Aligarh Muslim University

本机构学者在这里署名、按本站篇数

合作机构同一篇文章里的其他机构

1. Thu Dau Mot University3
2. Indian Institute of Technology Roorkee印度2
3. University of Kashmir印度2
4. Institut Supérieur des Études Technologiques de Nabeul突尼斯2
5. HUTECH University2
6. Tongji University中国2
7. King Saud University沙特阿拉伯1
8. The University of Queensland澳大利亚1

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逐年被引

最新文献

1. 1
   Prevalence and Antimicrobial Resistance of Campylobacter jejuni in Raw Fish Meat and Retail Fish Market Environments in Bareilly, India: Implications for Food Safety From a One Health Surveillance PerspectiveJournal of Food Safety20260
2. 2
   Landslide susceptibility mapping and kinematic analysis in Bachchangad catchment, Uttarakhand, India: a comparative study using machine learning benchmark classifiersNatural Hazards20261
3. 3
   Assessment of the major biochemical and physiological mechanisms underlying green-synthesised selenium nanoparticles-mediated alleviation of lanthanum toxicity in mung bean (Vigna radiata L.)Journal of Hazardous Materials202512
4. 4
   Landslide susceptibility analysis and hazard zonation of Koh-e-Suleman range using weighted overlay techniqueGeomatics, Natural Hazards and Risk20240
5. 5
   Beyond the banks and deluge: understanding riverscape, flood vulnerability, and responses in kashmirNatural Hazards202414
6. 6
   Trace elements in the Upper Indus River Basin (UIRB) of Western Himalayas: Quantification, sources modeling, and impactsJournal of Hazardous Materials202425
7. 7
   Unveiling extensive and intensive disaster risks: an in-depth analysis of Asia’s vulnerabilityEnvironmental Hazards20242
8. 8
   Preparing for the unthinkable: A systematic look at disaster preparedness in librariesInternational Journal of Disaster Risk Reduction202410
9. 9
   Flood potential mapping by integrating the bivariate statistics, multi-criteria decision-making, and machine learning techniquesStochastic Environmental Research and Risk Assessment202215
10. 10
    An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, IndiaNatural Hazards202266

高被引文献

1. 1
   A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mappingGeomatics, Natural Hazards and Risk2021149
2. 2
   Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, ChinaNatural Hazards201971
3. 3
   An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, IndiaNatural Hazards202266
4. 4
   Optimization and estimation in system reliability allocation problemReliability Engineering & System Safety202164
5. 5
   Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approachNatural Hazards202241
6. 6
   Geotechnical assessment of cut slopes in the landslide-prone Himalayas: rock mass characterization and simulation approachNatural Hazards202041
7. 7
   Trace elements in the Upper Indus River Basin (UIRB) of Western Himalayas: Quantification, sources modeling, and impactsJournal of Hazardous Materials202425
8. 8
   Flood potential mapping by integrating the bivariate statistics, multi-criteria decision-making, and machine learning techniquesStochastic Environmental Research and Risk Assessment202215
9. 9
   Beyond the banks and deluge: understanding riverscape, flood vulnerability, and responses in kashmirNatural Hazards202414
10. 10
    Retracing Realistic Disaster Scenarios from Archival Sources: A Key Tool for Disaster Risk ReductionInternational Journal of Disaster Risk Science202112

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