Parameter Optimization for CNN-LSTM by Using Uniform Experimental Design.
Cheng-Hsin YenFu-I ChouYu-Cheng LiaoPo-Yuan YangJyh-Horng ChouPublished in: ISPACS (2021)
Keyphrases
- experimental design
- parameter optimization
- genetic algorithm ga
- genetic algorithm
- differential evolution
- parameter estimation
- parameter settings
- active learning
- empirical studies
- support vector machine
- pid controller
- feature selection
- sample size
- class imbalance
- learning objects
- model selection
- optimization algorithm
- evolutionary algorithm
- objective function
- bayesian networks