Rahmati O - Search Results

1

Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods.

Rahmati O, Choubin B, Fathabadi A, Coulon F, Soltani E, Shahabi H, Mollaefar E, Tiefenbacher J, Cipullo S, Ahmad BB, Tien Bui D. Rahmati O, et al. Sci Total Environ. 2019 Oct 20;688:855-866. doi: 10.1016/j.scitotenv.2019.06.320. Epub 2019 Jun 21. Sci Total Environ. 2019. PMID: 31255823

2

Application of Dempster-Shafer theory, spatial analysis and remote sensing for groundwater potentiality and nitrate pollution analysis in the semi-arid region of Khuzestan, Iran.

Rahmati O, Melesse AM. Rahmati O, et al. Sci Total Environ. 2016 Oct 15;568:1110-1123. doi: 10.1016/j.scitotenv.2016.06.176. Epub 2016 Jun 26. Sci Total Environ. 2016. PMID: 27358196

3

River suspended sediment modelling using the CART model: A comparative study of machine learning techniques.

Choubin B, Darabi H, Rahmati O, Sajedi-Hosseini F, Kløve B. Choubin B, et al. Among authors: rahmati o. Sci Total Environ. 2018 Feb 15;615:272-281. doi: 10.1016/j.scitotenv.2017.09.293. Epub 2017 Oct 2. Sci Total Environ. 2018. PMID: 28982076

4

How can statistical and artificial intelligence approaches predict piping erosion susceptibility?

Hosseinalizadeh M, Kariminejad N, Rahmati O, Keesstra S, Alinejad M, Mohammadian Behbahani A. Hosseinalizadeh M, et al. Among authors: rahmati o. Sci Total Environ. 2019 Jan 1;646:1554-1566. doi: 10.1016/j.scitotenv.2018.07.396. Epub 2018 Jul 29. Sci Total Environ. 2019. PMID: 30235640

5

Evaluation of watershed health using Fuzzy-ANP approach considering geo-environmental and topo-hydrological criteria.

Alilou H, Rahmati O, Singh VP, Choubin B, Pradhan B, Keesstra S, Ghiasi SS, Sadeghi SH. Alilou H, et al. Among authors: rahmati o. J Environ Manage. 2019 Feb 15;232:22-36. doi: 10.1016/j.jenvman.2018.11.019. Epub 2018 Nov 20. J Environ Manage. 2019. PMID: 30466009

6

Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models.

Azareh A, Rahmati O, Rafiei-Sardooi E, Sankey JB, Lee S, Shahabi H, Ahmad BB. Azareh A, et al. Among authors: rahmati o. Sci Total Environ. 2019 Mar 10;655:684-696. doi: 10.1016/j.scitotenv.2018.11.235. Epub 2018 Nov 17. Sci Total Environ. 2019. PMID: 30476849

7

PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches.

Rahmati O, Kornejady A, Samadi M, Deo RC, Conoscenti C, Lombardo L, Dayal K, Taghizadeh-Mehrjardi R, Pourghasemi HR, Kumar S, Bui DT. Rahmati O, et al. Sci Total Environ. 2019 May 10;664:296-311. doi: 10.1016/j.scitotenv.2019.02.017. Epub 2019 Feb 2. Sci Total Environ. 2019. PMID: 30743123

8

A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination.

Sajedi-Hosseini F, Malekian A, Choubin B, Rahmati O, Cipullo S, Coulon F, Pradhan B. Sajedi-Hosseini F, et al. Among authors: rahmati o. Sci Total Environ. 2018 Dec 10;644:954-962. doi: 10.1016/j.scitotenv.2018.07.054. Epub 2018 Jul 11. Sci Total Environ. 2018. PMID: 30743892

9

Land subsidence modelling using tree-based machine learning algorithms.

Rahmati O, Falah F, Naghibi SA, Biggs T, Soltani M, Deo RC, Cerdà A, Mohammadi F, Tien Bui D. Rahmati O, et al. Sci Total Environ. 2019 Jul 1;672:239-252. doi: 10.1016/j.scitotenv.2019.03.496. Epub 2019 Apr 2. Sci Total Environ. 2019. PMID: 30959291

10

Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia.

Rahmati O, Falah F, Dayal KS, Deo RC, Mohammadi F, Biggs T, Moghaddam DD, Naghibi SA, Bui DT. Rahmati O, et al. Sci Total Environ. 2020 Jan 10;699:134230. doi: 10.1016/j.scitotenv.2019.134230. Epub 2019 Sep 6. Sci Total Environ. 2020. PMID: 31522053

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