Prediction of the Electrical Strength and Boiling Temperature of the Substitutes for Greenhouse Gas SF₆ Using Neural Network and Random Forest.
Hao SunLuqi LiangChunlin WangYi WuFei YangMingzhe RongPublished in: IEEE Access (2020)
Keyphrases
- random forest
- neural network
- short term prediction
- prediction model
- genetic algorithm
- random forests
- prediction accuracy
- ensemble methods
- decision trees
- heat transfer
- ensemble classifier
- solar radiation
- feature set
- wind speed
- fold cross validation
- artificial neural networks
- environmental variables
- ensemble learning
- multi layer perceptron
- multi label
- feature importance
- computer vision
- decision tree learning algorithms
- rotation forest
- base classifiers
- feature extraction
- small number