Interpretable machine learning optimization (InterOpt) for operational parameters: a case study of highly-efficient shale gas development.
Yuntian ChenDongxiao ZhangQun ZhaoDexun LiuPublished in: CoRR (2022)
Keyphrases
- highly efficient
- machine learning
- low cost
- case study
- fine tuning
- computer vision
- genetic algorithm
- machine learning algorithms
- decision making
- decision trees
- three dimensional
- gray code
- parameter optimization
- optimization problems
- software engineering
- maximum likelihood
- parameter estimation
- optimization method
- real time
- input parameters
- feature selection
- learning algorithm