Showing results 1 to 20 of 27
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| Issue Date | Title | Author(s) |
| 2020-08-03 | A comparison between three conditioning factors dataset for landslide prediction in the sajadrood catchment of iran | Kalantar, B; Ueda, N; Al-Najjar, HAH; Saeidi, V; Gibril, MBA; Halin, AA |
| 2019-01-01 | Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, Malaysia | Jumaah, HJ; Ameen, MH; Kalantar, B; Rizeei, HM; Jumaah, SJ |
| 2019-04-01 | Application of rotation forest with decision trees as base classifier and a novel ensemble model in spatial modeling of groundwater potential | Naghibi, SA; Dolatkordestani, M; Rezaei, A; Amouzegari, P; Heravi, MT; Kalantar, B; Pradhan, B |
| 2020-11-01 | Assessment of convolutional neural network architectures for earthquake-induced building damage detection based on pre-and post-event orthophoto images | Kalantar, B; Ueda, N; Al-Najjar, HAH; Halin, AA |
| 2018-12-01 | Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN) | Kalantar, B; Pradhan, B; Amir Naghibi, S; Motevalli, A; Mansor, S |
| 2017-05-01 | A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping | Naghibi, SA; Moghaddam, DD; Kalantar, B; Pradhan, B; Kisi, O |
| 2019-01-01 | Conditioning factor determination for mapping and prediction of landslide susceptibility using machine learning algorithms | Al-Najjar, HAH; Kalantar, B; Pradhan, B; Saeidi, V |
| 2019-07 | Conditioning Factors Determination for Landslide Susceptibility Mapping Using Support Vector Machine Learning | Kalantar, B; Ueda, N; Lay, US; Al-Najjar, HAH; Halin, AA |
| 2017-05-04 | Debris flow susceptibility assessment using airborne laser scanning data | Pradhan, B; Kalantar, B; Abdulwahid, WM; Dieu, BT |
| 2017-05-19 | Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis | Kalantar, B; Mansor, SB; Sameen, MI; Pradhan, B; Shafri, HZM |
| 2017-05-04 | Ensemble disagreement active learning for spatial prediction of shallow landslide | Pradhan, B; Sameen, MI; Kalantar, B |
| 2018-01-01 | A geospatial solution using a TOPSIS approach for prioritizing urban projects in Libya | Amazeeq, MSAB; Kalantar, B; Al-Najjar, HAH; Idrees, MO; Pradhan, B; Mansor, S |
| 2017 | GIS-based Groundwater Spring Potential Mapping Using Data Mining Boosted Regression Tree and Probabilistic Frequency Ratio Models in Iran | Mousavi, SM; Golkarian, A; Naghibi, SA; Kalantar, B; Pradhan, B |
| 2019-02-13 | Groundwater potential mapping using a novel data-mining ensemble model | Kordestani, MD; Naghibi, SA; Hashemi, H; Ahmadi, K; Kalantar, B; Pradhan, B |
| 2018-03-01 | Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS | Golkarian, A; Naghibi, SA; Kalantar, B; Pradhan, B |
| 2018-04-01 | Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach | Hong, H; Pradhan, B; Sameen, MI; Kalantar, B; Zhu, A; Chen, W |
| 2019-06-01 | Land cover classification from fused DSM and UAV images using convolutional neural networks | Al-Najjar, HAH; Kalantar, B; Pradhan, B; Saeidi, V; Halin, AA; Ueda, N; Mansor, S |
| 2019-01-01 | Land use and land cover mapping using rule-based classification in Karbala City, Iraq | Ahmed, AA; Kalantar, B; Pradhan, B; Mansor, S; Sameen, MI |
| 2021-08-02 | Landslide susceptibility modeling: An integrated novel method based on machine learning feature transformation | Al-Najjar, HAH; Pradhan, B; Kalantar, B; Sameen, MI; Santosh, M; Alamri, A |
| 2017-09-12 | Modelling mean albedo of individual roofs in complex urban areas using satellite images and airborne laser scanning point clouds | Kalantar, B; Mansor, S; Khuzaimah, Z; Sameen, MI; Pradhan, B |
