Novel Approach to Predicting Soil Permeability Coefficient Using Gaussian Process Regression
Abstract
:1. Introduction
2. Methodology
2.1. Data Catalog
2.2. Gaussian Process Regression
Details of Kernel Functions
- Polynomial (Poly)
- 2.
- Radial basis function (RBF)
- 3.
- Pearson universal kernel (PUK)
2.3. Performance Metrics and Evaluation
3. Results and Discussion
4. Comparison of Performance with Other Methods
5. Sensitivity Analysis
6. Conclusions
- Comparing GPR models’ performance reveals that the GPR-PUK model gives more accurate prediction results with the coefficient of determination being 0.951, achieved from the correlation between experimental and estimated values of k.
- The GPR-PUK model’s estimation of the soil permeability coefficient was found to be more reliable than that of the ANN, SVM, RF, and M5P models reported in the literature.
- The findings of the sensitivity analysis demonstrate that different input factors have varying degrees of significance on the coefficient of soil permeability as w > e > LL > PL > CC > γ.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Notation
ANN | Artificial neural network |
RF | Random forest |
SVM | Support vector machine |
GPR | Gaussian process regression |
MAE | Mean absolute error |
M5P | M5Prime algorithm |
RMSE | Root mean square error |
PUK | Pearson universal kernel |
RBF | Radial basis function |
XGBoost | Extreme gradient boosting |
R2 | Coefficient of determination |
R | Correlation coefficient |
k | Soil permeability coefficient (×10−9 cm/s) |
LL | Liquid limit (%) |
PL | Plastic limit (%) |
CC | Clay content (%) |
e | Void ratio |
w | Natural water content (%) |
γ | Specific density (g/cm3) |
Appendix A
S. No. | CC (%) | w (%) | LL (%) | PL (%) | γ (g/cm3) | e | k (×10−9 cm/s) |
---|---|---|---|---|---|---|---|
1 | 44 | 93.73 | 75.62 | 46.8 | 2.59 | 2.453 | 0.029 |
2 | 21.7 | 20.71 | 24.58 | 13.5 | 2.72 | 0.639 | 0.01 |
3 | 51.8 | 20.98 | 38.17 | 20.2 | 2.73 | 0.625 | 0.003 |
4 | 9.7 | 18.02 | 20.51 | 14.2 | 2.68 | 0.605 | 0.007 |
5 | 46.9 | 95.58 | 82.25 | 53 | 2.6 | 2.514 | 0.026 |
6 | 12.7 | 22.71 | 28.5 | 17.8 | 2.69 | 0.671 | 0.01 |
7 | 47.5 | 85.35 | 71.24 | 40.5 | 2.62 | 2.275 | 0.014 |
8 | 59.4 | 24.95 | 41.87 | 22.3 | 2.74 | 0.713 | 0.003 |
9 | 9.2 | 23.97 | 26.52 | 19.8 | 2.67 | 0.723 | 0.008 |
