Self-tuning linear adaptive genetic algorithm for feature selection in machinery fault diagnosis
Advanced pattern recognition of a machine learning classifier function, aka the black box allows automated machinery fault diagnosis and outperforms classic decision-making mechanisms. Nonetheless, the black box supervised learning is subject to overfitting when the usefulness of statistical input f...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/107056/1/OoiChingShengPFTIR2021.pdf http://eprints.utm.my/107056/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:156412?site_name=GlobalView&query=Self-tuning+linear+adaptive+genetic+algorithm+for+feature+selection+in+machinery+fault+diagnosis&f0=sm_type%3A%22Thesis%22&queryType=vitalDismax |
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http://eprints.utm.my/107056/1/OoiChingShengPFTIR2021.pdfhttp://eprints.utm.my/107056/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:156412?site_name=GlobalView&query=Self-tuning+linear+adaptive+genetic+algorithm+for+feature+selection+in+machinery+fault+diagnosis&f0=sm_type%3A%22Thesis%22&queryType=vitalDismax