An Intelligent Model to Analyze Aviation Incidents
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/30341DOI: 10.12988/ces.2017.7435
ISSN: 1314-7641
Date
2017-05-25Bibliographic citation
Aguilar, J., Shi, D., Gutiérrez De Mesa, J.A., Chávez, D. An Intelligent Model to Analyze Aviation Incidents. En: Contemporary Engineering Sciences, 2017, v. 10, n. 10, p. 463-473
Keywords
Aviation Incidents
Text mining
Fuzzy Cognitive Map
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Publisher's version
https://doi.org/10.12988/ces.2017.7435Rights
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Access rights
info:eu-repo/semantics/openAccess
Abstract
In this paper, we propose a hybrid intelligent model based on text mining and Fuzzy Cognitive Map (FCM), in order to determine the causes of aviation incidents. Our approach considers several dimensions of the problem, to define the possible causes of an aviation incident. It considers the human factors, one of the main causes of incidents, but also includes other aspects that normally are not considered in the analysis of Aviation incidents, such as the conditions of the flight or of the airplane. Particularly, we propose text mining tasks to extract the key information from the reports of the incidents, and a Multilevel FCM to integrate the different dimensions considered in our approach. We use a database about reports of aviation incidents to train and test our system. The preliminary results are very encouraging, because we can infer the reasons of the incidents.
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