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Dieu Tien Bui

Showing results (21-30 of 44) with videos related to

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The Science of the Total Environment|February 11, 2018
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern IranKhabat Khosravi, Binh Thai Pham, Kamran Chapi, et al.
The Science of the Total Environment|June 13, 2020
Identifying sources of dust aerosol using a new framework based on remote sensing and modellingOmid Rahmati, Farnoush Mohammadi, Seid Saeid Ghiasi, et al.
The Science of the Total Environment|September 4, 2020
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, IndiaAman Arora, Alireza Arabameri, Manish Pandey, et al.
The Science of the Total Environment|April 9, 2019
Land subsidence modelling using tree-based machine learning algorithmsOmid Rahmati, Fatemeh Falah, Seyed Amir Naghibi, et al.
Sensors (Basel, Switzerland)|August 2, 2018
Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning AlgorithmsDieu Tien Bui, Himan Shahabi, Ataollah Shirzadi, et al.
The Science of the Total Environment|February 3, 2020
Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithmDieu Tien Bui, Khabat Khosravi, Mahshid Karimi, et al.
The Science of the Total Environment|December 17, 2019
Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, AustraliaOmid Rahmati, Mahdi Panahi, Zahra Kalantari, et al.
The Science of the Total Environment|November 10, 2019
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm areaDieu Tien Bui, Nhat-Duc Hoang, Francisco Martínez-Álvarez, et al.
The Science of the Total Environment|September 16, 2019
Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland AustraliaOmid Rahmati, Fatemeh Falah, Kavina Shaanu Dayal, et al.
Healthcare (Basel, Switzerland)|June 4, 2020
Analysis of Outbreak and Global Impacts of the COVID-19Ishaani Priyadarshini, Pinaki Mohanty, Raghvendra Kumar, et al.
Pageof 5

Showing results (21-30 of 44) with videos related to

Sort By:
Pageof 5
The Science of the Total Environment|February 11, 2018
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern IranKhabat Khosravi, Binh Thai Pham, Kamran Chapi, et al.
The Science of the Total Environment|June 13, 2020
Identifying sources of dust aerosol using a new framework based on remote sensing and modellingOmid Rahmati, Farnoush Mohammadi, Seid Saeid Ghiasi, et al.
The Science of the Total Environment|September 4, 2020
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, IndiaAman Arora, Alireza Arabameri, Manish Pandey, et al.
The Science of the Total Environment|April 9, 2019
Land subsidence modelling using tree-based machine learning algorithmsOmid Rahmati, Fatemeh Falah, Seyed Amir Naghibi, et al.
Sensors (Basel, Switzerland)|August 2, 2018
Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning AlgorithmsDieu Tien Bui, Himan Shahabi, Ataollah Shirzadi, et al.
The Science of the Total Environment|February 3, 2020
Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithmDieu Tien Bui, Khabat Khosravi, Mahshid Karimi, et al.
The Science of the Total Environment|December 17, 2019
Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, AustraliaOmid Rahmati, Mahdi Panahi, Zahra Kalantari, et al.
The Science of the Total Environment|November 10, 2019
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm areaDieu Tien Bui, Nhat-Duc Hoang, Francisco Martínez-Álvarez, et al.
The Science of the Total Environment|September 16, 2019
Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland AustraliaOmid Rahmati, Fatemeh Falah, Kavina Shaanu Dayal, et al.
Healthcare (Basel, Switzerland)|June 4, 2020
Analysis of Outbreak and Global Impacts of the COVID-19Ishaani Priyadarshini, Pinaki Mohanty, Raghvendra Kumar, et al.
Pageof 5