首页|New Support Vector Machines Findings Reported from Griffith University (Detectio n of Signal Integrity Issues In Vibration Monitoring Using One-class Support Vec tor Machine)
New Support Vector Machines Findings Reported from Griffith University (Detectio n of Signal Integrity Issues In Vibration Monitoring Using One-class Support Vec tor Machine)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Support Vecto r Machines have been published. According to news reporting originating from Gol d Coast, Australia, by NewsRx correspondents, research stated, "This paper prese nts an analysis of the common signal integrity issues in vibration monitoring ca used by sensor saturation and signal distortion, or sensor loosening and detachm ent, and the development of a method of detecting the occurrence of vibration si gnal integrity issues using a one-class support vector machine. For this, vibrat ion signals with distortions due to sensor saturation and/or sensor detachment a re analysed to determine parameters sensitive to common integrity issues." Financial support for this research came from Griffith University - Gold Coast C ampus.
Gold CoastAustraliaAustralia and New ZealandEmerging TechnologiesMachine LearningSupport Vector MachinesVect or MachinesGriffith University
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