APA (7th ed.) Citation

M, N., R, K., M, S., & M, C. (2026). A hybrid AI-genetic algorithm framework for the optimization of polymer flooding strategies: A numerical simulation-based approach. Scientific reports, 16(1), 3934. https://doi.org/10.1038/s41598-025-33874-y

Chicago Style (17th ed.) Citation

M, Nourizadeh, Khosravi R, Simjoo M, and Chahardowli M. "A Hybrid AI-genetic Algorithm Framework for the Optimization of Polymer Flooding Strategies: A Numerical Simulation-based Approach." Scientific Reports 16, no. 1 (2026): 3934. https://doi.org/10.1038/s41598-025-33874-y.

MLA (9th ed.) Citation

M, Nourizadeh, et al. "A Hybrid AI-genetic Algorithm Framework for the Optimization of Polymer Flooding Strategies: A Numerical Simulation-based Approach." Scientific Reports, vol. 16, no. 1, 2026, p. 3934, https://doi.org/10.1038/s41598-025-33874-y.