基于數(shù)據(jù)的流程工業(yè)生產(chǎn)過程指標(biāo)預(yù)測方法綜述
發(fā)布時間:2018-08-31 11:17
【摘要】:生產(chǎn)過程關(guān)鍵指標(biāo)的預(yù)測對于流程工業(yè)生產(chǎn)調(diào)度,安全生產(chǎn)和節(jié)能環(huán)保有著重要作用.目前,已有多種基于工業(yè)生產(chǎn)數(shù)據(jù)提出的生產(chǎn)過程指標(biāo)預(yù)測方法,主要涉及特征(變量)選擇,預(yù)測模型構(gòu)建及其模型參數(shù)優(yōu)化這三方面.本文分別針對以上三方面論述了基于數(shù)據(jù)的工業(yè)生產(chǎn)過程指標(biāo)預(yù)測國內(nèi)外研究現(xiàn)狀,分析了各種方法的優(yōu)缺點.最后,指出了流程工業(yè)生產(chǎn)過程指標(biāo)預(yù)測方法在工業(yè)大數(shù)據(jù)及知識自動化等方面的未來研究方向和前景.
[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.
【作者單位】: 大連理工大學(xué)控制科學(xué)與工程學(xué)院;
【基金】:國家自然科學(xué)基金(61473056,61533005,61522304,U1560102) 國家科技支撐計劃(2015BAF22B01) 中央高校基本科研基金(DUT16RC(3)031)資助~~
【分類號】:TP18
本文編號: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.
【作者單位】: 大連理工大學(xué)控制科學(xué)與工程學(xué)院;
【基金】:國家自然科學(xué)基金(61473056,61533005,61522304,U1560102) 國家科技支撐計劃(2015BAF22B01) 中央高校基本科研基金(DUT16RC(3)031)資助~~
【分類號】:TP18
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