Data-driven approaches for predicting performance degradation of solid oxide fuel cells system considering prolonged operation and shutdown accumulation effect-Reference-Cited by-同舟云学术

Data-driven approaches for predicting performance degradation of solid oxide fuel cells system considering prolonged operation and shutdown accumulation effect

Published:2024-04 Issue: Volume:598 Page:234186
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Wu Xiao-long,Li Yu,Cai Shiyun,Xu Yuanwu,Hu Lingyan,Chi Bo,Peng Jingxuan,Li Xi^ORCID

Funder

National Natural Science Foundation of China

Jiangxi Provincial Natural Science Foundation

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference70 articles.

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1. Application of Multiple Linear Regression and Artificial Neural Networks in Analyses and Predictions of the Thermoelectric Performance of Solid Oxide Fuel Cell Systems;Energies;2024-08-16

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