Evolution of Deep Neural Network Architecture Using Particle Swarm Optimization to Improve the Performance in Determining the Friction Angle of Soil

Table 1

Inputs and output of the present study.

N°	S	N30	G	e	H	Z1	Z2	(ϕ)
Unit			(kN/m^3)		(m)	(m)	(m)	(^o)
1	3	8	18.95	0.846	3.600	4.300	7.900	16.983
2	4	8	19.33	0.782	3.400	1.100	4.500	20.042
3	4	17	19.47	0.765	14.000	1.200	15.200	22.328
4	3	8	18.9	0.842	3.100	3.200	6.300	15.600
.	.	.	.	.	.	.	.	.
.	.	.	.	.	.	.	.	.
243	3	5	18.68	0.930	6.600	2.000	8.600	8.870
244	6	16	20.63	0.560	5.400	4.000	9.400	16.420
245	6	44	20.41	0.584	13.100	40.000	53.100	16.902
Min	2	2	16.2	0.416	0.800	0.000	2.000	4.23
Average	4.649	14.629	19.24	0.784	6.305	13.369	19.673	16.648
Max	9	85	21.57	1.394	33.000	77.320	79.320	33.4
SD	1.882	10.940	0.948	0.194	5.560	14.414	15.590	6.953