Bandyopadhyay, S, Fabian, M, Bremner, J et al. (5 more authors) (2022) Machine Learning Model using a Fiber Bragg Grating-based Sensor System to measure Battery State-of-Charge. In: Proceedings of Optical Fiber Sensors. Optical Fiber Sensors, 29 Aug - 02 Sep 2022, Virginia, USA. Optica Publishing Group ISBN 978-1-957171-14-2
Abstract
A data-driven regression model using Machine Learning (ML) coding has been developed to predict the state-of-the-charge of a battery based on a Fiber Bragg Grating-based sensor, achieving a supervised ML model accuracy of 99.95%.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Apr 2023 14:47 |
Last Modified: | 04 Apr 2023 14:47 |
Published Version: | http://dx.doi.org/10.1364/ofs.2022.w4.17 |
Status: | Published |
Publisher: | Optica Publishing Group |
Identification Number: | 10.1364/ofs.2022.w4.17 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197087 |
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