Artificial Neural Network Based Modeling of Novel Low-carbon Energy Combustion-Reference-Cited by-同舟云学术

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Artificial Neural Network Based Modeling of Novel Low-carbon Energy Combustion

Published:2024-05-17 Issue: Volume:33 Page:324-327
ISSN:
Container-title:2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET)
language:
Short-container-title:

Author:

Tian Ling¹,Li Junxin²,Nie Yuhong³,Xiao Hua³

Affiliation:

1. Guangzhou Maritime University,Department of Public Physical Education,Guangzhou, Guangdong,China,510725

2. Hangzhou Normal University,School of Information Sciences and Technology,Hangzhou, Zhejiang,China,310000

3. Guangzhou Maritime University,School of Naval Architecture and Ocean Engineering,Guangzhou, Guangdong,China,510725

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10625771/10625773/10625821.pdf?arnumber=10625821

Reference18 articles.

1. Effects of Methanol–Ammonia Blending Ratio on Performance and Emission Characteristics of a Compression Ignition Engine

2. Emission reduction and cost-benefit analysis of the use of ammonia and green hydrogen as fuel for marine applications

3. Effects of Ammonia Substitution on Explosion Limits of Methane

4. Support vector machine

5. Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models

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