Training feedforward neural networks using hybrid particle swarm optimization and gravitational search algorithm

DOI10.1016/j.amc.2012.04.069zbMath1282.90248OpenAlexW2050546928MaRDI QIDQ387497

Hossein Moradian Sardroudi, Siti Zaiton Mohd Hashim, SeyedAli Mirjalili

Publication date: 23 December 2013

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2012.04.069

zbMATH Keywords

FNNneural networkmultilayer perceptronevolutionary algorithmgravitational search algorithmparticle swarm optimizationPSOlearning neural network

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59)

Related Items (13)

Hybrid particle swarm optimization and pattern search algorithm ⋮ Autonomous particles groups for particle swarm optimization ⋮ A generic framework for handling constraints with agent-based optimization algorithms and application to aerodynamic design ⋮ Stability analysis of particle dynamics in gravitational search optimization algorithm ⋮ GSA improvement via the von Neumann stability analysis ⋮ Solving Dirichlet boundary problems for ODEs via swarm intelligence ⋮ Training artificial neural networks by a hybrid PSO-CS algorithm ⋮ A new swarm intelligence approach for clustering based on krill herd with elitism strategy ⋮ A novel Hausdorff fractional NGMC\((p,\mathrm{n})\) grey prediction model with grey wolf optimizer and its applications in forecasting energy production and conversion of China ⋮ A review on computational intelligence for identification of nonlinear dynamical systems ⋮ A novel kernel extreme learning machine algorithm based on self-adaptive artificial bee colony optimisation strategy ⋮ Two kinds of classifications based on improved gravitational search algorithm and particle swarm optimization algorithm ⋮ Quantum particle swarm optimization algorithm with the truncated mean stabilization strategy

Uses Software

• BGSA
• GSA

Cites Work

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• BGSA: Binary gravitational search algorithm
• A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
• An online gradient method with momentum for two-layer feedforward neural networks
• Approximating polynomial functions by feedforward artificial neural networks: Capacity analysis and design
• An adaptive conjugate gradient learning algorithm for efficient training of neural networks
• Multilayer feedforward networks are universal approximators
• GSA: A gravitational search algorithm

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