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Interactive Trouble Condition Sign Discovery for Hydroelectric Power Plants.

, , and . ICONIP (2), volume 5507 of Lecture Notes in Computer Science, page 663-670. Springer, (2008)

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Trouble condition sign discovery based on support vector machines for hydroelectric power plants., , and . IJCNN, page 2358-2365. IEEE Computer Society, (2009)Unusual condition monitoring based on support vector machines for hydroelectric power plants., , and . IEEE Congress on Evolutionary Computation, page 2254-2261. IEEE, (2008)Interactive Trouble Condition Sign Discovery for Hydroelectric Power Plants., , and . ICONIP (2), volume 5507 of Lecture Notes in Computer Science, page 663-670. Springer, (2008)Interactive Abnormal Condition Sign Discovery for Hydroelectric Power Plants., , and . PAKDD Workshops, volume 5433 of Lecture Notes in Computer Science, page 181-192. Springer, (2008)Pneumatically Driven Ophthalmologic Surgery Robot with Intraocular Pressure Control., , , , and . RO-MAN, page 358-362. IEEE, (2023)An incremental learning using schema extraction mechanism for autonomous mobile robot., , and . CIRA, page 1126-1131. IEEE, (2003)A cornea holding device for transplantation surgery using negative pressure., , and . CCTA, page 720-725. IEEE, (2017)One-Class SVM based Unusual Condition Monitoring for Risk Management of Hydroelectric Power Plants., , and . IJCNN, page 857-862. IEEE, (2007)Unusual Condition Detection of Bearing Vibration in Hydroelectric Power Plants for Risk Management., , and . JSAI, volume 4384 of Lecture Notes in Computer Science, page 317-331. Springer, (2006)Unusual Condition Mining for Risk Management of Hydroelectric Power Plants., , and . ICDM Workshops, page 694-698. IEEE Computer Society, (2006)