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Mining and visualizing uncertain data objects and named data networking traffics by fuzzy self-organizing map

Autor
Karami, A.; Guerrero, M.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
2nd International Workshop on Artificial Intelligence and Cognition
Any de l'edició
2014
Data de presentació
2014-11
Llibre d'actes
Proceedings of the Second International Workshop on Artificial Intelligence and Cognition (AIC 2014): Torino, Italy, November 26-27, 2014
Pàgina inicial
156
Pàgina final
163
Editor
CEUR-WS.org
Projecte finançador
Plataforma de Servicios para Ciudades Inteligentes con redes M2M densas
Repositori
http://hdl.handle.net/2117/26239 Obrir en finestra nova
URL
http://ceur-ws.org/Vol-1315/paper14.pdf Obrir en finestra nova
Resum
Uncertainty is widely spread in real-world data. Uncertain data-in computer science-is typically found in the area of sensor networks where the sensors sense the environment with certain error. Mining and visualizing uncertain data is one of the new challenges that face uncertain databases. This paper presents a new intelligent hybrid algorithm that applies fuzzy set theory into the context of the Self-Organizing Map to mine and visualize uncertain objects. The algorithm is tested in some benchm...
Citació
Karami, A.; Guerrero, M. Mining and visualizing uncertain data objects and named data networking traffics by fuzzy self-organizing map. A: International Workshop on Artificial Intelligence and Cognition. "Proceedings of the Second International Workshop on Artificial Intelligence and Cognition (AIC 2014): Torino, Italy, November 26-27, 2014". Torino: CEUR-WS.org, 2014, p. 156-163.
Paraules clau
Algorithms, Artificial Intelligence, Conformal Mapping, Fuzzy Sets, Self Organizing Maps, Bench-mark Problems, Fuzzy Self-organizing Maps, Hybrid Algorithms, Named Data Networkings, Performance Criterion, Real-world, Uncertain Database, Uncertain Datas
Grup de recerca
CNDS - Xarxes de Computadors i Sistemes Distribuïts

Participants

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