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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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| 1 |
Material Type: Article
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GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of IranRemote sensing (Basel, Switzerland), 2020-08, Vol.12 (15), p.2478 [Peer Reviewed Journal]2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12152478Full text available |
| 2 |
Material Type: Article
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Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithmsStochastic environmental research and risk assessment, 2020-12, Vol.34 (12), p.2277-2300 [Peer Reviewed Journal]Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 1436-3240 ;EISSN: 1436-3259 ;DOI: 10.1007/s00477-020-01862-5Full text available |
| 3 |
Material Type: Article
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A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, AustraliaSensors (Basel, Switzerland), 2019-11, Vol.19 (22), p.4893 [Peer Reviewed Journal]2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s19224893 ;PMID: 31717546Full text available |
| 4 |
Material Type: Article
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GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility AssessmentWater (Basel), 2020-03, Vol.12 (3), p.683 [Peer Reviewed Journal]ISSN: 2073-4441 ;EISSN: 2073-4441 ;DOI: 10.3390/w12030683Full text available |
| 5 |
Material Type: Article
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A tree-based intelligence ensemble approach for spatial prediction of potential groundwaterInternational journal of digital earth, 2020-12, Vol.13 (12), p.1408-1429 [Peer Reviewed Journal]ISSN: 1753-8947 ;EISSN: 1753-8955 ;DOI: 10.1080/17538947.2020.1718785Digital Resources/Online E-Resources |
| 6 |
Material Type: Article
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Flood susceptibility mapping using an improved analytic network process with statistical modelsGeomatics, natural hazards and risk, 2020-01, Vol.11 (1), p.2282-2314 [Peer Reviewed Journal]2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2020 ;2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1947-5705 ;EISSN: 1947-5713 ;DOI: 10.1080/19475705.2020.1836036Full text available |
| 7 |
Material Type: Article
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Earthquake Vulnerability Mapping Using Different Hybrid ModelsSymmetry (Basel), 2020-03, Vol.12 (3), p.405 [Peer Reviewed Journal]2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2073-8994 ;EISSN: 2073-8994 ;DOI: 10.3390/sym12030405Full text available |
| 8 |
Material Type: Article
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Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential MappingApplied sciences, 2020-04, Vol.10 (7), p.2469 [Peer Reviewed Journal]ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app10072469Full text available |
| 9 |
Material Type: Article
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A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility MappingWater (Basel), 2019-10, Vol.11 (10), p.2076 [Peer Reviewed Journal]2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2073-4441 ;EISSN: 2073-4441 ;DOI: 10.3390/w11102076Full text available |
| 10 |
Material Type: Article
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Spatial Prediction of Future Flood Risk: An Approach to the Effects of Climate ChangeGeosciences (Basel), 2021-01, Vol.11 (1), p.25 [Peer Reviewed Journal]ISSN: 2076-3263 ;EISSN: 2076-3263 ;DOI: 10.3390/geosciences11010025Full text available |
| 11 |
Material Type: Article
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Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and PredictionSymmetry (Basel), 2020-06, Vol.12 (6), p.1022 [Peer Reviewed Journal]2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2073-8994 ;EISSN: 2073-8994 ;DOI: 10.3390/sym12061022Full text available |
| 12 |
Material Type: Article
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Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of IranForests, 2020-04, Vol.11 (4), p.421 [Peer Reviewed Journal]ISSN: 1999-4907 ;EISSN: 1999-4907 ;DOI: 10.3390/f11040421Full text available |
| 13 |
Material Type: Article
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GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining ModelsApplied sciences, 2020-03, Vol.10 (6), p.2039 [Peer Reviewed Journal]ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app10062039Full text available |
| 14 |
Material Type: Article
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Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst WatershedWater (Basel), 2021-09, Vol.13 (18), p.2540 [Peer Reviewed Journal]2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2073-4441 ;EISSN: 2073-4441 ;DOI: 10.3390/w13182540Full text available |
| 15 |
Material Type: Article
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Improving Voting Feature Intervals for Spatial Prediction of LandslidesMathematical problems in engineering, 2020-10, Vol.2020, p.1-15 [Peer Reviewed Journal]Copyright © 2020 Binh Thai Pham et al. ;COPYRIGHT 2020 Hindawi Limited ;Copyright © 2020 Binh Thai Pham et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;ISSN: 1024-123X ;ISSN: 1563-5147 ;EISSN: 1563-5147 ;DOI: 10.1155/2020/4310791Full text available |
| 16 |
Material Type: Article
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Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, IranSustainability, 2019-10, Vol.11 (19), p.5426 [Peer Reviewed Journal]2019. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2071-1050 ;EISSN: 2071-1050 ;DOI: 10.3390/su11195426Full text available |
| 17 |
Material Type: Article
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A New Approach for Smart Soil Erosion Modeling: Integration of Empirical and Machine-Learning ModelsEnvironmental modeling & assessment, 2023-02, Vol.28 (1), p.145-160 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;COPYRIGHT 2023 Springer ;ISSN: 1420-2026 ;EISSN: 1573-2967 ;DOI: 10.1007/s10666-022-09858-xFull text available |
| 18 |
Material Type: Article
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New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mappingHydrological sciences journal, 2020-12, Vol.65 (16), p.2816-2837 [Peer Reviewed Journal]2020 IAHS 2020 ;2020 IAHS ;ISSN: 0262-6667 ;EISSN: 2150-3435 ;DOI: 10.1080/02626667.2020.1842412Full text available |
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