EEDCHS-PSO: Energy-Efficient Dynamic Cluster Head Selection with Differential Evolution and Particle Swarm Optimization

The communication subsystem in WSNs is primarily responsible for energy consumption which becomes a consistent in the networks owing to the usage of non-rechargeable battery having a limited power supply. The technology of communicating through wireless m

  • PDF / 30,595,978 Bytes
  • 780 Pages / 439.37 x 666.142 pts Page_size
  • 5 Downloads / 185 Views

DOWNLOAD

REPORT

Recommend Documents
Hybridizing particle swarm optimization with simulated annealing and differential evolution

234 30 2MB

Ensemble particle swarm optimization and differential evolution with alternative mutation method

145 14 1MB

A novel hybrid dynamic fireworks algorithm with particle swarm optimization

201 89 3MB

An improved particle swarm optimization with clone selection principle for dynamic economic emission dispatch

188 60 697KB

Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Pe

174 82 1MB

Differential privacy distributed learning under chaotic quantum particle swarm optimization

159 69 772KB

Including Dynamic Adaptative Topology to Particle Swarm Optimization Algorithms

196 38 16MB

Nonlinear Regression in Dynamic Environments Using Particle Swarm Optimization

211 95 20MB

Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm

168 30 86MB

Hybridizing salp swarm algorithm with particle swarm optimization algorithm for recent optimization functions

272 59 5MB

Dynamic Optimization and Differential Games

202 89 5MB

Fractional Order Darwinian Particle Swarm Optimization Applications

208 42 5MB