Author:
YILMAZ Metin,YAZİCİ Ahmet,ÇINAR Eyüp
Publisher
Eskisehir Osmangazi Universitesi Muhendislik ve Mimarlik Fakultesi Dergisi
Reference12 articles.
1. Ahmad, W., Khan, S.A. & Kim, J. (2017). A hybrid prognostics technique for rolling element bearings using adaptive predictive model. IEEE Transactions on Industrial Electronics. doi: http://dx.doi.org/10.1109/TIE.2017.2733487
2. Chan, Y.S. & Tou Ng.H. (2008). MAXSIM: A maximum similarity metric for machine translation evaluation. Department of Computer Science National University of Singapore Law Link, Singapore 117590
3. Cosme, L.B., D’Angelo, M.F.S.V., Caminhas, W. M., Yin, S. & Palhares, R.M. (2017). A novel fault prognostic approach based on particle filters and differential evolution. Springer Science+Business Media, LLC 2017. doi: http://dx.doi.org/10.1007/s10489-017-1013-1
4. Data-Driven Documents, (2020). JavaScript library for manipulating documents based on data. Erişim Adresi: https://d3js.org
5. Hendrickx, K., Meert, W., Mollet, Y., Gyselinck, J., Cornelis, B., Gryllias, K. & Davis, J. (2019). A general anomaly detection framework for fleet-based condition monitoring of machines. Mechanical Systems and Signal Processing, 139, (2020), 106585. doi: http://dx.doi.org/10.1016/j.ymssp.2019.106585
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