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

Table 1

Samples of training 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	87	3.1	1.6	2.3	0.12	1.54	0.123	II	II
2	7	78	3.9	0.9	4.2	0.08	3.21	0.132	I	I
3	8	79	2.3	1.2	3.2	0.17	1.32	0.112	II	II
4	8	81	1.8	0.8	2.5	0.18	2.33	0.185	I	I
5	9	82	2.3	0.6	1.8	0.12	4.12	0.156	II	II
6	7	79	8.2	1.8	5.6	0.31	2.45	0.125	III	III
7	7	108	11.9	1.6	20.0	0.12	7.12	0.175	III	III
8	8	82	3.6	1.6	17.0	0.13	1.75	0.132	IV	IV
9	9	86	8.8	1.3	17.0	0.16	1.62	0.175	IV	IV
10	8	92	4.0	0.9	13.0	0.14	1.32	0.164	III	III
11	7	111	5.8	2.8	8.0	0.12	1.42	0.124	II	II
12	7	98	9.2	1.5	10.0	0.14	2.12	0.266	II	II
13	9	65	5.3	1.5	8.0	0.12	2.62	0.232	I	I
14	8	64	2.0	0.8	9.0	0.12	1.36	0.212	II	II
15	7	45	2.6	1.6	6.0	0.32	2.12	0.111	II	II
16	8	35	2.61	0.6	12.0	0.25	1.75	0.325	I	I
17	8	75	1.8	1.2	7.0	0.15	2.12	0.133	III	III
18	9	106	8.5	3.0	28.0	0.23	3.01	0.285	III	III
19	7	32	3.8	0.9	6.0	0.16	1.74	0.325	II	II
20	8	25	6.8	0.9	9.0	0.12	4.11	0.311	I	I
21	7	109	13.8	2.8	15.0	0.18	2.65	0.162	III	III
22	9	42	4.5	3.2	25.0	0.32	5.41	0.156	IV	IV
23	9	45	1.3	0.9	13.0	0.19	2.65	0.132	III	III
24	8	120	5.1	2.8	12.0	0.21	2.23	0.174	II	II
25	7	110	3.3	3.1	1.2	0.16	2.45	0.133	II	II
26	7	46	4.3	2.9	13.0	0.22	1.98	0.173	III	III
27	8	23	14.8	3.9	35.0	0.15	2.31	0.284	IV	IV
28	8	110	14.5	1.2	21.0	0.13	1.93	0.122	III	III
29	8	65	5.3	3.7	20.0	0.20	1.85	0.186	IV	IV
30	8	25	3.6	2.3	16.0	0.25	2.65	0.196	III	III