Application and Comparison of Machine Learning Algorithms for Predicting Rock Deformation in Hydraulic Tunnels

Table 1

Surrounding rock deformation data.

Date	Deformation/mm
2019/7/10	0.000
2019/7/11	14.500
2019/7/12	31.370
2019/7/12	34.285
2019/7/13	46.175
2019/7/14	50.260
2019/7/15	55.880
2019/7/16	64.330
2019/7/17	71.455
2019/7/18	79.985
2019/7/19	88.355
2019/7/20	95.840
2019/7/21	102.580
2019/7/22	109.910
2019/7/23	114.030
2019/7/24	120.265
2019/7/25	124.495
2019/7/26	128.205
2019/7/27	132.62
2019/7/28	135.865
2019/7/29	138.600
2019/7/30	141.730
2019/7/31	144.540
2019/8/1	147.835
2019/8/2	151.990
2019/8/3	155.160
2019/8/4	157.240
2019/8/5	160.930
2019/8/6	164.335
2019/8/7	165.520
2019/8/8	166.530
2019/8/9	169.550
2019/8/10	172.260
2019/8/11	174.055
2019/8/12	176.655
2019/8/13	178.485
2019/8/14	180.655
2019/8/15	182.840
2019/8/17	187.745
2019/8/19	191.600
2019/8/21	195.715
2019/8/25	202.39
2019/8/28	207.475
2019/8/30	210.705
2019/9/1	213.070
2019/9/4	216.885
2019/9/7	222.100
2019/9/8	222.575
2019/9/11	225.055
2019/9/15	225.300
2019/9/20	235.305
2019/9/22	235.805
2019/9/23	236.090
2019/9/26	239.375
2019/9/27	239.390
2019/9/30	242.245
2019/10/4	245.155
2019/10/6	247.280
2019/10/9	251.560
2019/10/11	254.090
2019/10/17	257.420
2019/10/23	260.300
2019/10/30	262.335
2019/11/8	262.805
2019/11/21	262.870
2019/11/28	263.070
2019/12/2	263.340
2019/12/12	265.791
2019/12/19	268.035
2019/12/24	268.140
2019/12/30	268.245