Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Soil Sampling and Analysis of Chemical Properties of Soil
2.3. Stepwise Regression for Input Selection
2.4. Modeling Techniques
2.5. Model Performance Assessing Parameters:
3. Results and Discussion
3.1. Results of MLP-Based Models
3.2. Results of BT-Based Models
3.3. Intercomparison of Applied Models
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | Units | Mean | Minimum | Median | Maximum | SD | CV | Skewness |
---|---|---|---|---|---|---|---|---|
pH | 7.76 | 6.70 | 7.88 | 8.80 | 0.41 | 0.05 | −0.21 | |
C | % | 3.66 | 1.78 | 3.51 | 6.70 | 0.99 | 0.27 | 0.80 |
P | mg kg−1 | 128.97 | 7.00 | 132.85 | 355.20 | 74.94 | 0.58 | 0.44 |
Ca | meq 100g−1 | 0.19 | 0.05 | 0.14 | 0.93 | 0.15 | 0.79 | 3.68 |
Mg | meq 100g−1 | 0.17 | 0.02 | 0.15 | 0.90 | 0.13 | 0.74 | 3.37 |
Co | mg kg−1 | 0.10 | 0.01 | 0.11 | 0.36 | 0.09 | 0.91 | 0.37 |
Cu | mg kg−1 | 0.51 | 0.01 | 0.19 | 12.79 | 1.99 | 3.89 | 5.77 |
Pb | mg kg−1 | 0.23 | 0.01 | 0.15 | 5.83 | 0.70 | 2.98 | 7.68 |
Models | Training | Testing | Validation | ||||
---|---|---|---|---|---|---|---|
Run | CC | RMSE | CC | RMSE | CC | RMSE | |
MLP 2-8-1 | 10 | 0.8676 | 0.0453 | 0.7226 | 0.0416 | 0.4026 | 0.0082 |
MLP 2-5-1 | 10 | 0.8574 | 0.0469 | 0.7107 | 0.0162 | 0.4582 | 0.0070 |
MLP 2-5-1 | 25 | 0.9075 | 0.0383 | 0.7645 | 0.0148 | 0.3138 | 0.0125 |
MLP 2-8-1 | 25 | 0.8547 | 0.0474 | 0.7186 | 0.0193 | 0.5119 | 0.0060 |
MLP 2-6-1 | 25 | 0.8511 | 0.0479 | 0.6662 | 0.0144 | 0.4769 | 0.0070 |
Models | Training | Testing | Validation | ||||
---|---|---|---|---|---|---|---|
Run | CC | RMSE | CC | RMSE | CC | RMSE | |
MLP 2-4-1 | 25 | 0.9407 | 0.0557 | 0.7420 | 0.0878 | 0.6635 | 0.1440 |
MLP 2-10-1 | 25 | 0.9488 | 0.0519 | 0.7366 | 0.0891 | 0.8626 | 0.0943 |
MLP 2-7-1 | 25 | 0.9331 | 0.0591 | 0.7554 | 0.0874 | 0.7883 | 0.0564 |
MLP 2-5-1 | 25 | 0.9372 | 0.0573 | 0.7264 | 0.0901 | 0.6828 | 0.0903 |
MLP 2-9-1 | 25 | 0.9463 | 0.0531 | 0.7393 | 0.0886 | 0.5610 | 0.0686 |
Models | Training | Testing | Validation | ||||
---|---|---|---|---|---|---|---|
Run | CC | RMSE | CC | RMSE | CC | RMSE | |
MLP 2-3-1 | 25 | 0.8561 | 0.0938 | 0.3529 | 0.1078 | 0.7132 | 0.0128 |
MLP 2-5-1 | 25 | 0.8465 | 0.0104 | 0.3490 | 0.1084 | 0.7113 | 0.0142 |
MLP 2-5-1 | 10 | 0.8378 | 0.0243 | 0.3602 | 0.1052 | 0.7119 | 0.0129 |
MLP 2-10-1 | 25 | 0.8562 | 0.0231 | 0.3706 | 0.1071 | 0.7114 | 0.0126 |
MLP 2-10-1 | 10 | 0.8518 | 0.0066 | 0.3563 | 0.1079 | 0.7095 | 0.0137 |
Output | Training | Testing | Validation | |||
---|---|---|---|---|---|---|
CC | RMSE | CC | RMSE | CC | RMSE | |
Co | 0.9159 | 0.0376 | 0.7092 | 0.0455 | 0.9062 | 0.0343 |
Cu | 0.9600 | 0.0478 | 0.8646 | 0.0755 | 0.8539 | 0.0854 |
Pb | 0.8000 | 0.1175 | 0.6450 | 0.0791 | 0.7064 | 0.1000 |
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Kumar, V.; Sihag, P.; Keshavarzi, A.; Pandita, S.; Rodríguez-Seijo, A. Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India. Appl. Sci. 2021, 11, 8362. https://doi.org/10.3390/app11188362
Kumar V, Sihag P, Keshavarzi A, Pandita S, Rodríguez-Seijo A. Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India. Applied Sciences. 2021; 11(18):8362. https://doi.org/10.3390/app11188362
Chicago/Turabian StyleKumar, Vinod, Parveen Sihag, Ali Keshavarzi, Shevita Pandita, and Andrés Rodríguez-Seijo. 2021. "Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India" Applied Sciences 11, no. 18: 8362. https://doi.org/10.3390/app11188362
APA StyleKumar, V., Sihag, P., Keshavarzi, A., Pandita, S., & Rodríguez-Seijo, A. (2021). Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India. Applied Sciences, 11(18), 8362. https://doi.org/10.3390/app11188362