Romulus Costache - Search Results

Year	Number of Results
2018	1
2019	5
2020	4
2021	3

1

Identification of areas prone to flash-flood phenomena using multiple-criteria decision-making, bivariate statistics, machine learning and their ensembles.

Costache R, Tien Bui D. Costache R, et al. Sci Total Environ. 2020 Apr 10;712:136492. doi: 10.1016/j.scitotenv.2019.136492. Epub 2020 Jan 7. Sci Total Environ. 2020. PMID: 31927448

2

Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment.

Costache R, Pham QB, Avand M, Thuy Linh NT, Vojtek M, Vojteková J, Lee S, Khoi DN, Thao Nhi PT, Dung TD. Costache R, et al. J Environ Manage. 2020 Jul 1;265:110485. doi: 10.1016/j.jenvman.2020.110485. Epub 2020 Apr 20. J Environ Manage. 2020. PMID: 32421551

3

Flood susceptibility mapping in Dingnan County (China) using adaptive neuro-fuzzy inference system with biogeography based optimization and imperialistic competitive algorithm.

Wang Y, Hong H, Chen W, Li S, Panahi M, Khosravi K, Shirzadi A, Shahabi H, Panahi S, Costache R. Wang Y, et al. Among authors: costache r. J Environ Manage. 2019 Oct 1;247:712-729. doi: 10.1016/j.jenvman.2019.06.102. Epub 2019 Jul 4. J Environ Manage. 2019. PMID: 31279803

4

A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area.

Tien Bui D, Hoang ND, Martínez-Álvarez F, Ngo PT, Hoa PV, Pham TD, Samui P, Costache R. Tien Bui D, et al. Among authors: costache r. Sci Total Environ. 2020 Jan 20;701:134413. doi: 10.1016/j.scitotenv.2019.134413. Epub 2019 Sep 12. Sci Total Environ. 2020. PMID: 31706212

5

Comparative assessment of the flash-flood potential within small mountain catchments using bivariate statistics and their novel hybrid integration with machine learning models.

Costache R, Hong H, Pham QB. Costache R, et al. Sci Total Environ. 2020 Apr 1;711:134514. doi: 10.1016/j.scitotenv.2019.134514. Epub 2019 Oct 8. Sci Total Environ. 2020. PMID: 31812401

6

Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania.

Costache R, Tien Bui D. Costache R, et al. Sci Total Environ. 2019 Nov 15;691:1098-1118. doi: 10.1016/j.scitotenv.2019.07.197. Epub 2019 Jul 16. Sci Total Environ. 2019. PMID: 31466192

7

Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors.

Costache R, Arabameri A, Blaschke T, Pham QB, Pham BT, Pandey M, Arora A, Linh NTT, Costache I. Costache R, et al. Sensors (Basel). 2021 Jan 4;21(1):280. doi: 10.3390/s21010280. Sensors (Basel). 2021. PMID: 33406613 Free PMC article.

8

Flash-Flood Potential assessment in the upper and middle sector of Prahova river catchment (Romania). A comparative approach between four hybrid models.

Costache R. Costache R. Sci Total Environ. 2019 Apr 1;659:1115-1134. doi: 10.1016/j.scitotenv.2018.12.397. Epub 2018 Dec 27. Sci Total Environ. 2019. PMID: 31096326

9

Predicting the sorption efficiency of heavy metal based on the biochar characteristics, metal sources, and environmental conditions using various novel hybrid machine learning models.

Ke B, Nguyen H, Bui XN, Bui HB, Choi Y, Zhou J, Moayedi H, Costache R, Nguyen-Trang T. Ke B, et al. Among authors: costache r. Chemosphere. 2021 Aug;276:130204. doi: 10.1016/j.chemosphere.2021.130204. Epub 2021 Mar 9. Chemosphere. 2021. PMID: 34088091

10

Flood susceptibility mapping by integrating frequency ratio and index of entropy with multilayer perceptron and classification and regression tree.

Wang Y, Fang Z, Hong H, Costache R, Tang X. Wang Y, et al. Among authors: costache r. J Environ Manage. 2021 Jul 1;289:112449. doi: 10.1016/j.jenvman.2021.112449. Epub 2021 Mar 31. J Environ Manage. 2021. PMID: 33812150

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