwig

Particle swarm optimization (PSO) is an optimization approach from the field of artificial intelligence. A population of so-called particles moves through the parameter space defined by the optimization problem, searching for good solutions. Inspired by natural swarms, the movements of the swarm members depend on own experiences and on the experiences of adjacent particles. PSO algorithms are m...

2010
Cheng-Jian Lin Chi-Feng Wu

In this paper, a recurrent functional neural fuzzy network (RFNFN) with symbiotic particle swarm optimization (SPSO) is proposed for solving identification and prediction problems. The proposed RFNFN model has feedback connections added in the membership function layer that can solve temporal problems. Moreover, an efficient learning algorithm, called symbiotic particle swarm optimization (SPSO...

2009
Yunyang Yan Zhibo Guo Jingyu Yang

Electric power line overhaul plan is an important issue on power system and engineering practice. As particle swarm optimization is to be a new intelligent algorithm. It is gradually applied into power system these years. This paper provides a relative mathematical model to solve the problems in power line overhaul. Particle swarm optimization algorithm has advantages of less parameters setting...

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