Prediction of environmental indicators in land leveling using artificial intelligence techniques

Chemical and Biological Technologies in Agriculture

Table 2 Analysis of variance for labor energy (LE), fuel energy (FE), total machinery cost (TMC), total machinery energy (TME) models

Model	Source	Sum of squares	df	Mean square	F value	P value Prob > F
LE model	Model	1.24¹¹	3	4.15¹⁰	5523.914	< 0.0001
	Slope	1.85⁹	1	1.85⁹	246.7733	< 0.0001
	Cut-fill volume (V)	1.21¹¹	1	1.21¹¹	16,149.7	< 0.0001
	Soil swelling index (SSI)	2.61⁸	1	2.61⁸	34.70285	< 0.0001
FE model	Model	1.84¹³	3	6.15¹²	4632.446458	< 0.0001
	Slope	3.43¹¹	1	3.43¹¹	258.640572	< 0.0001
	V	1.78¹³	1	1.78¹³	13,457.37208	< 0.0001
	% Sand	3.28¹⁰	1	3.28¹⁰	24.73922519	< 0.0001
TMC model	Model	1.16¹⁹	3	3.88¹⁸	4751.319	< 0.0001
	Slope	1.8¹⁷	1	1.8¹⁷	220.2573	< 0.0001
	V	1.13¹⁹	1	1.13¹⁹	13,881.29	< 0.0001
	SSI	2.21¹⁶	1	2.21¹⁶	27.00684	< 0.0001
TME model	Model	6.64¹⁶	3	2.21¹⁶	5653.467	< 0.0001
	Slope	9.6¹⁴	1	9.6¹⁴	245.4494	< 0.0001
	V	6.47¹⁶	1	6.47¹⁶	16,537.35	< 0.0001
	SSI	1.44¹⁴	1	1.44¹⁴	36.87527	< 0.0001