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金霉素发酵过程优化调度策略研究

Keywords: 金霉素发酵,数据场聚类,效益函数,优化调度策略,滚动学习预报

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Abstract:

针对金霉素发酵过程影响优化控制的难测参数,提出了一种基于数据场聚类、模糊神经网络和滚动学习预报的优化调度策略.提取输入变量数据场聚类特征值作为模糊神经网络模型结构参数的初始值,消除人为参数选择的随机性误差,并在预测模型中加入离线数据模型修正算法.因此,提出的优化调度策略提高了对金霉素发酵过程难测变量的预测精度,增强了预报模型的鲁棒性.现场运行结果表明,提出的方案将企业金霉素生产的综合效益提高了9.12%,具有很好的应用价值.

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