- Published
- 2021-10-25
- Venue
- Progress in Energy and Combustion Science, vol. 88, pp. 100967
- Cited by
- 291
- Open access
- No free copy found
- DOI
- 10.1016/j.pecs.2021.100967
Cite this paper
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- APA 7
Aliramezani, M., Koch, C. R., & Shahbakhti, M. (2021). Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions. Progress in Energy and Combustion Science, 88, 100967. https://doi.org/10.1016/j.pecs.2021.100967
- MLA 9
Aliramezani, Masoud, et al. "Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions." Progress in Energy and Combustion Science, vol. 88, 2021, pp. 100967, https://doi.org/10.1016/j.pecs.2021.100967.
- Chicago
Aliramezani, Masoud, Charles Robert Koch, and Mahdi Shahbakhti. "Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions." Progress in Energy and Combustion Science 88 (2021): 100967. https://doi.org/10.1016/j.pecs.2021.100967.
- GOST
Aliramezani M., Koch C. R., Shahbakhti M. Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions // Progress in Energy and Combustion Science. — 2021. — Vol. 88. — P. 100967. — URL: https://doi.org/10.1016/j.pecs.2021.100967
- BibTeX
@article{aliramezani2021modeling, title = {{Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions}}, author = {Masoud Aliramezani and Charles Robert Koch and Mahdi Shahbakhti}, journal = {Progress in Energy and Combustion Science}, year = {2021}, volume = {88}, pages = {100967}, doi = {10.1016/j.pecs.2021.100967}, url = {https://doi.org/10.1016/j.pecs.2021.100967} }- RIS
TY - JOUR AU - Aliramezani, Masoud AU - Koch, Charles Robert AU - Shahbakhti, Mahdi TI - Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions JO - Progress in Energy and Combustion Science VL - 88 SP - 100967 PY - 2021 DA - 2021/10/25 DO - 10.1016/j.pecs.2021.100967 UR - https://doi.org/10.1016/j.pecs.2021.100967 ER -