COVID-19 Propagation Prediction Model Using Improved Grey Wolf Optimization Algorithms in Combination with XGBoost and Bagging-Integrated Learning

Table 5

Algorithm-related parameters.

Model	Parameter setting
Bagging-COLGWO-XGBoost	n_estimators = 21
Bagging-COLGWO-GBDT	n_estimators = 21
COLGWO-XGBoost	n_estimators = 18; learning_rate = 0.8561; max_depth = 7
COLGWO- GBDT	n_estimators = 22; learning_rate = 0.3208; max_depth = 4
GWO-XGBoost	n_estimators = 46; learning_rate = 0.8563; max_depth = 6
GWO-GBDT	n_estimators = 38; learning_rate = 0.5996; max_depth = 4
XGBoost	Default parameter
GBDT	Default parameter
LSTM	Optimizer = Adam; loss = mse; epochs = 100
RNN	Optimizer = Adam; loss = mse; epochs = 100
CNN	Optimizer = Adam; loss = mse; epochs = 100
SVR	Default parameter
MLP	Default parameter
LR	Default parameter
COLGWO	Iteration number: 100; Population size: 30
GWO	Iteration number: 100; Population size: 30