Details

Title

Recurrent Neural Networks for Predictive Maintenance of Mill Fan Systems

Journal title

International Journal of Electronics and Telecommunications

Yearbook

2011

Numer

No 3

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee of Electronics and Telecommunications

Date

2011

Identifier

ISSN 2081-8491 (until 2012) ; eISSN 2300-1933 (since 2013)

References

Haykin S. (1999), Neural Networks: A Comprehensive Foundation. ; Ciarapica F. (2006), Managing the Condition-Based Mintenance of a Combined-Cycle Power Plant: An Approach Using Soft Computing Techniques, Journal of Loss Prevention in the Process Industries, 19, 316, doi.org/10.1016/j.jlp.2005.07.018 ; Elman J. (1990), Finding Structure in Time, Cognitive Science, 14, 179, doi.org/10.1207/s15516709cog1402_1 ; H. Jaeger, "Tutorial on Training Recurrent Nural Networks, Covering BPPT, RTRL, EKF and the "Echo State Network"Approach," German National Research Center for Information Technology, GMD Report 159, 2002. ; Jaeger H. (2003), Adaptive Nonlinear System Identification with Echo State Networks, null, 593. ; Lukosevicius M. (2009), Reservoir Computing Approaches to Recurrent Neural Network Training, Computer Science Review, 3, 127, doi.org/10.1016/j.cosrev.2009.03.005 ; Schrauwen B. (2008), Improving Reservoirs Using Intrinsic Plasticity, Neurocomputing, 71, 1159, doi.org/10.1016/j.neucom.2007.12.020 ; Koprinkova-Hristova P. (2010), Adaptive Critic Design with ESN Critic for Bioprocess Optimization, Lecture Notes in Computer Science, 6353, 438, doi.org/10.1007/978-3-642-15822-3_54 ; Koprinkova-Hristova P. (2010), Adaptive Critic Design with Echo State Network, null, 1010. ; Balabanov T. (2011), Neural Network Model of Mill-Fan System Elements Vibration for Predictive Maintenance, null, 410. ; <a target="_blank" href='http://www.mathworks.com/matlabcentral/fileexchange/18289'>Http://www.mathworks.com/matlabcentral/fileexchange/18289</a> ; Prokhorov D. (2005), Echo State Networks: Appeal and Challenges, null, 1463. ; <a target="_blank" href='http://www.reservoir-computing.org/software'>http://www.reservoir-computing.org/software</a> ; Donoho D. (1995), De-Noising by Soft-Thresholding, IEEE Transactions on Information Theory, 41, 3, 613, doi.org/10.1109/18.382009

DOI

10.2478/v10177-011-0055-2

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