Influence of soil salinity on the bearing capacity of the frozen wall

Autor: Mikhail Semin, Lev Levin, Sergey Bublik, Andrey Brovka, Ivan Dedyulya

Publikováno v: Frattura ed Integrità Strutturale, Vol 18, Iss 69, Pp 106-114 (2024)

The article describes the results of laboratory studies on the unfrozen water content and ultimate long-term strength of frozen clay and chalk samples in the temperature range from -10 to -25 �C. The soil samples contained dissolved salt in the por

Externí odkaz: https://doaj.org/article/18caee699c054dc89f77b510fd9eb72a

Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region

Autor: Neeraj Dhanraj Bokde, Zainab Hasan Ali, Maysam Th. Al-Hadidi, Aitazaz Ahsan Farooque, Mehdi Jamei, Ali Abdulridha Al Maliki, Beste Hamiye Beyaztas, Hossam Faris, Zaher Mundher Yaseen

Publikováno v: IEEE Access, Vol 9, Pp 53617-53635 (2021)

Quantification of the soil physicochemical properties is one of the essential process in the field of soil geo-science. In the current research, three types of machine learning (ML) models including support vector machine (SVM), random forest (RF), a

Externí odkaz: https://doaj.org/article/a5e24a91168745989f03ebd263c9d3b6

CALICUM, Mg AND Na RELEASE KINETICS FROM SALINE- SODIC SOIL MIXED WITH SOME AMENDMENTS

Autor: Al-Hadethi & Al-Alwani

Publikováno v: The Iraqi Journal of Agricultural science, Vol 51, Iss 6 (2020)

This study was aimed to investigate the effect of phosphogypsum and humic acids on the leaching and releasing of salts from saline- sodic soil. A laboratory experiment was conducted in polyethylene columns (60.0 cm and 7.1 cm). The columns were fille

Externí odkaz: https://doaj.org/article/25dac1856dd243518e804ddf94d0066d

Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region

Autor: Hossam Faris, Maysam Th. Al-Hadidi, Mehdi Jamei, Zainab Hasan Ali, Zaher Mundher Yaseen, Neeraj Dhanraj Bokde, Aitazaz A. Farooque, Beste Hamiye Beyaztas, Ali Al Maliki

Publikováno v: IEEE Access, Vol 9, Pp 53617-53635 (2021)
Bokde, N, Hasan Ali, Z, Th. Al-Hadidi, M, Ahsan Farooque, A, Jamei, M, Abdulridha Al Maliki, A, Hamiye Beyaztas, B, Faris, H & Mundher Yaseen, Z 2021, ' Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region ', IEEE Access, vol. 9, pp. 53617-53635 . https://doi.org/10.1109/ACCESS.2021.3071015

Quantification of the soil physicochemical properties is one of the essential process in the field of soil geo-science. In the current research, three types of machine learning (ML) models including support vector machine (SVM), random forest (RF), a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3102edb01074617bc8cf0eda3c3046c4
https://avesis.deu.edu.tr/publication/details/f1f61381-550b-4114-93a7-b4f2a6a02c94/oai

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