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Beyond Standard Particle Swarm Optimisation
International Journal of Swarm Intelligence Research, 2010Currently, two very similar versions of PSO are available that could be called “standard”. While it is easy to merge them, their common drawbacks still remain. Therefore, in this paper, the author goes beyond simple merging by suggesting simple yet robust changes and solving a few well-known, common problems, while retaining the classical structure ...
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Nonlinear Mapping using Particle Swarm Optimisation
2005 IEEE Congress on Evolutionary Computation, 2005Large datasets consisting of high-dimensional vectors commonly describe complex objects. Having these vectors exist in a smaller dimension where the topological characteristics of the original space are preserved, allows clusters or patterns inherent in the data to be identified.
A.I. Edwards +2 more
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Particle swarm optimisation: a triggered approach
International Journal of Industrial and Systems Engineering, 2014This paper presents a modification to the particle swarm optimisation (PSO) to tackle two difficulties observed in many applications: premature convergence of the solution, and the degree of confidence of the decision maker. This approach, known as triggered particle swarm optimisation, treats the problem in a dynamic environment and making each ...
Mohamed H. Gadallah +2 more
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Particle swarm optimisation with differential mutation
International Journal of Intelligent Systems Technologies and Applications, 2012Particle swarm optimisation PSO is population-based optimisation algorithm having stochastic in nature. PSO has quick convergence speed but often gets stuck into local optima due to lacks of diversity. In this work, first mutation operator adopted from Differential Evolution DE algorithm is applied in PSO with decreasing inertia weight PSO-DMLB.
Tapas Si, Nanda Dulal Jana
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Baseline detection using Particle Swarm Optimisation
2010 10th International Conference on Intelligent Systems Design and Applications, 2010Signature is a popular method of seeking approval and authentication between various parties in many transaction applications. Signature pattern recognition is done by processing a set of data that consists of (x, y) coordinates, representing online signature.
Siti-Hakimah Manshor +4 more
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Particle Swarm Optimisation with Enhanced Memory Particles
2014Particle swarm optimisation (PSO) is a general purpose optimisation algorithm in which a population of particles are attracted to their past success and the success of other particles. This paper introduces a new variant of the PSO algorithm, PSO with Enhanced Memory Particles, where the cognitive influence is enhanced by having particles remember ...
Ian Broderick, Enda Howley
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Particle swarm optimisation for object classification
2008 23rd International Conference Image and Vision Computing New Zealand, 2008This paper describes a new approach to the use of particle swarm optimisation (PSO) for object classification problems. Instead of using PSO to evolve only a set of good parameter values for another machine learning method for object classification, the new approach developed in this paper can be used as a stand alone method for classification. Two new
H. Evans, M. Zhang
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Particle Swarm Optimisation of Electromagnetic Soundings
Proceedings, 2016We discuss through synthetic and real data some the application of PSO in electromagnetic soundings. The suggested approach can be easily adapted to resistivity soundings (RS), time domain soundings (TDEM) , magneto-telluric (MT) and audio-magneto-telluric survey (AMT). We propose an overview on the PSO for solving 1D problems with a priori information
GODIO, Alberto +2 more
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Perceptive particle swarm optimisation: an investigation
Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005Conventional particle swarm optimisation relies on exchanging information through social interaction among individuals. However for real-world problems involving control of physical agents (i.e., robot control), such detailed social interaction is not always possible. Recently, the perceptive particle swarm optimisation (PPSO) algorithm was proposed to
B. Kaewkamnerdpong, P.J. Bentley
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Particle swarm optimisation: time for uniformisation
International Journal of Computing Science and Mathematics, 2013Particle swarm optimisation PSO is an evolutionary algorithm that has been successfully applied to many optimisation problems in different fields. PSO has been heuristically proposed based in a social analogy for large groups in nature. Since its publication, research has been carried to understand the PSO convergence and improving its numerical ...
Juan Luis Fernández Martínez +1 more
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