10 | 55.3 | 98.01 | 73.63 | 40.1 | 2.59 | 2.597 | 0.035 |
11 | 44.8 | 79.96 | 75.45 | 43.6 | 2.59 | 2.083 | 0.039 |
12 | 51.1 | 73.75 | 66.96 | 35.8 | 2.61 | 1.966 | 0.061 |
13 | 46.1 | 25.78 | 38.03 | 17.5 | 2.73 | 0.808 | 0.003 |
14 | 56.1 | 83.25 | 78.23 | 41.9 | 2.62 | 2.235 | 0.055 |
15 | 16.1 | 17.52 | 25.85 | 12.2 | 2.69 | 0.546 | 0.01 |
16 | 49 | 25.45 | 48.24 | 24.8 | 2.72 | 0.711 | 0.003 |
17 | 10.7 | 24.53 | 27.22 | 19.6 | 2.69 | 0.713 | 0.007 |
18 | 64 | 78.72 | 75.53 | 39.5 | 2.64 | 2.106 | 0.03 |
19 | 5.7 | 17.35 | 20.34 | 14.25 | 2.66 | 0.494 | 0.006 |
20 | 41.9 | 69.26 | 66.42 | 48.5 | 2.64 | 1.87 | 0.029 |
21 | 9.5 | 18.12 | 21.2 | 14.5 | 2.68 | 0.567 | 0.008 |
22 | 7.6 | 20.23 | 23.62 | 16.8 | 2.69 | 0.64 | 0.007 |
23 | 11 | 20.14 | 22.78 | 16.1 | 2.67 | 0.608 | 0.008 |
24 | 45 | 35.53 | 53.56 | 28.6 | 2.74 | 1.015 | 0.004 |
25 | 8.5 | 20.81 | 25.31 | 18.53 | 2.68 | 0.576 | 0.005 |
26 | 8.6 | 20.12 | 20.82 | 14.8 | 2.67 | 0.599 | 0.007 |
27 | 10.7 | 17.25 | 19.5 | 13.5 | 2.68 | 0.558 | 0.008 |
28 | 8.9 | 21.79 | 24.98 | 19 | 2.68 | 0.654 | 0.007 |
29 | 46.4 | 99.9 | 82.11 | 43.6 | 2.58 | 2.634 | 0.041 |
30 | 9.7 | 17.34 | 20.49 | 14.3 | 2.66 | 0.486 | 0.007 |
31 | 25.9 | 21.23 | 31.18 | 13.2 | 2.72 | 0.609 | 0.005 |
32 | 12.5 | 19.25 | 23.46 | 14.67 | 2.67 | 0.628 | 0.008 |
33 | 8.4 | 19.46 | 22.97 | 17.43 | 2.68 | 0.605 | 0.007 |
34 | 8.1 | 23.28 | 26.8 | 20.36 | 2.68 | 0.707 | 0.011 |
35 | 23.6 | 18.84 | 27.48 | 13.8 | 2.71 | 0.604 | 0.006 |
36 | 63.4 | 73.1 | 68.47 | 35 | 2.61 | 1.933 | 0.028 |
37 | 19 | 18.35 | 23.61 | 13.35 | 2.7 | 0.579 | 0.007 |
38 | 42.5 | 27.28 | 39.99 | 21.74 | 2.72 | 0.789 | 0.003 |
39 | 49.4 | 62.2 | 59.99 | 38.5 | 2.63 | 1.657 | 0.026 |
40 | 23.5 | 21.32 | 32.23 | 16.4 | 2.71 | 0.604 | 0.005 |
41 | 6.1 | 16.97 | 21.01 | 15.87 | 2.66 | 0.556 | 0.007 |
42 | 7.7 | 21.23 | 25.3 | 18.5 | 2.68 | 0.654 | 0.009 |
43 | 9.7 | 18.01 | 20.3 | 14.2 | 2.67 | 0.599 | 0.007 |
44 | 8.5 | 25.49 | 27.49 | 21.32 | 2.67 | 0.723 | 0.008 |
45 | 60.2 | 95.09 | 84.05 | 54.8 | 2.63 | 2.507 | 0.038 |
46 | 40.3 | 20.75 | 40.77 | 18.64 | 2.72 | 0.591 | 0.003 |
47 | 8.4 | 18.25 | 21.08 | 14.5 | 2.69 | 0.592 | 0.008 |
48 | 50.7 | 28.97 | 46.04 | 25.2 | 2.72 | 0.889 | 0.003 |
49 | 8.8 | 17.19 | 19.81 | 14.3 | 2.68 | 0.549 | 0.007 |
