Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution.
Sung-Kwun OhWook-Dong KimWitold PedryczSu-Chong JooPublished in: Neurocomputing (2012)
Keyphrases
- differential evolution
- particle swarm optimization
- radial basis function neural network
- radial basis function
- optimization algorithm
- convergence speed
- evolutionary algorithm
- particle swarm optimization pso
- genetic algorithm
- optimization method
- evolutionary strategy
- neural network
- pso algorithm
- rbf network
- hybrid algorithm
- k means
- multi objective
- rbf neural network
- rbfnn
- particle swarm
- pattern classification
- particle swarm optimization algorithm
- global optimization
- metaheuristic
- hidden layer
- function approximation
- artificial neural networks
- genetic programming
- support vector machine svm