Fuzzy dissimilarity-based classification for disaster initial assessment
A correct initial assessment of disaster consequences is crucial for an adequate decision-making in disaster and emergency management. However, such an initial assessment needs to be correct, but not necessarily fully precise, and thus it can be associated with a fuzzy classification problem in whic...
| Autores: | , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/35668 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/35668 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.8 Fuzzy rule based classification systems Disaster management Dissimilarity Investigación operativa (Matemáticas) 1207 Investigación Operativa |
| Sumario: | A correct initial assessment of disaster consequences is crucial for an adequate decision-making in disaster and emergency management. However, such an initial assessment needs to be correct, but not necessarily fully precise, and thus it can be associated with a fuzzy classification problem in which the set of classes presents a relevant structure. This paper proposes the consideration of a dissimilarity operator in order to introduce such a structure in the classifier's learning and reasoning procedures, leading to an improvement in the classifiers adaptation to the disaster management context features and decision making requirements. |
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