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- W2896351606 abstract "Environmental disturbances and system uncertainties are the main obstacles for wastewater treatment process of paper-making process. In this paper, a neural network based on on LSTM which is a neural network that can learn long-term dependencies is constructed to simulate the environment of the above process. A deep reinforcement learning method is then proposed to optimize the wastewater treatment process. With the proposed design, the control scheme could not only obtain a good performance of the control system, but also can enhance the robustness of the closed-loop system. Numerical simulations are given to demonstrate the effectiveness of the proposed method." @default.
- W2896351606 created "2018-10-26" @default.
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- W2896351606 date "2018-07-01" @default.
- W2896351606 modified "2023-09-28" @default.
- W2896351606 title "Modeling and Optimization of Paper-making Wastewater Treatment Based on Reinforcement Learning" @default.
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- W2896351606 doi "https://doi.org/10.23919/chicc.2018.8482733" @default.
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