A multi-objective memetic and hybrid methodology for optimizing the parameters and performance of artificial neural networks.
Leandro M. AlmeidaTeresa Bernarda LudermirPublished in: Neurocomputing (2010)
Keyphrases
- multi objective
- artificial neural networks
- optimization algorithm
- neural network
- evolutionary algorithm
- differential evolution
- particle swarm optimization
- genetic algorithm
- sensitivity analysis
- objective function
- maximum likelihood
- multi objective optimization
- computational intelligence
- input variables
- multiple objectives
- analytical models
- multi objective evolutionary algorithms
- hybrid model
- simulated annealing and tabu search
- memetic algorithm
- design methodology
- control parameters
- parameter values
- soft computing
- neural network model