Multiple learning neural network algorithm for parameter estimation of proton exchange membrane fuel cell models-Reference-Cited by-同舟云学术

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Multiple learning neural network algorithm for parameter estimation of proton exchange membrane fuel cell models

Published:2023-02 Issue:1 Volume:2 Page:100040
ISSN:2773-1537
Container-title:Green Energy and Intelligent Transportation
language:en
Short-container-title:Green Energy and Intelligent Transportation

Author:

Zhang Yiying^ORCID,Huang Chao,Huang Hailong^ORCID,Wu Jingda^ORCID

Publisher

Elsevier BV

Reference65 articles.

1. Insights into the development of microbial fuel cells for generating biohydrogen, bioelectricity, and treating wastewater;Ahmed;Energy,2022

2. Artificial intelligence and numerical models in hybrid renewable energy systems with fuel cells: advances and prospects;Al-Othman;Energy Convers Manag,2022

3. Performance assessment and optimization of two novel cogeneration systems integrating proton exchange membrane fuel cell with organic flash cycle for low temperature geothermal heat recovery;Yu;Energy,2022

4. Application of flower pollination algorithm for enhanced proton exchange membrane fuel cell modelling;Priya;Int J Hydrogen Energy,2019

5. Evaluation of a fuel cell system designed for unmanned aerial vehicles;Santos;Energy,2022

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1. A multi-model evaluation of Enhanced Tunicate Swarm Optimization for parameter identification;Energy Reports;2024-12

2. High accuracy and adaptability of PEMFC degradation interval prediction with Informer-GPR under dynamic conditions;Energy;2024-10

3. Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm;Scientific Reports;2024-09-09

4. Implementation of Accurate Parameter Identification for Proton Exchange Membrane Fuel Cells and Photovoltaic Cells Based on Improved Honey Badger Algorithm;Micromachines;2024-07-31

5. Modelling of PEM fuel cell for parameter estimation utilizing clan co-operative based spotted hyena optimizer;Energy Conversion and Management;2024-06

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