Numerical Integration Method Based on Particle Swarm Optimization
نویسندگان
چکیده
In this paper, a novel numerical double integration method based on Particle Swarm Optimization (PSO) was presented. PSO is a technique based on the cooperation between particles. The exchange of information between these particles allows to resolve difficult problems. This approach is carefully handled and tested with an illustrated example.
منابع مشابه
GENERALIZED FLEXIBILITY-BASED MODEL UPDATING APPROACH VIA DEMOCRATIC PARTICLE SWARM OPTIMIZATION ALGORITHM FOR STRUCTURAL DAMAGE PROGNOSIS
This paper presents a new model updating approach for structural damage localization and quantification. Based on the Modal Assurance Criterion (MAC), a new damage-sensitive cost function is introduced by employing the main diagonal and anti-diagonal members of the calculated Generalized Flexibility Matrix (GFM) for the monitored structure and its analytical model. Then, ...
متن کاملAN EFFICIENT HYBRID ALGORITHM BASED ON PARTICLE SWARM AND SIMULATED ANNEALING FOR OPTIMAL DESIGN OF SPACE TRUSSES
In this paper, an efficient optimization algorithm is proposed based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to optimize truss structures. The proposed algorithm utilizes the PSO for finding high fitness regions in the search space and the SA is used to perform further investigation in these regions. This strategy helps to use of information obtained by swarm in an opt...
متن کاملResearch of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information
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...
متن کاملResearch of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information
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...
متن کاملDesign of Distributed Detection Systems with Correlated Heterogeneous Sensors
The optimization of sensor thresholds and fusion rule for heterogeneous and correlated sensor suite is accomplished through a particle swarm optimization algorithm. Different correlation structures are assumed and the effect of correlation on the choice of final fusion rule and thresholds is analyzed. Optimal decision fusion for correlated sensors includes estimation of 2 joint probabilities. B...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011