Application of Machine Learning to Gasoline Direct Injection Systems: Towards a Data-Driven Development-Reference-Cited by-同舟云学术

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Application of Machine Learning to Gasoline Direct Injection Systems: Towards a Data-Driven Development

Published:2020-12 Issue: Volume: Page:
ISSN:
Container-title:2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)
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Author:

Botticelli Massimiliano,Hellmann Robin,Jochmann Paul,Georg Stapf Karl,Schunemann Erik

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9356100/9356131/09356238.pdf?arnumber=9356238

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Impact of Injection Valve Condition on Data-driven Prediction of Key Combustion Parameters Based on an Intelligent Diesel Fuel Injector for Large Engine Applications;SAE Technical Paper Series;2024-04-09

2. Novel method for temperature prediction in rotary kiln process through machine learning and CFD;Powder Technology;2024-04

3. Application of Levenberg-Marquardt Algorithm in Neural Network Based Actual Engine Torque Estimation and Monitoring;2023 IEEE Pune Section International Conference (PuneCon);2023-12-14

4. A data-driven approach for the quick prediction of in-furnace phenomena of pulverized coal combustion in an ironmaking blast furnace;Chemical Engineering Science;2022-10

5. AI-Driven Gasoline Direct Injection Development: A Knowledge-Discovery Framework for Comprehensible Evaluations of Complex Physical Phenomena;Proceedings;2021

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