Energy efficient information collection in wireless sensor networks using adaptive compressive sensing
We consider the problem of using wireless sensor networks (WSNs) to measure the
temporal-spatial field of some scalar physical quantities. Our goal is to obtain a sufficiently …
temporal-spatial field of some scalar physical quantities. Our goal is to obtain a sufficiently …
Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm
The particle swarm optimization (PSO) algorithm is a stochastic search technique based on
the social dynamics of a flock of birds. It has been established that the performance of the …
the social dynamics of a flock of birds. It has been established that the performance of the …
Particle swarm optimization
A Engelbrecht - Proceedings of the Companion Publication of the 2014 …, 2014 - dl.acm.org
Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and
Evolutionary Computation: Particle swarm o Page 1 Particle Swarm Optimization AP …
Evolutionary Computation: Particle swarm o Page 1 Particle Swarm Optimization AP …
General purpose optimization library (GPOL): a flexible and efficient multi-purpose optimization library in Python
Several interesting libraries for optimization have been proposed. Some focus on individual
optimization algorithms, or limited sets of them, and others focus on limited sets of problems …
optimization algorithms, or limited sets of them, and others focus on limited sets of problems …
A performance study on synchronicity and neighborhood size in particle swarm optimization
This article presents a performance study on the effect of synchronicity in communications
and neighborhood size in Particle Swarm Optimization (PSO) on large-scale optimization …
and neighborhood size in Particle Swarm Optimization (PSO) on large-scale optimization …
Competitive Coevolution-Based Improved Phasor Particle Swarm Optimization Algorithm for Solving Continuous Problems
Particle swarm optimization (PSO) is a population-based heuristic algorithm that is widely
used for optimization problems. Phasor PSO (PPSO), an extension of PSO, uses the phase …
used for optimization problems. Phasor PSO (PPSO), an extension of PSO, uses the phase …
Biomimicry of parasitic behavior in a coevolutionary particle swarm optimization algorithm for global optimization
The declining of population diversity is often considered as the primary reason for solutions
falling into the local optima in particle swarm optimization (PSO). Inspired by the …
falling into the local optima in particle swarm optimization (PSO). Inspired by the …
Particle swarm optimization: iteration strategies revisited
AP Engelbrecht - … Intelligence and 11th Brazilian Congress on …, 2013 - ieeexplore.ieee.org
Particle swarm optimization (PSO) is an iterative algorithm, where particle positions and best
positions are updated per iteration. The order in which particle positions and best positions …
positions are updated per iteration. The order in which particle positions and best positions …
Asynchronous particle swarm optimization for swarm robotics
In the original particle swarm optimization algorithm, particles' update is done
synchronously. The whole swarm fitness is evaluated first before particle update process is …
synchronously. The whole swarm fitness is evaluated first before particle update process is …
Development and applications of particle swarm optimization for constructing optimal experimental designs
SJ Walsh - 2021 - scholarworks.montana.edu
The primary objective motivating this dissertation was to illustrate the efficacy of particle
swarm optimization (PSO) as the engine of an algorithm to generate optimal design of …
swarm optimization (PSO) as the engine of an algorithm to generate optimal design of …