Economic Analysis for Collapse Hazard Areas

Heo, Bo-Young; Heo, W.

doi:10.3390/app7070693

Cited by 2 publications

(2 citation statements)

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“…The vulnerability assessment methods used in the natural hazards field can be broadly classified into four categories: (1) historical hazard statistics (Heo and Heo 2017;Malmin 2021) ; (2) evaluation indicator systems (Wen and Yang 2016;Salazar et al 2021;Seonyoung and Seokhoon 2022); (3) hazard loss curves (Rossi et al 2012;Wen et al 2018); and (4) machine learning methods (Chen et al 2020;Yacine et al 2021;Li et al 2022;Mangukiya and Sharma 2022;Taromideh et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Vulnerability Assessment Method for Immovable Cultural Relics Based on Artificial Neural Networks—An Example of a Heavy Rainfall Event in Henan Province

Gong

Liu

et al. 2022

Int J Disaster Risk Sci

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Cultural relic conservation capability is an important issue in cultural relic conservation research, and it is critical to decrease the vulnerability of immovable cultural relics to rainfall hazards. Commonly used vulnerability assessment methods are subjective, are mostly applied to regional conditions, and cannot accurately assess the vulnerability of cultural relics. In addition, it is impossible to predict the future vulnerability of cultural relics. Therefore, this study proposed a machine learning-based vulnerability assessment method that not only can assess cultural relics individually but also predict the vulnerability of cultural relics under different rainfall hazard intensities. An extreme rainfall event in Henan Province in 2021 was selected as an example, with a survey report on the damage to cultural relics as a database. The results imply that the back propagation (BP) neural network-based method of assessing the vulnerability of immovable cultural relics is reliable, with an accuracy rate higher than 92%. Based on this model to predict the vulnerability of Zhengzhou City’s cultural relics, the vulnerability levels of cultural relics under different recurrence periods of heavy rainfall were obtained. Among them, the vulnerability of ancient sites is higher than those of other cultural relic types. The assessment model used in this study is suitable for predicting the vulnerability of immovable cultural relics to heavy rainfall hazards and can provide a technical means for cultural relic conservation studies.

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Section: Introductionmentioning

confidence: 99%

Vulnerability Assessment Method for Immovable Cultural Relics Based on Artificial Neural Networks—An Example of a Heavy Rainfall Event in Henan Province

Gong

Liu

et al. 2022

Int J Disaster Risk Sci

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“…Analysis of the current status of the various environments and causes of fire in domestic buildings has proven that it is necessary to build a sustainable and cost-effective [9] AR-based Smart Building Disaster Management System that will be adapted for various environmental factors. In this paper, an AR-based smart building and town disaster management system that provides information visualization and an optimal guide for quick initial response during about 5 min using smart element AR-based disaster management service system is proposed.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure

Park

et al. 2018

Applied Sciences

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Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it is necessary to take appropriate action accordingly. There has been an increasing effort to develop such disaster management systems worldwide by applying information communication technology (ICT), and many studies have been conducted in practice. In this paper, an augmented reality (AR)-based Smart Building and Town Disaster Management System is suggested in order to acquire visibility and to grasp occupants in case of fire disasters in buildings. This system provides visualization information and optimal guide for quick initial response by utilizing smart element AR-based disaster management service through linkage of physical virtual domain in the building. Additionally, we show a scenario flow chart of the fire extinguishment process according to the time from the ignition stage to the extinguishment stage in the building. Finally, we introduce the related sensors, the actuators, and a small test-bed for AR-based disaster management service. This test-bed was designed for interlocking and interoperability test of the system between the sensors and the actuators. It is expected that the proposed system can provide a quick and safe rescue guideline to the occupants and rescuers in the building where fire is generated and in regions of poor visibility.

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Economic Analysis for Collapse Hazard Areas

Cited by 2 publications

References 0 publications

Vulnerability Assessment Method for Immovable Cultural Relics Based on Artificial Neural Networks—An Example of a Heavy Rainfall Event in Henan Province

Vulnerability Assessment Method for Immovable Cultural Relics Based on Artificial Neural Networks—An Example of a Heavy Rainfall Event in Henan Province

Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure

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