Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 270

1.

Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

Li C, Zhou J.

ISA Trans. 2014 Sep;53(5):1534-43. doi: 10.1016/j.isatra.2014.05.019. Epub 2014 Jun 27.

PMID:
24981891
2.

A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.

Hu D, Sarosh A, Dong YF.

ISA Trans. 2012 Mar;51(2):309-16. doi: 10.1016/j.isatra.2011.10.005. Epub 2011 Oct 28.

PMID:
22035775
3.

Vicinal support vector classifier using supervised kernel-based clustering.

Yang X, Cao A, Song Q, Schaefer G, Su Y.

Artif Intell Med. 2014 Mar;60(3):189-96. doi: 10.1016/j.artmed.2014.01.003. Epub 2014 Feb 7.

PMID:
24637294
4.

Weighted Kernel Entropy Component Analysis for Fault Diagnosis of Rolling Bearings.

Zhou H, Shi T, Liao G, Xuan J, Duan J, Su L, He Z, Lai W.

Sensors (Basel). 2017 Mar 18;17(3). pii: E625. doi: 10.3390/s17030625.

5.

Compound feature selection and parameter optimization of ELM for fault diagnosis of rolling element bearings.

Luo M, Li C, Zhang X, Li R, An X.

ISA Trans. 2016 Nov;65:556-566. doi: 10.1016/j.isatra.2016.08.022. Epub 2016 Sep 9.

PMID:
27622428
6.

A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform.

Yu X, Ding E, Chen C, Liu X, Li L.

Sensors (Basel). 2015 Nov 3;15(11):27869-93. doi: 10.3390/s151127869.

7.
8.

A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System.

Yuan X, Song M, Zhou F, Chen Z, Li Y.

Comput Intell Neurosci. 2015;2015:606734. doi: 10.1155/2015/606734. Epub 2015 Jul 2.

9.

Semi-supervised information-maximization clustering.

Calandriello D, Niu G, Sugiyama M.

Neural Netw. 2014 Sep;57:103-11. doi: 10.1016/j.neunet.2014.05.016. Epub 2014 Jun 4.

PMID:
24975502
10.

Enhanced manifold regularization for semi-supervised classification.

Gan H, Luo Z, Fan Y, Sang N.

J Opt Soc Am A Opt Image Sci Vis. 2016 Jun 1;33(6):1207-13. doi: 10.1364/JOSAA.33.001207.

PMID:
27409451
11.

An unsupervised text mining method for relation extraction from biomedical literature.

Quan C, Wang M, Ren F.

PLoS One. 2014 Jul 18;9(7):e102039. doi: 10.1371/journal.pone.0102039. eCollection 2014.

12.

A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network.

Liu Z, Liu Y, Shan H, Cai B, Huang Q.

PLoS One. 2015 May 4;10(5):e0125703. doi: 10.1371/journal.pone.0125703. eCollection 2015.

13.

Semi-Supervised Kernel Mean Shift Clustering.

Anand S, Mittal S, Tuzel O, Meer P.

IEEE Trans Pattern Anal Mach Intell. 2013 Sep 30. [Epub ahead of print]

PMID:
24101327
14.

Incremental multi-class semi-supervised clustering regularized by Kalman filtering.

Mehrkanoon S, Agudelo OM, Suykens JA.

Neural Netw. 2015 Nov;71:88-104. doi: 10.1016/j.neunet.2015.08.001. Epub 2015 Aug 14.

PMID:
26319050
15.

[Application of optimized parameters SVM based on photoacoustic spectroscopy method in fault diagnosis of power transformer].

Zhang YX, Cheng ZF, Xu ZP, Bai J.

Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Jan;35(1):10-3. Chinese.

PMID:
25993810
16.

Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network.

He J, Yang S, Gan C.

Sensors (Basel). 2017 Jul 4;17(7). pii: E1564. doi: 10.3390/s17071564.

17.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line.

Huang N, Qi J, Li F, Yang D, Cai G, Huang G, Zheng J, Li Z.

Sensors (Basel). 2017 Sep 16;17(9). pii: E2133. doi: 10.3390/s17092133.

18.

Semi-Supervised Kernel Mean Shift Clustering.

Anand S, Mittal S, Tuzel O, Meer P.

IEEE Trans Pattern Anal Mach Intell. 2014 Jun;36(6):1201-15. doi: 10.1109/TPAMI.2013.190.

PMID:
26353281
19.

Multi-fault clustering and diagnosis of gear system mined by spectrum entropy clustering based on higher order cumulants.

Shao R, Li J, Hu W, Dong F.

Rev Sci Instrum. 2013 Feb;84(2):025107. doi: 10.1063/1.4789777.

PMID:
23464251
20.

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Chang CC, Lin PY.

Neural Netw. 2015 Mar;63:170-84. doi: 10.1016/j.neunet.2014.11.006. Epub 2014 Dec 11.

PMID:
25550195

Supplemental Content

Support Center