Fulian Yuzhan Precision Technology Co., Ltd

Hong-wei Zhang

Qing-yu Wang

Cheng-lun Lee

Chen-ting Wu

Ying-ying Nie

Deng-kui Tian

Xin-di Lei

A parameter setting method acquires historical processing data, pre-processes the historical processing data to obtain sample data, and creates a trained regression algorithm using the sample data, then acquires preliminary emulated processing data and predetermined objective parameters inputted, wherein the preliminary emulated processing data and the predetermined objective parameters constitute emulated processing data. A reinforcement learning algorithm is trained with the historical processing data, emulated processing data, and the reinforcement learning algorithm; an actual objective parameter are set according to the actual reference parameters and the reinforcement learning algorithm. Scale of the training data for the reinforcement learning algorithm is greatly increased by the trained regression algorithm, which improves the accuracy of the learning algorithm. A parameter setting device, an electronic device, and a storage medium are also disclosed.

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Zhengzhou, China

Hong-wei Zhang