Search

Your search keyword '"Brute Force Algorithm"' showing total 2 results
Start Over Descriptor "Brute Force Algorithm" Publisher universitat politecnica de catalunya
2 results on '"Brute Force Algorithm"'

1. Analysis of the location of emergency vehicles in the Sistema d'Emergències Mèdiques (SEM) using machine learning techniques

Author

Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica, Aguilar Igartua, Mónica, Barbecho Bautista, Pablo Andrés, Li, Ruojin, Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica, Aguilar Igartua, Mónica, Barbecho Bautista, Pablo Andrés, and Li, Ruojin

Abstract

Emergency Medical Service is an essential part of the modern emergency medical service system. The survival rate of emergency patients depends mainly on the time between the issuance of an emergency call and the arrival of an ambulance at the scene of need. Therefore, the location of the ambulance base and the deployment of ambulances are crucial for Emergency Medical Service. Over three years, the project collaborates between Sistema d'Emergències Mèdiques (SEM) and UPC's Smart Services for Information Systems and Communication Networks (SISCOM). The project's main objective is to help SEM establish a complete ambulance location management system in Catalonia. This paper analyses and uses real data provided by SEM for the Regió Sanitària of Terres de l'Ebre in Catalonia. The real data provided by SEM are used to train the LSTM model, thus verifying the feasibility of the LSTM model for this type of problem. Based on the real data provided by SEM, there are four ambulances located in four different ambulance bases in this region. Therefore, another objective of this project is to simulate which configuration has the shortest patient waiting time and ambulance response time under the same conditions for all different ambulance configurations using our proposed Brute Force algorithm.

Published
2022

2. Analysis of the location of emergency vehicles in the Sistema d'Emergències Mèdiques (SEM) using machine learning techniques

Author

Li, Ruojin, Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica, Aguilar Igartua, Mónica, and Barbecho Bautista, Pablo Andrés

Subjects
Location-based services, long short-term memory(LSTM), Ambulàncies, Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors [Àrees temàtiques de la UPC], Geolocalització, Serveis de, Ambulances, ambulance, brute force algorithm, location, relocation
Abstract

Emergency Medical Service is an essential part of the modern emergency medical service system. The survival rate of emergency patients depends mainly on the time between the issuance of an emergency call and the arrival of an ambulance at the scene of need. Therefore, the location of the ambulance base and the deployment of ambulances are crucial for Emergency Medical Service. Over three years, the project collaborates between Sistema d'Emergències Mèdiques (SEM) and UPC's Smart Services for Information Systems and Communication Networks (SISCOM). The project's main objective is to help SEM establish a complete ambulance location management system in Catalonia. This paper analyses and uses real data provided by SEM for the Regió Sanitària of Terres de l'Ebre in Catalonia. The real data provided by SEM are used to train the LSTM model, thus verifying the feasibility of the LSTM model for this type of problem. Based on the real data provided by SEM, there are four ambulances located in four different ambulance bases in this region. Therefore, another objective of this project is to simulate which configuration has the shortest patient waiting time and ambulance response time under the same conditions for all different ambulance configurations using our proposed Brute Force algorithm.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results