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Application of Clustering Methods for Online Tool Condition Monitoring and Fault Diagnosis in High-Speed Milling Processes.

, , , , and . IEEE Systems Journal, 10 (2): 721-732 (2016)

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A Survey on Artificial Intelligence-Based Modeling Techniques for High Speed Milling Processes., , , , , , , and . IEEE Systems Journal, 9 (3): 1069-1080 (2015)Comprehensive Fuzzy Turing Machines, An Evolution to the Concept of Finite State Machine Control., , and . CoRR, (2019)Genetic Dynamic Fuzzy Neural Network (GDFNN) for Nonlinear System Identification., , , , , , , and . ISNN (2), volume 6676 of Lecture Notes in Computer Science, page 525-534. Springer, (2011)Sequential fuzzy clustering based dynamic fuzzy neural network for fault diagnosis and prognosis., , , and . Neurocomputing, (2016)Application of Clustering Methods for Online Tool Condition Monitoring and Fault Diagnosis in High-Speed Milling Processes., , , , and . IEEE Systems Journal, 10 (2): 721-732 (2016)Intelligent selective packet discarding using general fuzzy automata., , , , and . SMC, page 3714-3720. IEEE, (2008)An enhanced online self-organizing fuzzy neural network., , , , and . ICARCV, page 2214-2220. IEEE, (2010)Flute based analysis of ball-nose milling signals using continuous wavelet analysis features., , , , , , , , , and . ICARCV, page 1359-1364. IEEE, (2010)Adaptive Network Fuzzy Inference System and support vector machine learning for tool wear estimation in high speed milling processes., , , , , , , and . IECON, page 2821-2826. IEEE, (2012)