Zhong, C., Li, G., & Meng, Z. (2022). A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems. Neural Computing and Applications, 1-25. https://doi.org/10.1007/s00521-022-07277-3
ISO-690 (author-date, English)ZHONG, Changting, LI, Gang and MENG, Zeng, 2022. A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems. Neural Computing and Applications. 3 June 2022. P. 1-25. DOI 10.1007/s00521-022-07277-3.
Modern Language Association 9th editionZhong, C., G. Li, and Z. Meng. “A Hybrid teaching–learning Slime Mould Algorithm for Global Optimization and Reliability-Based Design Optimization Problems”. Neural Computing and Applications, June 2022, pp. 1-25, https://doi.org/10.1007/s00521-022-07277-3.
Mohr Siebeck - Recht (Deutsch - Österreich)Zhong, Changting/Li, Gang/Meng, Zeng: A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems, Neural Computing and Applications 2022, 1-25.
Emerald - HarvardZhong, C., Li, G. and Meng, Z. (2022), “A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems”, Neural Computing and Applications, pp. 1-25.