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Py学习  »  机器学习算法

AOGS摘要征集|数据驱动和机器学习方法在灾害风险减缓和缓解中的应用

Hydro90 • 1 年前 • 244 次点击  


Dear Colleagues,

    We would like to invite you to submit contributions to the session on “AS43-Application of data-driven and machine learning approaches in disaster risk reduction and mitigation” at AOGS 20th Annual Meeting, which will take place in Singapore, between July 30 and Aug 4, 2023.

AS43- Application of data-driven and machine learning approaches in disaster risk reduction and mitigation

Convener: Dr Kelvin Ng; Co-conveners: Prof. Zhan Tian, Prof. Gregor C. Leckebusch

Session details:

Reducing the impact of extreme meteorological and hydrological events, such as tropical cyclone and extreme Mei-yu precipitation, has been an active research area for the recent years. However, it remains challenging due to the complexity of the physical processing which would result in extreme events. In recent years, data-driven and machine learning approaches have been widely applied to study extreme events as well as improvement in forecasting these extreme events. This in turn improve the societal capacity in mitigating the impact of extreme events. This session focuses on advances in applied data-driven and machine learning approaches in meteorological and hydrological extremes in the context of disaster risk reduction and mitigation. This session also welcomes contributions, which employed hybrid (i.e., machine learning and process-based model) approaches, in the context of disaster risk reduction and mitigation.


Details of the conference can be found here:

https://www.asiaoceania.org/aogs2023/public.asp?page=home.asp


Details of how to submit can be found here:

https://www.asiaoceania.org/aogs2023/public.asp?page=submit_abstracts.asp


We hope to see you in Singapore!

Best,

Kelvin, Zhan, Gregor

Dr. Kelvin S. Ng




会议邀请


    欢迎大家来参加2023年7月30日至8月4日在新加坡举行的AS43 -“数据驱动和机器学习方法在灾害风险减缓和缓解中的应用”会议,摘要投递日期截止2023年2月14日。各种极端的气象和水文事件,如热带气旋和极端的梅雨降雨,对我们的日常生活带来不小的影响,比如洪水、滑坡,多种灾害等。但是,由于极端事件发生的物理过程十分复杂,想要有效预测和减缓灾害还是一项挑战。近年来,数据驱动和机器学习技术不断深入发展,已被广泛用于研究极端事件和改善预测,进而提高社会减灾的能力。本次会议将围绕应用数据驱动和机器学习方法在气象和水文灾害减缓和缓解领域进行深入探讨,欢迎投稿者就基于机器学习和模型相结合的方式在灾害风险减缓和缓解上进行研究分享。


更多关于此次会议的信息,请访问

https://www.asiaoceania.org/aogs2023/public.asp?page=home.asp

了解如何提交稿件详见

https://www.asiaoceania.org/aogs2023/public.asp?page=submit_abstracts.asp


期待您的参与!

Kelvin, Zhan, Gregor Kelvin S. Ng

博士 研究员 伯明翰大学 地理、地球与环境科学学院

英国伯明翰市Edgbaston B15 2TT

k.s.ng@bham.ac.uk

编辑:陈雅静 | 校稿:周旭东

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244 次点击