| GHBS samples from the Nankai Trough in Japan |
ANN |
NS |
HSTS and HSSS |
0.9958 |
NS |
0.0013 |
The new NN structure outperformed the CNN in the
estimation of the tensile and shear strength |
(51) |
| HSTS and HSSS |
0.9297 |
0.05 |
| Morphology and saturation of Alaminos Canyon (Block
21) |
LSTM and LSF |
GR, ρ, Vp, RL |
Vs |
0.876 |
1.5634 |
0.0114 |
The LSTM method performs better than LSF in the predictions
of the shear wave velocity and the hydrate morphologies |
(81) |
| GHBS saturation in the Shenhu area, South China Sea (SH7) |
RNN |
R and AV |
HS |
0.7085 |
NS |
0.1208 |
This method has a higher accuracy prediction of gas hydrate
saturation than traditional machine learning methods |
(82) |
| GHBS saturation, Korean East Sea region |
RF |
CT Scan (DS, IWS, GHF, and GWD) |
HS |
NS |
NS |
27 |
The RF best predicts the performance
for water,
gas, and GH saturation in the samples among the three methods. The
CNN and SVR also exhibit sufficient performances |
(83) |
| SVR |
CT Scan (DS, IWS, GHF, and GWD) |
HS |
1088.5 |
| CNN |
CT Scan (DS, IWS, GHF, and GWD) |
HS |
434 |
