Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
  • Fan C. Evaluation of Machine Learning Methods for Image Classification: A Case Study of Facility Surface Damage. Machine Learning for Networking. (1-10).

    https://doi.org/10.1007/978-3-030-98978-1_1

  • Fu W, Tan J, Zhang X, Chen T, Wang K and Mrugalski M. (2019). Blind Parameter Identification of MAR Model and Mutation Hybrid GWO-SCA Optimized SVM for Fault Diagnosis of Rotating Machinery. Complexity. 2019. Online publication date: 1-Jan-2019.

    https://doi.org/10.1155/2019/3264969

  • Ferreira B, Silva R and Pereira V. Feature selection using non-binary decision trees applied to condition monitoring. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). (1-7).

    https://doi.org/10.1109/ETFA.2017.8247642

  • Silva R and Reis R. Adaptive self-organizing map applied to lathe tool condition monitoring. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). (1-6).

    https://doi.org/10.1109/ETFA.2017.8247641

  • Pacheco F, Cerrada M, Sánchez R, Cabrera D, Li C and Valente de Oliveira J. (2017). Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery. Expert Systems with Applications: An International Journal. 71:C. (69-86). Online publication date: 1-Apr-2017.

    https://doi.org/10.1016/j.eswa.2016.11.024

  • Peng L, Zhang H, Zhang H and Yang B. (2017). A fast feature weighting algorithm of data gravitation classification. Information Sciences: an International Journal. 375:C. (54-78). Online publication date: 1-Jan-2017.

    https://doi.org/10.1016/j.ins.2016.09.044