Evaluating seismic risk in small and medium-sized cities with the modified vulnerability index method, a case study in Jiangyou City, China

Hao, Zheng; Guo, Lanlan; Liu, Jifu; Tao, Zheng; Deng, Zhifei

doi:10.1007/s10518-019-00757-3

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…Most of the vulnerability models for buildings estimate building behaviors with given earthquake intensity based on historical records or experimental results. The structural system is generally considered by almost all research since the building structure controls the seismic resistance of the building aggregate (Zheng et al, 2019). Several other indices related to structures are also taken into account frequently, such as building height/number of stories, building age, building standard, and plan irregularity (Coskun et al, 2019;Zhang, Hsu, et al, 2019).…”

Section: Vulnerability Model Of Assetsmentioning

confidence: 99%

“…Several other indices related to structures are also taken into account frequently, such as building height/number of stories, building age, building standard, and plan irregularity (Coskun et al, 2019;Zhang, Hsu, et al, 2019). Some features of surrounding environments are also included in some vulnerability models, for example, soil condition, slope, distance to active faults, and the angle between building and fault Coskun et al, 2019;Zheng et al, 2019).…”

Section: Vulnerability Model Of Assetsmentioning

confidence: 99%

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System vulnerability modeling and assessment in seismic-prone areas using machine learning

Chen¹

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Earthquakes have caused great social and economic losses to human societies in recent years. Vulnerability modeling and assessment are important measurements for seismic risk mitigation. Conventional seismic vulnerability analysis frameworks have limitations such as subjectivity, low capacity of index information, or high computation cost. The motivation of this thesis is to overcome these drawbacks by employing machine learning techniques. In this thesis, a machine learning-based seismic vulnerability management framework is proposed. The proposed framework is composed of four objectives: Objective 1 aims to assess the regional seismic vulnerability with the information fusion approach. Objective 2 aims to assess the building vulnerability by XGBoost models learned from earthquake building damage data. Objective 3 aims to predict the casualty rate and economic loss of earthquake disaster areas with AutoML models. Objective 4 aims to explore the effective emergency response plans of hospital networks by Multi-objective optimization.12

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Section: Vulnerability Model Of Assetsmentioning

confidence: 99%

Section: Vulnerability Model Of Assetsmentioning

confidence: 99%

System vulnerability modeling and assessment in seismic-prone areas using machine learning

Chen¹

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Urban Geology for the Enhancement of the Hypogean Geosites: the Perugia Underground (Central Italy)

et al. 2021

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Urban geology analyses natural risks and promotes geoheritage in urban areas. In the cities, characterized by a high cultural value, the hypogean artificial cavities, often present in the downtown, offer a unique opportunity to show the geological substratum. Moreover, these places could be a point of interest in urban trekking with the abiotic component of the landscape as a topic (geotourism). To investigate these areas, rigorous bibliographic research and a geomorphological assessment are the first steps, but, besides, non-invasive methods are new techniques increasingly in demand. In this paper, we present a multidisciplinary study on the Etruscan Well (third century B.C.), one of the most important Etruscan artefacts in Perugia (Umbria region, Central Italy). The characteristics of the sedimentary deposits outcropping along the perimeter walls have been collected. Moreover, to show the underground geoheritage, we provide a 3D model of the well and the surrounding area integrating a georeferenced laser scanner survey with ground-penetrating radar prospecting. We aim to obtain a tridimensional mapping of accessible internal rooms to depict the geological characteristics of the Etruscan Well, also revealing a surrounding network of buried galleries. The results are not only a meaningful advancement in the archaeological, geological and historical knowledge of the downtown of Perugia but are a hint for the geoheritage promotion and dissemination, providing images and 3D reconstruction of underground areas.

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Vulnerability assessment of cities to earthquake based on the catastrophe theory: a case study of Tabriz city, Iran

2020

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Evaluating seismic risk in small and medium-sized cities with the modified vulnerability index method, a case study in Jiangyou City, China

Cited by 5 publications

References 17 publications

System vulnerability modeling and assessment in seismic-prone areas using machine learning

System vulnerability modeling and assessment in seismic-prone areas using machine learning

Urban Geology for the Enhancement of the Hypogean Geosites: the Perugia Underground (Central Italy)

Vulnerability assessment of cities to earthquake based on the catastrophe theory: a case study of Tabriz city, Iran

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