An enhanced automated machine learning model for optimizing cycle-to-cycle variation in hydrogen-enriched methanol engines

Zhu, Yizi; He, Zhixia; Xuan, Tiemin; Shao, Zhuang

doi:10.1016/j.apenergy.2024.123019

Applied Energy

2024

DOI: 10.1016/j.apenergy.2024.123019

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An enhanced automated machine learning model for optimizing cycle-to-cycle variation in hydrogen-enriched methanol engines

Yizi Zhu,

Zhixia He,

Tiemin Xuan

et al.

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An enhanced automated machine learning model for optimizing cycle-to-cycle variation in hydrogen-enriched methanol engines

Cited by 5 publications

References 49 publications

System design and thermo-economic analysis of a novel gas turbine combined cycle co-driven by methanol and solar energy

System design and thermo-economic analysis of a novel gas turbine combined cycle co-driven by methanol and solar energy

An ensemble learning algorithm for optimization of spark ignition engine performance fuelled with methane/hydrogen blends

Co-optimization and prediction of high-efficiency combustion and zero-carbon emission at part load in the hydrogen direct injection engine based on VVT, split injection and ANN

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