Developing an Integrative Data Intelligence Model for Construction Cost Estimation

Table 4

Performance measures of AI models for testing data.

	R^2	RMSE	MAE	MAPE	Nash	WI
XGBoost-RF model
Model I	0.62154	1227246.543	874941.6745	0.55214	0.58448	0.88937
Model II	0.66971	831959.7023	619292.1689	0.35191	0.80904	0.94221
Model III	0.87382	804900.462	582701.9977	0.30825	0.82126	0.9404
Model IV	0.8553	859581.3363	591577.1935	0.2804	0.79615	0.92993
Model V	0.85961	823500.3632	554104.6337	0.25399	0.81291	0.93815
Model VI	0.87211	693311.4488	424619.6505	0.25539	0.86739	0.962557
Model VII	0.86511	706201.1783	461238.6876	0.26279	0.86241	0.961966
XGBoost-ANN model
Model I	0.59486	1297368.569	919557.1617	0.56905	0.53564	0.88069
Model II	0.75537	1150901.062	763471.3537	0.33141	0.63458	0.9049
Model III	0.73428	1004876.227	578230.6713	0.28253	0.72142	0.9241
Model IV	0.7481	979906.0497	523097.5798	0.28778	0.7351	0.92872
Model V	0.85042	750698.034	459356.0909	0.26579	0.84453	0.95641
Model VI	0.84828	864172.2326	570128.7514	0.23589	0.79398	0.93062
Model VII	0.83202	836314.9646	545942.9388	0.23004	0.80704	0.93977
XGBoost-SVM model
Model I	0.64182	1158278.86	803076.3523	0.80044	0.62987	0.89511
Model II	0.77873	946666.831	713338.1417	0.38731	0.75276	0.92379
Model III	0.81801	879551.0025	631843.2588	0.33659	0.78658	0.93023
Model IV	0.8256	856049.4301	586251.8811	0.26047	0.79783	0.93494
Model V	0.83321	826462.8309	542359.3988	0.23651	0.81156	0.94219
Model VI	0.78213	907434.4113	623458.3053	0.24091	0.77283	0.93306
Model VII	0.75791	958666.6949	633398.3941	0.24339	0.74646	0.92462