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2016 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2016 - Proceedings(1)
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Proceedings - 11th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2017(1)
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Clustering algorithm using rough set theory for unsupervised feature selection
Conference ObjectAbstract: Nowadays, the available data to describe real world problems grows in considerable manner, due to thPalabras claves:Autores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusAttribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery
ArticleAbstract: Features extracted from real world applications increase dramatically, while machine learning methodPalabras claves:Attribute clustering, Fault severity classification, feature selection, Rotating machinery, Rough setAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusA methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery
Conference ObjectAbstract: Selecting an adequate machine learning model, e.g. for feature selection or classification, is a verPalabras claves:Autores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusA review on data-driven fault severity assessment in rolling bearings
ReviewAbstract: Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in induPalabras claves:Fault assessment, Fault severity, Fault size, Quantitative diagnosis, Rolling bearingsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopusMulti-fault diagnosis of rotating machinery by using feature ranking methods and SVM-based classifiers
Conference ObjectAbstract: Rotating machinery plays an important role in industries for motion transmission in machines; the brPalabras claves:Feature ranking, Helical gearbox, Multi-fault diagnosisAutores:Fannia Pacheco, Jean Carlo Macancela Poveda, Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopusHierarchical feature selection based on relative dependency for gear fault diagnosis
ArticleAbstract: Feature selection is an important aspect under study in machine learning based diagnosis, that aimsPalabras claves:Attribute clustering, feature selection, Gear fault diagnosis, Relative dependency, Rough setsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusMethodological framework for data processing based on the Data Science paradigm
Conference ObjectAbstract: This paper describes the steps for achieving data processing in a methodological context, which takePalabras claves:Data Mining, data science, Health management, industrial processes, Knowledge engineeringAutores:Altamiranda J., Fannia Pacheco, José Lisandro Aguilar Castro, Mariela Cerrada Lozada, Rangel C.Fuentes:scopusMethodology for detecting the feasibility of using data mining in an organization
Conference ObjectAbstract: This paper proposes a methodology to identify the feasibility of applying Data Mining techniques (DMPalabras claves:Data Analysis, Data Mining, Health management, industrial processes, Knowledge engineeringAutores:Altamiranda J., Fannia Pacheco, José Lisandro Aguilar Castro, Mariela Cerrada Lozada, Rangel C.Fuentes:scopusSOA Based Integrated Software to Develop Fault Diagnosis Models Using Machine Learning in Rotating Machinery
Conference ObjectAbstract: Fault detection and diagnostic software (FDDS) supports technicians and engineers to deal with operaPalabras claves:e-Maintenance, Fault diagnosis, Industrial supervision, Machine learning, Rotating machinery, SOAAutores:Diego R. Cabrera, Fannia Pacheco, Jean Carlo Macancela Poveda, Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez LojaFuentes:googlescopus