Advances and Applications of Artificial Intelligence and Numerical Simulation in Risk Emergency Management and Treatment, volume II

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Yunhui Zhang

Southwest Jiaotong University

Yihuai Zhang

University of Glasgow

Long Yan

Central South University

Lei Xia

KU ⁯Leuven

Chengyi Pu

Central University of Finance and Economics

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This Research Topic is Volume II of a series. The previous volume can be found here: Advances and Applications of Artificial Intelligence and Numerical Simulation in Risk Emergency Management and Treatment

Our world is composed of multidimensional and multifaceted risks. In general, geological, environmental, and ecological risks would exist in both natural and engineering situations, such as karst desertification, water inrush, rock burst, debris flow, and landslide. These risks have great safety threats to human survival. In this regard, risk emergency management and treatment (REMT) has become a pivotal topic addressing the national governance system and its governance capacity. It underlines how to prevent and resolve grand security risks, to timely respond to all kinds of disasters and accidents, as well as to safeguard people’s lives and property and social stability.

Qualitative and semi-qualitative analyses were often conducted in the REMT, as they failed to yield robust results due to massive data obtained from field monitoring and laboratory experiments. With the notable progress of intelligent and informative technologies, artificial intelligence and numerical simulation have been successfully employed in the REMT. To explore the advancements of risk mechanisms, assessments, and treatments performed by artificial intelligence and numerical simulation, we invite authors to contribute Original Research of constructive, conceptual, experimental, empirical, theoretical, or practical studies to this Research Topic, in particular the interdisciplinary approaches between natural and social sciences. New Technical Notes are also welcome.

Potential topics include, but are not limited to:

• Deep learning in risk big-data analysis
• Spatial-temporal mathematical models for risk real-timing monitoring
• Applications of artificial intelligence in the risk forecasting
• Risk early-warning models by artificial intelligence
• Remote sensing and geophysical exploration applied in risk assessment
• Numerical simulation of risk treatment in various situation
• Optimizing decision-making in the REMT
• Case studies in engineering challenges, e.g. geohazards in geological engineering

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Editors

Yunhui Zhang

Southwest Jiaotong University

Yihuai Zhang

University of Glasgow

Long Yan

Central South University

Lei Xia

KU ⁯Leuven

Chengyi Pu

Central University of Finance and Economics

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Published In

Frontiers in Earth Science

Environmental Informatics and Remote Sensing

Frontiers in Environmental Science

Environmental Informatics and Remote Sensing

Frontiers in Ecology and Evolution

Environmental Informatics and Remote Sensing

Frontiers in Marine Science

Environmental Informatics and Remote Sensing

Frontiers in ICT

Environmental Informatics and Remote Sensing

Frontiers in Applied Mathematics and Statistics

Environmental Informatics and Remote Sensing

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