Mosalla Tabari, M., Ebadi, H., & Alizadeh Zakaria, Z. (2025). PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau). Earth Science Informatics, 18(2). https://doi.org/10.1007/s12145-025-01719-x

MOSALLA TABARI, Maedeh, EBADI, Hamid und ALIZADEH ZAKARIA, Zahra, 2025. PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau). Earth Science Informatics. 1 Februar 2025. Vol. 18, no. 2, . DOI 10.1007/s12145-025-01719-x.

Mosalla Tabari, M., H. Ebadi, und Z. Alizadeh Zakaria. „PSO-Random Forest Approach to Enhance Flood-Prone Area Identification: Using Ground and Remote Sensing Data (case Study: Ottawa-Gatineau)“. Earth Science Informatics, Bd. 18, Nr. 2, Februar 2025, https://doi.org/10.1007/s12145-025-01719-x.

Mosalla Tabari, Maedeh/Ebadi, Hamid/Alizadeh Zakaria, Zahra: PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau), Earth Science Informatics 2025,

Mosalla Tabari, M., Ebadi, H. und Alizadeh Zakaria, Z. (2025), „PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau)“, Earth Science Informatics, Vol. 18 No. 2, verfügbar unter:https://doi.org/10.1007/s12145-025-01719-x.