首页|Researcher at Guangdong Ocean University Targets Artificial Intelligence (A Comp rehensive Review of Assessing Storm Surge Disasters: From Traditional Statistica l Methods to Artificial Intelligence-Based Techniques)

Researcher at Guangdong Ocean University Targets Artificial Intelligence (A Comp rehensive Review of Assessing Storm Surge Disasters: From Traditional Statistica l Methods to Artificial Intelligence-Based Techniques)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news originating from Zhanjiang, People's R epublic of China, by NewsRx correspondents, research stated, "In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increas ingly significant." Funders for this research include National Key Research And Development Program of China; National Natural Science Foundation of China; Innovative Team Plan For Department of Education of Guangdong Province; Guangdong Science And Technology Plan Project; Independent Research Project of Southern Ocean Laboratory; Guangd ong Ocean University Scientific Research Program. Our news correspondents obtained a quote from the research from Guangdong Ocean University: "However, due to differences in geography, climate, and other condit ions among the affected areas, a single method for assessing the risk of storm s urge disasters cannot be fully applicable to all regions. To address this issue, an increasing number of new methods and models are being applied in the field o f storm surge disaster risk assessment. This paper introduces representative tra ditional statistical methods, numerical simulation methods, and artificial intel ligence-based techniques in this field."

Guangdong Ocean UniversityZhanjiangP eople's Republic of ChinaAsiaArtificial IntelligenceEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Apr.1)