基于K-Means聚类与Ridge回归算法的煤炭发热量预测研究

乔世超, 陈衡, 李博, 潘佩媛, 徐钢

Research on Coal Calorific Value Prediction Based on K-Means Clustering and Ridge Regression Algorithm

Shichao QIAO, Heng CHEN, Bo LI, Peiyuan PAN, Gang XU

表3 不同回归算法对应的模型评价指标

Tab. 3 Model evaluation indicators corresponding to different regression algorithms

回归算法	回归方程	δ_MAE	δ_RMSE	R²
OLS回归	$Q_{n e t, a r} = 26.569 84 - 0.337 03 M_{a r} - 0.291 47 A_{a r} + 0.103 11 F_{C, a r}$	0.270 36	0.628 38	0.942 94
Lasso回归	$Q_{n e t, a r} = 21.542 41 - 0.150 61 M_{a r} - 0.222 05 A_{a r} + 0.133 61 F_{C, a r}$	0.464 60	0.792 84	0.909 16
Ridge回归	$Q_{n e t, a r} = 26.569 15 - 0.337 01 M_{a r} - 0.291 46 A_{a r} + 0.103 12 F_{C, a r}$	0.248 45	0.592 63	0.945 63
Elastic Net回归	$Q_{n e t, a r} = 23.358 12 - 0.220 51 M_{a r} - 0.247 72 A_{a r} + 0.123 42 F_{C, a r}$	0.358 70	0.696 54	0.929 89