Outputs (2)

Reinforcement Q-Learning for PDF Tracking Control of Stochastic Systems with Unknown Dynamics (2024)
Journal Article
Yang, W., Zhou, Y., Zhang, Y., & Ren, Y. (2024). Reinforcement Q-Learning for PDF Tracking Control of Stochastic Systems with Unknown Dynamics. Mathematics, 12(16), Article 2499. https://doi.org/10.3390/math12162499

Tracking control of the output probability density function presents significant challenges, particularly when dealing with unknown system models and multiplicative noise disturbances. To address these challenges, this paper introduces a novel tracki... Read More about Reinforcement Q-Learning for PDF Tracking Control of Stochastic Systems with Unknown Dynamics.

Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions (2024)
Journal Article
Liu, J., Zhang, Y., Zhou, Y., & Chen, J. (2024). Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions. Mathematics, 12(5), Article 667. https://doi.org/10.3390/math12050667

This study presents a novel event-triggered relearning framework for neural network modeling, designed to improve prediction precision in dynamic stochastic complex industrial systems under non-stationary and variable conditions. Firstly, a sliding w... Read More about Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions.