Training a deep net with OSELM
Versione 1.0.0 (3,22 MB) da
BERGHOUT Tarek
This algorithm is a basic example that will help to construct a deep belief neural network with Extreme Learning Machine rules (i.e OSELM))
This algorithm is a basic example that will help to construct a deep belief neural network with Extreme Learning Machine rules (i.e OSELM)
You can use these papers which uses similar paradigms to this algorithm for betters undrestandings
Please cite our papers :
% Berghout, Tarek et al. 2021. “A Deep Supervised Learning Approach for Condition-Based Maintenance of Naval Propulsion Systems.” Ocean Engineering 221: 108525. https://linkinghub.elsevier.com/retrieve/pii/S0029801820314323.
% Berghout, Tarek et al. 2020. “Aircraft Engines Remaining Useful Life Prediction with an Adaptive Denoising Online Sequential Extreme Learning Machine.” Engineering Applications of Artificial Intelligence 96: 103936. https://linkinghub.elsevier.com/retrieve/pii/S095219762030258X.
% Berghout, Tarek et al. 2020. “Aircraft Engines Remaining Useful Life Prediction with an Improved Online Sequential Extreme Learning Machine.” Applied Sciences 10(3): 1062. https://www.mdpi.com/2076-3417/10/3/1062.
Cita come
BERGHOUT Tarek (2024). Training a deep net with OSELM (https://www.mathworks.com/matlabcentral/fileexchange/97392-training-a-deep-net-with-oselm), MATLAB Central File Exchange. Recuperato .
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Versione | Pubblicato | Note della release | |
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1.0.0 |