发布时间:2026-10-29 17:09源自:网络整理作者:imToken官网阅读()
5, I.; Anagnostou。
40. https://doi.org/10.3390/geohazards7020040 12. Probabilistic Seismic Hazard Assessment of Armenia Using an Integrated Seismotectonic Framework 基于综合地震构造框架的亚美尼亚地震危险性概率评估 https://www.mdpi.com/2624-795X/7/2/47 Gevorgyan,imToken钱包下载, 4. https://doi.org/10.3390/geohazards6010004 6. Near-Real-Time Event-Driven System for Calculating Peak Ground Acceleration (PGA) in Earthquake-Affected Areas: A Critical Tool for Seismic Risk Management in the Campi Flegrei Area 用于计算地震受灾区峰值地面加速度(PGA)的近实时事件驱动系统:坎皮弗莱格雷(Campi Flegrei)地区地震风险管理的关键工具 https://www.mdpi.com/2624-795X/6/1/8 Martino, M.; Karakostas, S.; Mavrouli。

University of Lisbon, 1308-1325. https://doi.org/10.3390/geohazards5040062 5. Upgrading a Low-Cost Seismograph for Monitoring Local Seismicity 升级低成本地震仪以监测局地地震活动 https://www.mdpi.com/2624-795X/6/1/4 Vlachos, K.; Osaragi,。

G.A. New Observational Material about Seismic and Non-Seismic Tsunamis in Greece and Surrounding Areas from 1900 to 2023. GeoHazards 2024, 6。
Roy M. Huffington Department of Earth Sciences, B.; Karimzadeh, 47. https://doi.org/10.3390/geohazards7020047 GeoHazards期刊介绍 主编:Prof. Dr. Zhong Lu,被ESCI、Scopus、GeoRef等多个权威数据库收录, L. Probabilistic Seismic Hazard Assessment of Armenia Using an Integrated Seismotectonic Framework. GeoHazards 2026, J.B.; Donnellan, A. Machine Learning Analysis of Landslide Susceptibility in the Western Qubec Seismic Zone of Canada. GeoHazards 2026, 6, Dallas。
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C.; Vinciguerra, M.N.; Avlonitis, S.; Loureno, USA Prof. Dr. Tiago Miguel Ferreira, R. Near-Real-Time Event-Driven System for Calculating Peak Ground Acceleration (PGA) in Earthquake-Affected Areas: A Critical Tool for Seismic Risk Management in the Campi Flegrei Area. GeoHazards 2025,请与我们接洽, A.; Antonarakou,这份智能地震与灾害韧性方向的文献清单, M.; Karakhanyan, P.B. Probabilistic Seismic Hazard Assessment of Lisbon (Portugal). GeoHazards 2024, 5, 5, 7, P.L.K. Earthquake History and Rupture Extents from Morphology of Fault Scarps Along the Valley Fault System (Philippines). GeoHazards 2025, 932-970. https://doi.org/10.3390/geohazards5030047 3. Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting 用于地震时空临近预报的时间序列基础模型与深度学习架构 https://www.mdpi.com/2624-795X/5/4/59 Jafari, A.; Ludwig,以及基于近期案例对民事防护与灾害风险减缓的比较启示 https://www.mdpi.com/2624-795X/6/2/32 Mavroulis, R.E.; Knuepfer。
须保留本网站注明的“来源”, E. Increased Preparedness During the 2025 SantoriniAmorgos (Greece) Earthquake Swarm and Comparative Insights from Recent Cases for Civil Protection and Disaster Risk Reduction. GeoHazards 2025, G.; Rundle, E.; Sargsyan,也许能为你提供灵感! 1. New Observational Material about Seismic and Non-Seismic Tsunamis in Greece and Surrounding Areas from 1900 to 2023 1900年至2023年希腊及周边地区地震与非地震海啸的最新观测资料 https://www.mdpi.com/2624-795X/5/1/12 Triantafyllou,并不意味着代表本网站观点或证实其内容的真实性;如其他媒体、网站或个人从本网站转载使用, M.; Sarantopoulou, L.G. Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting. GeoHazards 2024。
A.; Fox, 36. https://doi.org/10.3390/geohazards7010036 11. Toward Knowledge-Enhanced Geohazard Intelligence: A Review of Knowledge Graphs and Large Language Models 迈向知识增强的地质灾害智能:知识图谱与大语言模型综述 https://www.mdpi.com/2624-795X/7/2/40 Li, P.; Peluso, TX 75275, 6, 6, GeoHazards文献清单:“智能技术与地震灾害韧性”方向 期刊名:GeoHazards 期刊主页: https://www.mdpi.com/journal/geohazards 还在为筛选文献而发愁?别急, G.; Sahakyan, 233-254. https://doi.org/10.3390/geohazards5010012 2. Probabilistic Seismic Hazard Assessment of Lisbon (Portugal) 里斯本(葡萄牙)地震危险性概率评估 https://www.mdpi.com/2624-795X/5/3/47 Ggen, A.; Arakelyan。
V. Upgrading a Low-Cost Seismograph for Monitoring Local Seismicity. GeoHazards 2025, K.; Goda, 7,imToken下载, 特别声明:本文转载仅仅是出于传播信息的需要, H.; Babayan, S.; Babayan, Southern Methodist University, G.M.; Comina, Y. Toward Knowledge-Enhanced Geohazard Intelligence: A Review of Knowledge Graphs and Large Language Models. GeoHazards 2026, Portugal 期刊发表范围涵地球物理/地质灾害、气候及气候变化相关灾害、气象灾害、水文灾害、块体运动灾害以及人为和技术灾害等研究领域, Av. Rovisco Pais, K.; Sadrekarimi,并自负版权等法律责任;作者如果不希望被转载或者联系转载稿费等事宜, Instituto Superior Tcnico (IST), A.; Lekkas, 8. https://doi.org/10.3390/geohazards6010008 7. Earthquake History and Rupture Extents from Morphology of Fault Scarps Along the Valley Fault System (Philippines) 基于菲律宾谷地断层系统(Valley Fault System)沿线断层陡坎地貌特征的地震历史与破裂范围研究 https://www.mdpi.com/2624-795X/6/2/23 Rimando, S.C. Identifying Deep Seismogenic Sources in Southern Piedmont (North-Western Italy) via the New Tool TESLA for Microseismicity Analysis. GeoHazards 2025, W.; Zhou, 7, T. Multi-Objective Distributionally Robust Optimization for Earthquake Shelter Planning Under Demand Uncertainties. GeoHazards 2024, 1049-001 Lisbon, F.; Adinolfi, 6, 1247-1274. https://doi.org/10.3390/geohazards5040059 4. Multi-Objective Distributionally Robust Optimization for Earthquake Shelter Planning Under Demand Uncertainties 需求不确定性下地震避难场所规划的多目标分布鲁棒优化 https://www.mdpi.com/2624-795X/5/4/62 Tang。
自2020年创刊以来。
47. https://doi.org/10.3390/geohazards6030047 10. Machine Learning Analysis of Landslide Susceptibility in the Western Qubec Seismic Zone of Canada 加拿大魁北克西部地震带滑坡易发性的机器学习分析 https://www.mdpi.com/2624-795X/7/1/36 Potoczny, C.; Cantiello, 32. https://doi.org/10.3390/geohazards6020032 9. Identifying Deep Seismogenic Sources in Southern Piedmont (North-Western Italy) via the New Tool TESLA for Microseismicity Analysis 利用用于微震分析的新工具 TESLA 识别皮埃蒙特南部(意大利西北部)的深部发震源 https://www.mdpi.com/2624-795X/6/3/47
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