50 | 46.6 | 76.77 | 64.83 | 38.17 | 2.63 | 2.023 | 0.025 |
51 | 9.6 | 17.99 | 20.42 | 15 | 2.67 | 0.571 | 0.008 |
52 | 8.6 | 19.9 | 23 | 16.9 | 2.68 | 0.586 | 0.009 |
53 | 9.2 | 17.81 | 21 | 14.3 | 2.68 | 0.506 | 0.01 |
54 | 11.7 | 19.77 | 23.91 | 13.5 | 2.68 | 0.567 | 0.035 |
55 | 9.4 | 17.85 | 20.48 | 14.8 | 2.68 | 0.558 | 0.008 |
56 | 45.1 | 93.19 | 88.93 | 48 | 2.62 | 2.447 | 0.057 |
57 | 46.1 | 70.21 | 65.46 | 33.6 | 2.64 | 1.87 | 0.071 |
58 | 37.4 | 21.13 | 32.44 | 14.2 | 2.71 | 0.642 | 0.003 |
59 | 45.3 | 19.6 | 30.92 | 13.2 | 2.73 | 0.569 | 0.007 |
60 | 19 | 24.55 | 29.08 | 19.6 | 2.68 | 0.707 | 0.017 |
61 | 37.6 | 87.71 | 75.34 | 40.5 | 2.63 | 2.329 | 0.048 |
62 | 8 | 18.05 | 20.99 | 14.3 | 2.68 | 0.595 | 0.01 |
63 | 8.5 | 19.85 | 23.67 | 17.58 | 2.67 | 0.599 | 0.008 |
64 | 9.6 | 18.18 | 22.58 | 16 | 2.68 | 0.567 | 0.006 |
65 | 8.6 | 18.02 | 20.51 | 14.6 | 2.69 | 0.592 | 0.012 |
66 | 8.3 | 18.01 | 21 | 14.2 | 2.67 | 0.599 | 0.007 |
67 | 10.2 | 18.15 | 22.14 | 15.6 | 2.67 | 0.517 | 0.006 |
68 | 8.6 | 24.84 | 29.32 | 22 | 2.68 | 0.752 | 0.012 |
69 | 45.8 | 89.51 | 85.86 | 42.7 | 2.63 | 2.372 | 0.051 |
70 | 38.6 | 22.79 | 35.83 | 15.2 | 2.72 | 0.689 | 0.009 |
71 | 8.2 | 17.12 | 19.7 | 13.8 | 2.67 | 0.571 | 0.01 |
72 | 26.5 | 21.89 | 30.98 | 17.4 | 2.72 | 0.619 | 0.005 |
73 | 24.5 | 18.28 | 28.11 | 12.5 | 2.71 | 0.522 | 0.006 |
74 | 21 | 20.62 | 28.62 | 17.4 | 2.69 | 0.592 | 0.014 |
75 | 9.3 | 21.14 | 23.89 | 18.53 | 2.68 | 0.686 | 0.008 |
76 | 8.4 | 18.02 | 21.1 | 14.5 | 2.67 | 0.552 | 0.009 |
77 | 9.8 | 18.07 | 20.62 | 14.5 | 2.68 | 0.567 | 0.01 |
78 | 30.4 | 22.23 | 39.53 | 18.64 | 2.72 | 0.648 | 0.004 |
79 | 9.8 | 22.03 | 23.92 | 17.8 | 2.68 | 0.644 | 0.008 |
80 | 6.7 | 18.91 | 21.49 | 15 | 2.69 | 0.582 | 0.007 |
81 | 43.4 | 25.6 | 34.5 | 15.6 | 2.73 | 0.717 | 0.005 |
82 | 40.1 | 25.53 | 36.11 | 19.2 | 2.72 | 0.755 | 0.01 |
83 | 8.7 | 15.09 | 18.9 | 12.63 | 2.66 | 0.462 | 0.008 |
84 | 9.4 | 19.64 | 23.8 | 17.2 | 2.67 | 0.648 | 0.009 |
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Dataset | Parameters | Clay Content, CC (%) | Water Content, w (%) | Liquid Limit, LL | Plastic Limit, PL | Specific Density, γ (g/cm3) | Void Ratio, e | Permeability Coefficient, k (×10−9 cm/s) |
---|---|---|---|---|---|---|---|---|
Training | Min | 5.7 | 16.97 | 19.5 | 12.2 | 2.58 | 0.486 | 0.003 |
