Prediction of California Bearing Ratio of Granular Soil by Multivariate Regression and Gene Expression Programming

Table 7

PQ [multinonlinear] regression analysis significant models.

Model id	Parameters	Model	R ^2	DW
PQ 1	Ln (Gr), Ln (F200) and Ln (S)		0.787	1.98443
PQ 2	Ln (Gr), Ln (F200), Ln (S) PL, LL, MDD and OMC		0.85	1.32803
PQ 3	Gr, F200, and S	CBR=−638 + 5.2Gr+ 0.2F200+ 10.8S+ 0.0366Gr^2+ 0.136F200^2− 0.0420S^2	0.794	1.85436
PQ 4	MDD and OMC	CBR=13434 − 13348MDD+ 28.3OMC+ 3286MDD^2− 1.265OMC^2	0.794	1.28769
PQ 5	Gr, F200, S, PL, LL, MDD, and OMC	CBR=9184 + 5.1Gr− 4.8F200+ 2.6S+ 7.86LL− 10.01PL− 9284MDD+ 16.6OMC− 0.0074Gr^2+ 0.211F200^2+ 0.0145S^2+ 2257MDD^2− 0.790OMC^2	0.888	1.50942
PQ 6	Gr, F200, S, MDD and OMC		0.871	1.64803
PQ 7	Ln (Gr), Ln (F200), Ln (S), MDD, and OMC		0.88	1.52370

Significance whereas .