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An analysis of particle swarm optimizers
Many scientific, engineering and economic problems involve the optimisation of a set of parameters. These problems include examples like minimising the losses in a power grid by finding the optimalExpand
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A study of particle swarm optimization particle trajectories
TLDR
This paper overviews current theoretical studies, and extend these studies to investigate particle trajectories for general swarms to include the influence of the inertia term. Expand
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A NICHING PARTICLE SWARM OPTIMIZER
TLDR
This paper describes a technique that extends the unimodal particle swarm optimizer to efficiently locate multiple optimal solutions in multimodal problems by monitoring the fitness of individual particles. Expand
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Cooperative learning in neural networks using particle swarm optimizers
TLDR
This paper presents a method to employ particle swarms optimizers in a cooperative configuration. Expand
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A Convergence Proof for the Particle Swarm Optimiser
TLDR
The Particle Swarm Optimiser (PSO) is a population based stochastic optimisation algorithm, empirically shown to be efficient and robust. Expand
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Effects of swarm size on Cooperative Particle Swarm Optimisers
TLDR
This paper investigates the effect of swarm size on the CPSO, showing that the CPS does not exhibit the same general trend as the original PSO. Expand
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Multiview Deep Learning for Land-Use Classification
TLDR
A multiscale input strategy for multiview deep learning is proposed for supervised multispectral land-use classification, and it is validated on a well-known data set. Expand
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Locating multiple optima using particle swarm optimization
TLDR
This paper presents a new particle swarm optimization (PSO) technique to locate and refine multiple solutions to multimodal optimization problems. Expand
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Using neighbourhoods with the guaranteed convergence PSO
TLDR
The standard particle swarm optimiser may prematurely converge on suboptimal solutions that are not even guaranteed to be local extrema. Expand
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Detecting Land Cover Change Using an Extended Kalman Filter on MODIS NDVI Time-Series Data
TLDR
A method for detecting land cover change using NDVI time-series data derived from 500-m MODIS satellite data is proposed, and experimental results indicate an 89% change detection accuracy. Expand
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