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Generation of classification rules using artificial immune system for fault diagnosis., , и . SMC, стр. 343-349. IEEE, (2010)A Robust Anomaly Detection in Pantograph-Catenary System Based on Mean-Shift Tracking and Foreground Detection., , и . SMC, стр. 4444-4449. IEEE, (2013)A new approach based on boundary analysis of reconstructed phase space for fault diagnosis., , и . ASCC, стр. 1-6. IEEE, (2013)A new real-time fuzzy logic based diagnosis of stator faults for inverter-fed induction motor under low speeds., , и . INDIN, стр. 446-451. IEEE, (2016)Improvement of relative accreditation methods based on data mining and artificial intelligence for higher education., , и . ITHET, стр. 1-7. IEEE, (2016)An efficient genetic algorithm for automated mining of both positive and negative quantitative association rules., и . Soft Comput., 10 (3): 230-237 (2006)Anomaly detection using a modified kernel-based tracking in the pantograph-catenary system., , и . Expert Syst. Appl., 42 (2): 938-948 (2015)Multi-objective rule mining using a chaotic particle swarm optimization algorithm., и . Knowl. Based Syst., 22 (6): 455-460 (2009)An approach for automated fault diagnosis based on a fuzzy decision tree and boundary analysis of a reconstructed phase space, , и . \ISA\ Transactions, 53 (2): 220 - 229 (2014)An adaptive artificial immune system for fault classification., , и . J. Intell. Manuf., 23 (5): 1489-1499 (2012)