A method to improve the resilience of multimodal transport network: Location selection strategy of emergency rescue facilities

J Guo, Q Du, Z He - Computers & Industrial Engineering, 2021 - Elsevier
This paper studies the location selection strategy of emergency rescue facilities in the
multimodal transport network to improve the resilience of the network. Based on the overall …

[HTML][HTML] Data-driven forecasting for operational planning of emergency medical services

P Abreu, D Santos, A Barbosa-Povoa - Socio-Economic Planning Sciences, 2023 - Elsevier
Emergency medical services (EMS) play a vital role in delivering pre-hospital care. The
operational efficiency of such services is critical and adequate demand forecasts can …

Forecasting the demand for emergency medical services

K Steins, N Matinrad, T Granberg - 2019 - scholarspace.manoa.hawaii.edu
Accurate forecast of the demand for emergency medical services (EMS) can help in
providing quick and efficient medical treatment and transportation of out-of-hospital patients …

[HTML][HTML] Short-term forecasting of emergency medical services demand exploring machine learning

N Shahidian, P Abreu, D Santos… - Computers & Industrial …, 2025 - Elsevier
This study addresses the challenge of forecasting short-term demand in Emergency Medical
Services (EMS) using machine learning techniques, which is essential for improving …

Forecasting emergency calls with a Poisson neural network-based assemble model

H Huang, M Jiang, Z Ding, M Zhou - IEEE Access, 2019 - ieeexplore.ieee.org
Forecasting emergency calls are of great importance in practice. By forecasting the
occurrence of unfortunate events, we can learn from these events and further prevent their …

A Novel Machine Learning Approach for Spatiotemporal Prediction of EMS Events: A Case Study from Barranquilla, Colombia

D Neira-Rodado, JC Paz-Roa, JW Escobar… - Heliyon, 2025 - cell.com
Anticipating the timing and location of future emergency calls is crucial for making informed
decisions about vehicle location and relocation, ultimately reducing response times and …

Bayesian spatio-temporal modelling and prediction of areal demands for ambulance services

V Nicoletta, A Guglielmi, A Ruiz… - IMA Journal of …, 2022 - academic.oup.com
Careful planning of an ambulance service is critical to reduce response times to emergency
calls and make assistance more effective. However, the demand for emergency services is …

Ambulance Demand Prediction via Convolutional Neural Networks

M Rautenstrauß, M Schiffer - arXiv preprint arXiv:2306.04994, 2023 - arxiv.org
Minimizing response times is crucial for emergency medical services to reduce patients'
waiting times and to increase their survival rates. Many models exist to optimize operational …

Models for Dispatch of Volunteers in Daily Emergency Response

N Matinrad - 2022 - diva-portal.org
Sufficient emergency resources are essential for emergency services to provide timely help
to affected people and to minimize damage to public and private assets and the …

An operations research approach for daily emergency management

N Matinrad - 2019 - diva-portal.org
Emergency services play a vital role in society by providing help to affected people and
minimizing damage to public and private assets as well as the environment during …