Shi, Z., Gao, J. und Guan, X. (2025) „Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost.“, Journal of Circuits, Systems & Computers, 34(1), S. 1-24. doi:10.1142/S0218126625500355.
Chicago Manual of Style 17th edition (full note)Shi, Zhaoyi, Jun Gao, und Xin Guan. „Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost.“. Journal of Circuits, Systems & Computers 34, Nr. 1 (15. Januar 2025): 1-24. https://doi.org/10.1142/S0218126625500355.
American Psychological Association 7th editionShi, Z., Gao, J., & Guan, X. (2025). Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost. Journal of Circuits, Systems & Computers, 34(1), 1-24. https://doi.org/10.1142/S0218126625500355
Modern Language Association 9th editionShi, Z., J. Gao, und X. Guan. „Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost.“. Journal of Circuits, Systems & Computers, Bd. 34, Nr. 1, Januar 2025, S. 1-24, https://doi.org/10.1142/S0218126625500355.
ISO-690 (author-date, Deutsch)SHI, Zhaoyi, Jun GAO und Xin GUAN, 2025. Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost. Journal of Circuits, Systems & Computers. 15 Januar 2025. Bd. 34, Nr. 1, S. 1-24. DOI 10.1142/S0218126625500355