A Hybrid Ensemble Model Based on ELM and Improved AdaBoost.RT Algorithm for Predicting the Iron Ore Sintering Characters

Table 1

Descriptive statistics of the variables.

Variables	Description	Unit	Minimum	Maximum	Average	Standard deviation
	Limestone	%	0.745	3.98	2.429	0.598
	Dolomite	%	3.074	5.381	4.208	0.434
	Quick lime	%	4.795	5.893	5.175	0.292
	Internal return fines	%	16.336	22.623	18.906	1.091
	Basicity	—	1.69	1.97	1.832	0.055
	Moisture rate	%	7.247	8.926	8.017	0.348
	Bed height	mm	653.444	816.063	768.691	35.457
	Bed permeability	—	33.935	56.957	45.276	3.575
	Strand speed	m/min	2.528	3.36	2.932	0.15
	Ignition density		1.534	2.255	1.824	0.141
	Ignition air-fuel ratio	—	4.98	6.321	5.124	0.182
	Insulation furnace temperature		488.428	973.015	729.905	111.987
	Preheating air temperature		229.296	328.856	294.24	14.022
	Exhaust fan negative pressure	kPa	12.616	19.483	16.886	1.141
	TFe	%	57.56	58.702	58.23	0.222
	FeO	%	7.376	10.498	8.806	0.573
	CaO	%	8.46	9.61	9.064	0.217
	MgO	%	1.258	1.78	1.483	0.1
		%	4.545	5.282	4.952	0.122
		%	1.588	1.83	1.724	0.046
	Solid fuel consumption	kg	40.963	53.971	47.223	2.304
	Gas fuel consumption		1.888	2.895	2.274	0.169
	Burning through point	—	24.459	27.924	26.588	0.542
	Tumbler index	%	74.2	84.1	78.424	1.5