Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace: http://hdl.handle.net/2117/26983
dc.contributor | Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
---|---|
dc.contributor | Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group |
dc.contributor.author | Cariño Corrales, Jesús Adolfo |
dc.contributor.author | Zurita Millán, Daniel |
dc.contributor.author | Delgado Prieto, Miquel |
dc.contributor.author | Ortega Redondo, Juan Antonio |
dc.contributor.author | Romero Troncoso, Rene De Jesus |
dc.date | 2014 |
dc.identifier.citation | Cariño , J.A. [et al.]. Hierarchical classification scheme based on identification, isolation and analysis of conflictive regions. A: IEEE International Conference on Emerging Technologies and Factory Automation. "Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation". Barcelona: Institute of Electrical and Electronics Engineers (IEEE), 2014. |
dc.identifier.citation | 978-1-4799-4846-8 |
dc.identifier.citation | 10.1109/ETFA.2014.7005208 |
dc.identifier.uri | http://hdl.handle.net/2117/26983 |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.relation | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7005208&isnumber=7005023 |
dc.rights | info:eu-repo/semantics/openAccess |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject | Àrees temàtiques de la UPC::Enginyeria electrònica |
dc.subject | Artificial intelligence |
dc.subject | keywords: {condition monitoring |
dc.subject | feature selection |
dc.subject | maintenance engineering |
dc.subject | mechanical engineering computing |
dc.subject | pattern classification |
dc.subject | support vector machines |
dc.subject | classification algorithm configuration |
dc.subject | classification training |
dc.subject | condition-based maintenance systems |
dc.subject | conflictive region analysis |
dc.subject | conflictive region identification |
dc.subject | conflictive region isolation |
dc.subject | feature reduction |
dc.subject | feature space transformation |
dc.subject | hierarchical classification scheme |
dc.subject | membership regions |
dc.subject | optimal data management |
dc.subject | physical magnitudes |
dc.subject | sequential layers |
dc.subject | upper levels |
dc.subject | Accuracy |
dc.subject | Databases |
dc.subject | Degradation |
dc.subject | Feature extraction |
dc.subject | Kernel |
dc.subject | Support vector machines |
dc.subject | Training |
dc.subject | Artificial Intelligence |
dc.subject | Classification Algorithms |
dc.subject | Condition Monitoring |
dc.subject | Feature extraction |
dc.subject | Machine Learning |
dc.subject | Support Vector Machines} |
dc.subject | Intel·ligència artificial |
dc.title | Hierarchical classification scheme based on identification, isolation and analysis of conflictive regions |
dc.type | info:eu-repo/semantics/publishedVersion |
dc.type | info:eu-repo/semantics/conferenceObject |
dc.description.abstract |