Study on Stochastic and Autoregressive Time Series Forecasting for Hydrogen Refueling Station

Study on Stochastic and Autoregressive Time Series Forecasting for Hydrogen Refueling Station

Hydrogen refueling stations are pivotal for renewable energy and carbon neutrality; however, they encounter challenges owing to equipment malfunctions. This study addresses the use of time-series forecasting techniques to predict and diagnose critical equipment failure at these stations. An analysis...

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Bibliographic Details
Main Authors: Ji-Wook Kim, Hong-In Won, Dong-Yong Park, In-Jae Kim, Jin-Woo Lee, Kyung-Duk Kim, Yoojeong Noh, Jin-Seok Jang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Autoregressive
hydrogen refueling station
probabilistic forecasting
recurrent neural network
time series forecasting
Online Access:https://ieeexplore.ieee.org/document/10359513/

Internet

https://ieeexplore.ieee.org/document/10359513/

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