GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace.
Andrés Sanz-GarcíaJulio Fernández-CenicerosFernando Antoñanzas-TorresAlpha V. Pernía-EspinozaFrancisco J. Martínez de Pisón AscacibarPublished in: Appl. Soft Comput. (2015)
Keyphrases
- parameter optimization
- genetic algorithm ga
- simulated annealing
- genetic algorithm
- random search
- fitness function
- initial population
- feature selection
- particle swarm optimization pso
- artificial neural networks
- support vector machine
- parameter settings
- differential evolution
- support vector regression
- neural network
- evolutionary algorithm
- parameter estimation
- crossover operator
- search algorithm
- metaheuristic
- pid controller
- optimal solution
- real time