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Heterogeneous Particle Swarm Optimization
2010Particles in the standard particle swarm optimization (PSO) algorithms, and most of its modifications, follow the same behaviours. That is, particles implement the same velocity and position update rules. This means that particles exhibit the same search characteristics.
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Emotional Particle Swarm Optimization
2009It is known that there is only information sharing in most particle swarm optimization. But competition among particles which is a good feature for searching progress does not exist. For all these, based on the idea of multiagent with emotion, bring in competition controlled by emotion to enhance performance of PSO after describing similarity between ...
Wei Wang 0162 +3 more
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The Thermodynamic Particle Swarm Optimizer
2008 International Conference on Computer Science and Software Engineering, 2008This paper has presented a novel optimization algorithm - thermodynamic particle swarm optimizers (TDPSO). It combines the simplified evolutionary equation and the thermodynamically strategy.The simplified equation without the velocity variable has drastically reduced computation costs to achieve faster convergence.
Yu Wu, Yuanxiang Li, Xing Xu, Shen Peng
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Predicted Particle Swarm Optimization
2006 5th IEEE International Conference on Cognitive Informatics, 2006The standard particle swarm optimization (PSO) may prematurely converge on suboptimal solution partly because of the insufficiency information utilization of the velocity. The time cost by velocity is longer than position of each particle of the swarm, though the velocity, limited by the constant vmax, only provides the positional displacement.
Zhihua Cui +2 more
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Particle Swarm Optimization on FPGA
2018 30th International Conference on Microelectronics (ICM), 2018The particle swarm optimization PSO is an attractive domain for community looking to enhance time for optimal solutions. Several works will be done for SW or SW/HW implementation. The latter often gives better performance. In this paper, we present a comparative study of these various solutions and we focus on the FPGA ones.
Monia Ettouil +2 more
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Particle Swarm Optimization with Disagreements
2011This paper introduces an enhancement to the particle swarm optimization algorithms that models a characteristic of social groups: the disagreements between individuals. After a short introduction, we describe the new concept theoretically and define a special type of particle swarm optimization with disagreements: the 6s-PSOD.
Andrei Lihu, Stefan Holban
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A naive Particle Swarm Optimization
2012 IEEE Congress on Evolutionary Computation, 2012Since the proposal of Particle Swarm Optimization (PSO), there have been many improvements of PSO which have not change the basic paradigm of PSO involving pattern of movement of particles, update mode of particles and algorithm framework. Instead of another improvement of PSO, a novel paradigm of PSO with more natural and simpler forms, called naive ...
Jin Qin, Zhenjun Liang
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Asynchronous Particle Swarm Optimization
2007 IEEE 15th Signal Processing and Communications Applications, 2007In this article we consider an asynchronous particle swarm optimization (PSO) algorithm. In addition to the fact that the particles can update their estimates independently time delays are also allowed in obtaining information from their neighbors. Moreover, we test the performance of the algorithm with a simulation example.
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Alignment particle swarm optimization
2009 8th IEEE International Conference on Cognitive Informatics, 2009Particle swarm optimization (PSO) simulates the boids' collective behaviors. The original biological background of boid should follow three basic simple steering behaviors: separation, alignment and cohesion. However, to promote a fast convergent speed, the velocity update manner of each boid omits the alignment rule, this may result premature ...
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