An automated machine learning-genetic algorithm (AutoML-GA) approach for efficient simulation-driven engine design optimization.
Opeoluwa OwoyelePinaki PalAlvaro Vidal TorreiraDaniel ProbstMatthew ShaxtedMichael WildePeter Kelly SenecalPublished in: CoRR (2021)
Keyphrases
- genetic algorithm
- machine learning
- genetic algorithm ga
- fitness function
- learning classifier systems
- evolutionary computing
- evolutionary algorithm
- data driven
- artificial neural networks
- optimization method
- hybrid algorithm
- hybrid genetic algorithm
- fuzzy logic
- multi objective
- decision trees
- real coded
- genetic search
- parallel genetic algorithm
- crossover operator
- multi objective optimization
- learning algorithm
- evolutionary computation
- mathematical model
- neural network
- ant colony optimization
- metaheuristic
- simulated annealing
- computer vision
- machine learning algorithms
- genetic programming
- text classification
- crossover and mutation
- active learning
- hybrid ga
- cutting stock problems
- genetic algorithm is employed