Artificial neural network approaches for disaster management: A literature review

S Guha, RK Jana, MK Sanyal - International Journal of Disaster Risk …, 2022 - Elsevier
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …

A stacking-based ensemble learning method for earthquake casualty prediction

S Cui, Y Yin, D Wang, Z Li, Y Wang - Applied Soft Computing, 2021 - Elsevier
The estimation of the loss and prediction of the casualties in earthquake-stricken areas are
vital for making rapid and accurate decisions during rescue efforts. The number of casualties …

Use of OR in earthquake operations management: A review of the literature and roadmap for future research

B Çoban, MP Scaparra, JR O'Hanley - International Journal of Disaster Risk …, 2021 - Elsevier
To reduce human losses and minimize social and economic disruption caused by large-
scale earthquakes, effective planning and operational decisions need to be made by …

A discrete-event simulation model of hospital patient flow following major earthquakes

A Basaglia, E Spacone, JW van de Lindt… - International Journal of …, 2022 - Elsevier
Following a major disaster, hospitals must promptly rearrange their organization and
treatment procedures to deal with the sudden arrival of a high number of injured people to …

Forecasting the number of the wounded after an earthquake disaster based on the continuous interval grey discrete verhulst model

J Zhang, T Wang, J Chang… - Discrete Dynamics in …, 2021 - Wiley Online Library
Earthquake disaster causes serious casualties, so the prediction of casualties is conducive
to the reasonable and efficient allocation of emergency relief materials, which plays a …

Deep learning forecasting of large induced earthquakes via precursory signals

V Convertito, F Giampaolo, O Amoroso, F Piccialli - Scientific reports, 2024 - nature.com
Precursory phenomena to earthquakes have always attracted researchers' attention. Among
the most investigated precursors, foreshocks play a key role. However, their prompt …

A multi-method patient arrival forecasting outline for hospital emergency departments

M Yucesan, M Gul, E Celik - International Journal of Healthcare …, 2020 - Taylor & Francis
Patient arrivals at the emergency department (ED) of hospitals has an unpredictable
behavior. So that, adequate forecasting of this process can serve a management baseline to …

Emergency department network under disaster conditions: The case of possible major Istanbul earthquake

M Gul, A Fuat Guneri, MM Gunal - Journal of the Operational …, 2020 - Taylor & Francis
Emergency departments (EDs) provide health care services to people in need of urgent
care. Their role is remarkable when extraordinary events that affect the public, such as …

A spatial evaluation method for earthquake disaster using optimized BP neural network model

H Zhou, A Che, X Shuai, Y Zhang - Geomatics, Natural Hazards …, 2023 - Taylor & Francis
Rapid spatial evaluation of seismic disaster after earthquake occurrence is required in
disaster emergency rescue management, because of its importance in decreasing …

A zoning earthquake casualty prediction model based on machine learning

B Li, A Gong, T Zeng, W Bao, C Xu, Z Huang - Remote Sensing, 2021 - mdpi.com
The evaluation of mortality in earthquake-stricken areas is vital for the emergency response
during rescue operations. Hence, an effective and universal approach for accurately …