Cite
Combining hybrid metaheuristic algorithms and reinforcement learning to improve the optimal control of nonlinear continuous-time systems with input constraints.
MLA
Khalili Amirabadi, Roya, and Omid Solaymani Fard. “Combining Hybrid Metaheuristic Algorithms and Reinforcement Learning to Improve the Optimal Control of Nonlinear Continuous-Time Systems with Input Constraints.” Computers & Electrical Engineering, vol. 116, May 2024, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.compeleceng.2024.109179.
APA
Khalili Amirabadi, R., & Solaymani Fard, O. (2024). Combining hybrid metaheuristic algorithms and reinforcement learning to improve the optimal control of nonlinear continuous-time systems with input constraints. Computers & Electrical Engineering, 116, N.PAG. https://doi.org/10.1016/j.compeleceng.2024.109179
Chicago
Khalili Amirabadi, Roya, and Omid Solaymani Fard. 2024. “Combining Hybrid Metaheuristic Algorithms and Reinforcement Learning to Improve the Optimal Control of Nonlinear Continuous-Time Systems with Input Constraints.” Computers & Electrical Engineering 116 (May): N.PAG. doi:10.1016/j.compeleceng.2024.109179.