001413689 000__ 02831nam\a2200577\i\4500 001413689 001__ 1413689 001413689 003__ DLC 001413689 005__ 20221109003318.0 001413689 006__ m\\\\\o\\d\\\\\\\\ 001413689 007__ cr\un\nnnunnun 001413689 008__ 220220s2022\\\\flua\\\\ob\\\\001\0\eng\d 001413689 010__ $$a 2021060650 001413689 020__ $$a9781000594935 001413689 020__ $$a1000594939 001413689 020__ $$a9781003240754 001413689 020__ $$a1003240755 001413689 020__ $$a9781000594928 001413689 020__ $$z9781032147253 001413689 020__ $$z9781032147260 001413689 040__ $$aNhCcYBP$$cNhCcYBP 001413689 042__ $$apcc 001413689 050_4 $$aTA169.6$$b.Y35 2022 001413689 08200 $$a620/.0044$$223/eng/20220325 001413689 1001_ $$aYang, Rui$$c(Professor of computer engineering),$$eauthor. 001413689 24510 $$aMachine learning-based fault diagnosis for industrial engineering systems /$$cRui Yang, Maiying Zhong. 001413689 250__ $$aFirst edition. 001413689 264_1 $$aBoca Raton ;$$aLondon :$$bCRC Press,$$c2022. 001413689 300__ $$a1 online resource. 001413689 336__ $$atext$$btxt$$2rdacontent 001413689 337__ $$acomputer$$bc$$2rdamedia 001413689 338__ $$aonline resource$$bcr$$2rdacarrier 001413689 4900_ $$aAdvances in intelligent decision-making 001413689 504__ $$aIncludes bibliographical references and index. 001413689 5050_ $$aBackground and related methods -- Fault diagnosis method based on recurrent convolutional neural network -- Fault diagnosis of rotating machinery gear based on random forest algorithm -- Bearing fault diagnosis under different working conditions based on generative adversarial networks -- Rotating machinery gearbox fault diagnosis based on one-dimensional convolutional neural network and random forest -- Fault diagnosis for rotating machinery gearbox based on improved random forest algorithm -- Imbalanced data fault diagnosis based on hybrid feature dimensionality reduction and varied density based safe level synthetic minority oversampling technique. 001413689 506__ $$aAccess limited to authorized users 001413689 533__ $$aElectronic reproduction.$$bAnn Arbor, MI$$nAvailable via World Wide Web. 001413689 588__ $$aDescription based on print version record and CIP data provided by publisher. 001413689 650_0 $$aFault location (Engineering)$$xAutomation. 001413689 650_0 $$aAutomatic test equipment. 001413689 650_0 $$aMachinery$$xTesting. 001413689 650_0 $$aIndustrial equipment$$xMaintenance and repair. 001413689 650_0 $$aMachine learning. 001413689 655_0 $$aElectronic books 001413689 7001_ $$aZhong, Maiying,$$eauthor. 001413689 7102_ $$aProQuest (Firm) 001413689 77608 $$iPrint version:$$aYang, Rui$$tMachine learning-based fault diagnosis for industrial engineering systems$$bFirst edition.$$dBoca Raton ; London : CRC Press, 2022$$z9781032147253$$w(DLC) 2021060649 001413689 852__ $$bebk 001413689 85640 $$3GOBI DDA$$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=6946404$$zOnline Access 001413689 909CO $$ooai:library.usi.edu:1413689$$pGLOBAL_SET 001413689 980__ $$aBIB 001413689 980__ $$aEBOOK 001413689 982__ $$aEbook 001413689 983__ $$aOnline