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Other ORP type . 2017
License: http://opensource.org/licenses/MIT
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Other ORP type . 2017
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Other ORP type . 2017
License: https://opensource.org/licenses/MIT
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ZENODO
Other ORP type . 2020
License: https://opensource.org/licenses/MIT
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ZENODO
Other ORP type . 2017
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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Claim

Specification of 'normal' wind turbine operating behaviour for rapid anomaly detection: through the use of machine learning algorithms

appsOther research productkeyboard_double_arrow_right Other ORP type 25 Aug 2017 English Publisher:Zenodo
Authors: Streethran, Nithiya;

doi: 10.5281/zenodo.2875804 , 10.5281/zenodo.4293919 , 10.5281/zenodo.2875796

Specification of 'normal' wind turbine operating behaviour for rapid anomaly detection: through the use of machine learning algorithms

Abstract

Specification of 'normal' wind turbine operating behaviour for rapid anomaly detection: through the use of machine learning algorithms by Nithiya Streethran (nmstreethran@gmail.com) Files from my master's dissertation, completed between May and August 2017 at Heriot-Watt University and Natural Power Consultants. https://github.com/nmstreethran/WindTurbineClassification

Keywords

python, wind turbine, operation and maintenance, machine learning, asset management, renewable energy, fault prediction

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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