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- W4310479533 endingPage "4522" @default.
- W4310479533 startingPage "4506" @default.
- W4310479533 abstract "Abstract The sintering process, as a primary modus of the blast furnace ironmaking industry, has enormous economic value and environmental protection significance for the iron and steel enterprises. Recently, with the emergence of artificial intelligence and big data, data‐driven modelling methods in the sintering process have increasingly received the researchers' attention. But now, there is still no systematic review of the data‐driven modelling approaches in the sintering process. Therefore, in this article, we conduct a comprehensive overview and prospects on the data‐driven models for the purpose of intelligent sintering. First, the mechanism and characteristics of the sintering process are introduced and analyzed elaborately. Second, the detailed research status of the sintering process is illustrated from four aspects: key parameters prediction, control, optimization, and others. Finally, several challenges and promising modelling methods such as deep learning in the sintering process are outlined and discussed for future research." @default.
- W4310479533 created "2022-12-10" @default.
- W4310479533 creator A5022431905 @default.
- W4310479533 creator A5027269981 @default.
- W4310479533 creator A5045468770 @default.
- W4310479533 creator A5049768588 @default.
- W4310479533 creator A5053220120 @default.
- W4310479533 creator A5056678232 @default.
- W4310479533 date "2022-12-29" @default.
- W4310479533 modified "2023-10-14" @default.
- W4310479533 title "Data‐driven modelling methods in sintering process: Current research status and perspectives" @default.
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