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《工程(英文)》 >> 2019年 第5卷 第6期 doi: 10.1016/j.eng.2019.10.005

基于强化模糊认知图实现数据与知识协作的氟化铝添加量决策方法

School of Information Science and Engineering, Central South University, Changsha 410083, China

收稿日期: 2018-10-13 修回日期: 2019-01-20 录用日期: 2019-02-14 发布日期: 2019-10-16

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摘要

在铝电解过程中,添加氟化铝能降低电解质的初晶温度,从而提高电流效率。氟化铝添加量的决策是一项复杂的知识型工作,需要考虑许多相关的因素,在实际生产中主要依赖于人工经验。由于工艺人员的主观性以及铝电解槽的复杂性,基于知识或者基于数据的决策方法难以保证添加的准确性。现有的决策方法难以囊括复杂的因果关系。本文针对氟化铝添加量的决策提出了一种基于强化模糊认知图的数据与知识协作策略。在这种方法中,改进的模糊k均值和模糊决策树用于提取模糊规则,其中提取的规则用于修正专家提出的初始框架。同时,采用状态转移优化算法(STA)获取强化模糊认知图的权重。将提出的方法与已有方法进行对比,结果表明,强化模糊认知的收敛速度快于基于Hebbian学习方法、粒子群优化方法以及遗传算法。不仅如此,基于所提方法氟化铝添加量的决策准确率高于其他方法。因此,针对氟化铝添加量的决策,本文提出的方法是有效的。

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