Sandy Soil Liquefaction Prediction Based on Clustering-Binary Tree Neural Network Algorithm Model

Table 2

Samples of testing for sand earthquake liquefaction.

Serial number	Intensity	Epicenter distance	Sand buried depth	Groundwater level	Number of hammers	Average particle size	Nonuniformity coefficient	Dynamic shear stress ratio	Measured category	Machine learning result
	I/grade	R (km)	ds (m)	(m)	N/strike	D50 (mm)	Cu
1	8	78	5.2	1.2	8.0	0.16	2.15	0.15	III	III
2	8	21	4.2	1.3	6.0	0.13	2.89	0.275	I	I
3	7	68	3.2	1.5	5.0	0.11	1.95	0.135	III	III
4	9	49	2.8	1.2	6.0	0.14	2.13	0.135	II	II
5	7	52	6.5	2.6	9.0	0.18	2.30	0.121	III	III
6	9	52	4.2	1.8	9.0	0.28	2.13	0.153	IV	IV
7	8	32	3.9	1.3	8.0	0.13	2.07	0.265	II	II
8	8	68	2.6	1.1	7.0	0.15	0.63	0.165	III	III
9	9	57	4.8	1.2	7.0	0.10	4.89	0.356	II	II
10	8	75	10.2	1.9	10.0	0.15	2.35	0.165	III	III