Mean | 28.056 | 37.82 | 40.219 | 23.882 | 2.6715 | 1.0576 | 0.016 | |
Max | 64 | 99.9 | 88.93 | 54.8 | 2.74 | 2.634 | 0.071 | |
Std. Dev | 19.761 | 28.62 | 22.228 | 12.347 | 0.0413 | 0.7234 | 0.016 | |
Testing | Min | 6.7 | 15.09 | 18.9 | 12.5 | 2.63 | 0.462 | 0.004 |
Mean | 18.36 | 25.75 | 30.304 | 18.279 | 2.6836 | 0.7553 | 0.012 | |
Max | 45.8 | 89.51 | 85.86 | 42.7 | 2.73 | 2.372 | 0.051 | |
Std. Dev | 13.337 | 19.13 | 16.272 | 7.3879 | 0.0256 | 0.4856 | 0.012 |
Model | Optimal Tuning Parameters |
---|---|
PUK kernel | {noise = 0.6, ω = 0.1, σ = 0.1} |
Poly kernel | {noise = 0.02} |
RBF kernel | = 0.6} |
Model | Training | Testing | Reference | ||||||
---|---|---|---|---|---|---|---|---|---|
R | R2 | MAE | RMSE | R | R2 | MAE | RMSE | ||
RF | 0.972 | - | 0.0023 | 0.0035 | 0.851 | - | 0.0049 | 0.0084 | [1] |
ANN | 0.948 | - | 0.0027 | 0.0047 | 0.845 | - | 0.005 | 0.001 | |
SVM | 0.861 | - | 0.0056 | 0.0078 | 0.844 | - | 0.0064 | 0.0098 | |
M5P | - | 0.792 | 0.004 | 0.0064 | - | 0.766 | 0.0045 | 0.0081 | [28] |
GPR (PUK) | 0.9901 | 0.980 | 0.0023 | 0.0038 | 0.9754 | 0.951 | 0.0037 | 0.0062 | Present study |
GPR (Poly kernel) | 0.964 | 0.929 | 0.0028 | 0.0047 | 0.9624 | 0.926 | 0.0223 | 0.0634 | |
GPR (RBF) | 0.9548 | 0.912 | 0.0031 | 0.0048 | 0.9387 | 0.881 | 0.0034 | 0.0047 | |
CatBoost | 0.960 | 0.922 | 0.0031 | 0.0052 | 0.958 | 0.9178 | 0.0013 | 0.0031 |
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Ahmad, M.; Keawsawasvong, S.; Bin Ibrahim, M.R.; Waseem, M.; Kashyzadeh, K.R.; Sabri, M.M.S. Novel Approach to Predicting Soil Permeability Coefficient Using Gaussian Process Regression. Sustainability 2022, 14, 8781. https://0-doi-org.brum.beds.ac.uk/10.3390/su14148781
Ahmad M, Keawsawasvong S, Bin Ibrahim MR, Waseem M, Kashyzadeh KR, Sabri MMS. Novel Approach to Predicting Soil Permeability Coefficient Using Gaussian Process Regression. Sustainability. 2022; 14(14):8781. https://0-doi-org.brum.beds.ac.uk/10.3390/su14148781
Chicago/Turabian StyleAhmad, Mahmood, Suraparb Keawsawasvong, Mohd Rasdan Bin Ibrahim, Muhammad Waseem, Kazem Reza Kashyzadeh, and Mohanad Muayad Sabri Sabri. 2022. "Novel Approach to Predicting Soil Permeability Coefficient Using Gaussian Process Regression" Sustainability 14, no. 14: 8781. https://0-doi-org.brum.beds.ac.uk/10.3390/su14148781