Predictive Modeling of Blast Furnace Gas Utilization Rate Using Different Data Pre-Processing Methods
نویسندگان
چکیده
The gas utilization rate (GUR) is an important indicator parameter for reflecting the energy consumption and smooth operation of a blast furnace (BF). In this study, original data BF are pre-processed by two methods, i.e., box plot 3? criterion, sets obtained. Then, support vector regression (SVR) used to construct prediction model based on sets, respectively. state parameters selected as input model. Gas after one hour (GUR-1h), hours (GUR-2h), three (GUR-3h) output parameters, simulation result demonstrates that using criterion pre-process raw leads better compared plot. Moreover, has best predictive effect when GUR-1h.
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ژورنال
عنوان ژورنال: Metals
سال: 2022
ISSN: ['2075-4701']
DOI: https://doi.org/10.3390/met12040535