Genetic learning particle swarm optimization [PDF]
, 2016 Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness.
Chung, Henry Shu-Hung +6 more
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A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm [PDF]
, 2005 IEEE Congress on Evolutionary Computation. Edimburgo, 5 september 2005This paper shows the performance of the binary PSO algorithm as a classification system.
Cervantes, Alejandro +2 more
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Particle Swarm Optimization Based Source Seeking [PDF]
, 2015 Signal source seeking using autonomous vehicles is a complex problem. The complexity increases manifold when signal intensities captured by physical sensors onboard are noisy and unreliable.
Bhattacharya, Sourabh +6 more
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Node placement in Wireless Mesh Networks: a comparison study of WMN-SA and WMN-PSO simulation systems [PDF]
, 2016 (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or ...
Barolli, Leonard +5 more
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Handling boundary constraints for particle swarm optimization in high-dimensional search space [PDF]
, 2011 Despite the fact that the popular particle swarm optimizer (PSO) is currently being extensively applied to many real-world problems that often have high-dimensional and complex fitness landscapes, the effects of boundary constraints on PSO have not ...
Chu, W, Gao, X, Sorooshian, S
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Building nearest prototype classifiers using a Michigan approach PSO [PDF]
, 2007 IEEE Swarm Intelligence Symposium. Honolulu, HI, 1-5 april 2007This paper presents an application of particle swarm optimization (PSO) to continuous classification problems, using a Michigan approach. In this work, PSO is used to process training data to
Cervantes, Alejandro +2 more
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Orthogonal learning particle swarm optimization [PDF]
, 2010 Particle swarm optimization (PSO) relies on its learning strategy to guide its search direction. Traditionally, each particle utilizes its historical best experience and its neighborhood’s best experience through linear summation.
Li, Y., Shi, Y-H., Zhan, Z-H., Zhang, J.
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Bi-velocity discrete particle swarm optimization and its application to multicast routing problem in communication networks [PDF]
, 2014 This paper proposes a novel bi-velocity discrete particle swarm optimization (BVDPSO) approach and extends its application to the NP-complete multicast routing problem (MRP).
Chen, Wei-Neng +5 more
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A particle swarm optimization based memetic algorithm for dynamic optimization problems [PDF]
, 2009 Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic.
AS Uyar +25 more
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The pathological role of Wnt5a in psoriasis and psoriatic arthritis. [PDF]
, 2019 Psoriasis (PsO) is a chronic inflammatory skin disease with both local and systemic components. PsO-associated arthritis, known as psoriatic arthritis (PsA), develops in approximately 13%-25% of PsO patients.
Li, Zhengxiao +2 more
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