International University of Business Agriculture and Technology

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. King Fahd University of Petroleum and Minerals沙特阿拉伯2
2. Chungbuk National University韩国1
3. Kyoto University日本1
4. Sichuan Vocational College of Cultural Industries中国1
5. International Centre for Integrated Mountain Development尼泊尔1
6. University of Central Florida美国1
7. Chengdu University中国1
8. Hiroshima University日本1

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最新文献

1. 1
   The role of artificial intelligence in predicting readmission risk in emergency patients: An umbrella reviewInternational Emergency Nursing20260
2. 2
   Compound multi-hazard assessment under CMIP6 climate scenarios: tracking seasonal flood-landslide and drought-fire interactions across NepalNatural Hazards20260
3. 3
   Scenario-driven data fusion for compound coastal flood risk and exposure assessment using night-time lights in JeddahGeomatics, Natural Hazards and Risk20262
4. 4
   Deciphering proteomic mechanisms explaining the role of glutathione as an aid in improving plant fitness and tolerance against cadmium-toxicity in Brassica napus L.Journal of Hazardous Materials202435
5. 5
   Resilience and recovery: A systematic review of tourism governance strategies in disaster-affected regionsInternational Journal of Disaster Risk Reduction202485
6. 6
   How do multiple kernel functions in machine learning algorithms improve precision in flood probability mapping?Natural Hazards202225
7. 7
   Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirementsAccident Analysis & Prevention2019157

高被引文献

1. 1
   Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirementsAccident Analysis & Prevention2019157
2. 2
   Resilience and recovery: A systematic review of tourism governance strategies in disaster-affected regionsInternational Journal of Disaster Risk Reduction202485
3. 3
   Deciphering proteomic mechanisms explaining the role of glutathione as an aid in improving plant fitness and tolerance against cadmium-toxicity in Brassica napus L.Journal of Hazardous Materials202435
4. 4
   How do multiple kernel functions in machine learning algorithms improve precision in flood probability mapping?Natural Hazards202225
5. 5
   Scenario-driven data fusion for compound coastal flood risk and exposure assessment using night-time lights in JeddahGeomatics, Natural Hazards and Risk20262

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