基于数据的流程工业生产过程指标预测方法综述
发布时间：2018-08-31 11:17
【摘要】：生产过程关键指标的预测对于流程工业生产调度,安全生产和节能环保有着重要作用.目前,已有多种基于工业生产数据提出的生产过程指标预测方法,主要涉及特征(变量)选择,预测模型构建及其模型参数优化这三方面.本文分别针对以上三方面论述了基于数据的工业生产过程指标预测国内外研究现状,分析了各种方法的优缺点.最后,指出了流程工业生产过程指标预测方法在工业大数据及知识自动化等方面的未来研究方向和前景.
[Abstract]:The prediction of key indicators of production process plays an important role in production scheduling, production safety and energy saving and environmental protection in process industry. At present, there are a variety of production process index prediction methods based on industrial production data, which mainly involve the selection of characteristics (variables), the construction of prediction model and the optimization of model parameters. According to the above three aspects, this paper discusses the research status of the data based industrial production process index prediction at home and abroad, and analyzes the advantages and disadvantages of various methods. Finally, the paper points out the future research direction and prospect of the forecasting method of process index in the aspects of industrial big data and knowledge automation.
【作者单位】： 大连理工大学控制科学与工程学院;
【基金】：国家自然科学基金(61473056,61533005,61522304,U1560102) 国家科技支撑计划(2015BAF22B01) 中央高校基本科研基金(DUT16RC(3)031)资助~~
【分类号】：TP18
本文编号：2214818
[Abstract]:The prediction of key indicators of production process plays an important role in production scheduling, production safety and energy saving and environmental protection in process industry. At present, there are a variety of production process index prediction methods based on industrial production data, which mainly involve the selection of characteristics (variables), the construction of prediction model and the optimization of model parameters. According to the above three aspects, this paper discusses the research status of the data based industrial production process index prediction at home and abroad, and analyzes the advantages and disadvantages of various methods. Finally, the paper points out the future research direction and prospect of the forecasting method of process index in the aspects of industrial big data and knowledge automation.
【作者单位】： 大连理工大学控制科学与工程学院;
【基金】：国家自然科学基金(61473056,61533005,61522304,U1560102) 国家科技支撑计划(2015BAF22B01) 中央高校基本科研基金(DUT16RC(3)031)资助~~
【分类号】：TP18
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