An Intelligent Model to Analyze Aviation Incidents
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 fac...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universidad de Alcalá (UAH) |
| Repositorio: | e_Buah Biblioteca Digital Universidad de Alcalá |
| Idioma: | inglés |
| OAI Identifier: | oai:ebuah.uah.es:10017/30341 |
| Acceso en línea: | http://hdl.handle.net/10017/30341 https://dx.doi.org/10.12988/ces.2017.7435 |
| Access Level: | acceso abierto |
| Palabra clave: | Aviation Incidents Text mining Fuzzy Cognitive Map Informática Computer science |
| Sumario: | 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. |
|---|