TY - GEN
T1 - Building a Decision Support System to Handle Teams in Disaster Situations - A Preliminary Approach
AU - Nunes, Isabel L.
AU - Calhamonas, Gabriel
AU - Marques, Mário
AU - Teodoro, M. Filomena
N1 - info:eu-repo/grantAgreement/FCT/5876/147271/PT#
Center for Computational and Stochastic Mathematics (CEMAT). Center of Naval Research (CINAV), Naval Academy, Portuguese Navy, Portugal.
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PY - 2020/1/1
Y1 - 2020/1/1
N2 - The objective of the present work is to build and implement a decision support system with the ability to prioritize certain teams for specific incidents taking into account the importance of each team that acts in case of emergency, the sequence of tasks that should perform all possible orders to be given. With such purpose, a collaborative estimation or forecasting technique that combines independent analysis with the maximum use of feedback was applied to build consensus among experts who interact anonymously (Delphi forecasting). The topic under discussion is distributed (in a series of rounds) between the participating experts who comment on it and modify the opinion(s) until a certain degree of mutual consensus is reached. In our case, the collection and summary of knowledge of a group of experts from a given area was done through various phases of questionnaires, accompanied byan organized feedback. Simultaneously, it was necessary to make a survey about the existing emergency teams, as well as of all possible tasks in case of emergency. With this purpose were held meetings with experienced individuals in emergency cases, some documents about some exercises performed were consulted, also direct observation of a simulation of a catastrophe exercise in which humanitarian aid is required allowed to collect and analyze some important data. The decision support system is not completed but we hope to have given an important contribution to its construction.
AB - The objective of the present work is to build and implement a decision support system with the ability to prioritize certain teams for specific incidents taking into account the importance of each team that acts in case of emergency, the sequence of tasks that should perform all possible orders to be given. With such purpose, a collaborative estimation or forecasting technique that combines independent analysis with the maximum use of feedback was applied to build consensus among experts who interact anonymously (Delphi forecasting). The topic under discussion is distributed (in a series of rounds) between the participating experts who comment on it and modify the opinion(s) until a certain degree of mutual consensus is reached. In our case, the collection and summary of knowledge of a group of experts from a given area was done through various phases of questionnaires, accompanied byan organized feedback. Simultaneously, it was necessary to make a survey about the existing emergency teams, as well as of all possible tasks in case of emergency. With this purpose were held meetings with experienced individuals in emergency cases, some documents about some exercises performed were consulted, also direct observation of a simulation of a catastrophe exercise in which humanitarian aid is required allowed to collect and analyze some important data. The decision support system is not completed but we hope to have given an important contribution to its construction.
KW - Catastrophe
KW - Decision support system
KW - Delphi method
KW - Expert
KW - Questionnaire
UR - http://www.scopus.com/inward/record.url?scp=85064863619&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-14347-3_54
DO - 10.1007/978-3-030-14347-3_54
M3 - Conference contribution
AN - SCOPUS:85064863619
SN - 978-3-030-14346-6
T3 - Advances in Intelligent Systems and Computing
SP - 551
EP - 559
BT - Hybrid Intelligent Systems - 18th International Conference on Hybrid Intelligent Systems HIS 2018
A2 - Madureira, Ana Maria
A2 - Gandhi, Niketa
A2 - Abraham, Ajith
A2 - Varela, Maria Leonilde
PB - Springer Verlag
CY - Cham
T2 - 18th International Conference on Hybrid Intelligent Systems, HIS 2018
Y2 - 13 December 2018 through 15 December 2018
ER -