Developing an Integrative Data Intelligence Model for Construction Cost Estimation

Table 3

Performance measures of AI models for training data.

	R^2	RMSE	MAE	MAPE	Nash	WI
XGBoost-RF model
Model I	0.76081	788890.3191	604981.6715	0.99102	0.75994	0.93074
Model II	0.70272	879643.0411	589663.4386	0.63845	0.70154	0.90834
Model III	0.91381	472714.8598	339706.5592	0.43244	0.91381	0.97704
Model IV	0.92352	446670.1333	328896.3663	0.44469	0.92304	0.97921
Model V	0.96647	323123.8558	208083.017	0.36537	0.95973	0.98879
Model VI	0.93993	394961.8018	274148.5711	0.41215	0.95603	0.98446
Model VII	0.90717	495125.5653	337773.447	0.43415	0.90544	0.97555
XGBoost-ANN model
Model I	0.69691	860530.7166	839959.9524	0.77566	0.61666	0.83414
Model II	0.88621	582676.712	290912.5011	0.26372	0.86904	0.96865
Model III	0.95504	341388.8802	224162.0108	0.37779	0.95505	0.98838
Model IV	0.95569	338911.6945	214402.0251	0.40876	0.95569	0.98856
Model V	0.97551	253464.6776	151999.7328	0.40876	0.97522	0.99376
Model VI	0.95603	337627.8199	226863.17	0.41546	0.71921	0.91102
Model VII	0.70773	1108463.447	872191.1237	0.95867	0.52607	0.75929
XGBoost-SVM model
Model I	0.71722	838810.8081	666081.6149	0.63946	0.71436	0.91413
Model II	0.89679	527105.4427	333897.5918	0.40414	0.89283	0.97276
Model III	0.80479	717164.8809	466107.817	0.64501	0.80161	0.93934
Model IV	0.80151	735499.0773	491505.0568	0.65881	0.79134	0.93388
Model V	0.8031	715627.4657	451267.6691	0.53051	0.80246	0.94242
Model VI	0.72157	853201.115	542534.255	0.60776	0.79545	0.93821
Model VII	0.80124	727702.5318	450836.0521	0.54879	0.79574	0.93678