Determining the Features Influencing the Structural Stability of Soils of Arid Regions Using a Hybrid GA-ANN Algorithm

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Kouchami Sardoo Iraj; Shirani Hosein; Esfandiarpour Boroujeni Isa; BESALATPOUR ALI ASGHAR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: APPLIED SOIL RESEARCH Year:2020 | Volume:8 | Issue:3 Page(s): 129-143

Download Full-Text

Persian Verion

View:

260

Download:

Cites:

Information Journal Paper

Title

Determining the Features Influencing the Structural Stability of Soils of Arid Regions Using a Hybrid GA-ANN Algorithm

Author(s)

Kouchami Sardoo Iraj | Shirani Hosein | Esfandiarpour Boroujeni Isa | BESALATPOUR ALI ASGHAR | Issue Writer Certificate

Keywords

OptimizationQ2

mean weight diameterQ2

multiple linear regressionQ1

sensitivity analysisQ2

Abstract

Aggregate stability of soils informs about their relative strengths against erosive forces and mechanical disruption. In this research, a hybrid Genetic Algorithm-Artificial Neural Network method was used to select the best subset of features affecting the mean weight diameter (MWD. In addition, the ability of ANNs and multiple linear regression (MLR) for quantifying the relationship between the MWD index and some soil properties was assessed. After the modeling process, the importance of the selected features in relation to spatial variability of aggregate stability was investigated. In order to prepare a suitable data set; MWD index and some soil features were measured in collected soils from 90 sampling points. Feature selection results showed that six soil features including clay, sand, organic matter, calcium carbonate, electrical conductivity, and sodium adsorption ratio had the greatest effect on the aggregates stability of the studied soils. According to the MWD modeling results, the obtained values of coefficient of determination (R2), mean absolute error percentage (MAEP), and root mean square error (RMSE) for the ANN model performance were 0. 94, 21. 39, and 0. 07% respectively. These findings indicated that the developed ANN model was able to predict the complex and nonlinear relationships between the MWD index and the soil properties selected by the algorithm. Based on the sensitivity analysis results, calcium carbonate equivalent, sand particles, and organic matter were identified as key factors in estimating aggregate stability. Overall, this study provides a robust framework for the prediction of aggregate stability and identifying the most determinant parameters influencing it in arid and semi-arid soils that could be applied to other regions with similar challenges...

Cites

No record.

References

No record.

Cite

APA: Copy

Kouchami Sardoo, Iraj, Shirani, Hosein, Esfandiarpour Boroujeni, Isa, & BESALATPOUR, ALI ASGHAR. (2020). Determining the Features Influencing the Structural Stability of Soils of Arid Regions Using a Hybrid GA-ANN Algorithm. APPLIED SOIL RESEARCH, 8(3 ), 129-143. SID. https://sid.ir/paper/390323/en

Vancouver: Copy

Kouchami Sardoo Iraj, Shirani Hosein, Esfandiarpour Boroujeni Isa, BESALATPOUR ALI ASGHAR. Determining the Features Influencing the Structural Stability of Soils of Arid Regions Using a Hybrid GA-ANN Algorithm. APPLIED SOIL RESEARCH[Internet]. 2020;8(3 ):129-143. Available from: https://sid.ir/paper/390323/en

IEEE: Copy

Iraj Kouchami Sardoo, Hosein Shirani, Isa Esfandiarpour Boroujeni, and ALI ASGHAR BESALATPOUR, “Determining the Features Influencing the Structural Stability of Soils of Arid Regions Using a Hybrid GA-ANN Algorithm,” APPLIED SOIL RESEARCH, vol. 8, no. 3 , pp. 129–143, 2020, [Online]. Available: https://sid.ir/paper/390323/en

Related Journal Papers