Results 191 to 200 of about 1,929 (230)

Particle Swarm Optimisation with Enhanced Memory Particles

2014
Particle 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, 2008
This 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, 2016
We 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, Massarotto, A., SANTILANO, ALESSANDRO   +2 more
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Perceptive particle swarm optimisation: an investigation

Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005
Conventional 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, 2013
Particle 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, Esperanza García Gonzalo   +1 more
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Random Flights for Particle Swarm Optimisers

Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing and Networks / 796: Software Engineering / 792: Web-based Education, 2013
Parametric Optimisation is an important problem that can be tackled with a range of bio-inspired problem space search algorithms. We show how a simplified Particle Swarm Optimiser (PSO) can efficiently exploit advanced space exploration with L´ evy flights, Rayleigh flights and Cauchy flights, and we discuss hybrid variations of these.
Alwyn V. Husselmann, Ken A. Hawick
openaire   +1 more source

Particle swarm optimiser with neighbourhood operator

Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), 2003
In recent years population based methods such as genetic algorithms, evolutionary programming, evolution strategies and genetic programming have been increasingly employed to solve a variety of optimisation problems. Recently, another novel population based optimisation algorithm - namely the particle swarm optimisation (PSO) algorithm, was introduced ...
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Multi-region particle swarm optimisation algorithm

International Journal of Computer Applications in Technology, 2012
A number of researchers have effectively applied particle swarm optimisation (PSO) to multi-objective optimisation problems. However, it is important to obtain a well-converged and well-distributed set of Pareto-optimal solutions. This paper proposes a multi-region particle swarm optimisation (MRPSO) algorithm for multi-objective optimisation.
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Particle Swarm Optimisation with Spatial Particle Extension

2002
In this paper, we introduce spatial extension to particles in the PSO model in order to overcome premature convergence in iterative optimisation. The standard PSO and the new model (SEPSO) are compared w.r.t. performance on well-studied benchmark problems.
Krink, Thiemo, Vesterstrøm, Jakob Svaneborg, Riget, Jacques   +2 more
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Connectivity-Aware Particle Swarm Optimisation for Swarm Shepherding

IEEE Transactions on Emerging Topics in Computational Intelligence, 2023
Reem E. Mohamed, Robert Hunjet, Saber Elsayed, Hussein Abbass   +3 more
openaire   +1 more source