Time-series forecasting of microbial fuel cell energy generation using deep learning

Time-series forecasting of microbial fuel cell energy generation using deep learning

Soil microbial fuel cells (SMFCs) are an emerging technology which offer clean and renewable energy in environments where more traditional power sources, such as chemical batteries or solar, are not suitable. With further development, SMFCs show great promise for use in robust and affordable outdoor...

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Bibliographic Details
Main Authors: Adam Hess-Dunlop, Harshitha Kakani, Stephen Taylor, Dylan Louie, Jason Eshraghian, Colleen Josephson
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Computer Science
Subjects:
microbial fuel cell (MFC)
soil microbial fuel cells
deep learning
energy prediction
quantile regression
Long Short Term Memory Networks (LSTM)
Online Access:https://www.frontiersin.org/articles/10.3389/fcomp.2024.1447745/full
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https://www.frontiersin.org/articles/10.3389/fcomp.2024.1447745/full

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