Prediction model of comprehensive coke ratio based on principal component analysis for sintering process

Hu, Jie; Wu, Min; Chen, Xin; Cao, Wei

doi:10.1109/chicc.2016.7553914

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…It has been observed in experimental studies that beyond 10 wt-% concentration, Al 2 O 3 acts as a network former and the incorporation of [AlO 4 ] - tetrahedral units into the [SiO 4 ] - tetrahedral units is the primary reason for viscosity increase to significant levels [58]. So, consideration to the choice of raw materials for the Ironmaking process and parameters like coke ratio in sintering [59] should be given prior to the importance to minimize alumina content in the slag system. It is also inferred from the plot that by increasing the C/S ratio from 0.8 to 1.2, the viscosity at a fixed Al 2 O 3 concentration can be decreased to a large extent.…”

Section: Resultsmentioning

confidence: 99%

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Pal,

Sahoo,

Biswajeet

et al. 2023

Ironmaking & Steelmaking

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The prediction of transport and thermodynamic properties of the blast furnace slag is an experimentally tedious job to accomplish as seen in part-1 of this work. Literature studies have shown that the use of machine learning in the determination of the properties as a function of composition is an effective technique for glassy slags. However, the application of machine learning and data science techniques in the prediction of high alumina slag properties has not been studied extensively so far. In this paper, the use of Support Vector Machine (SVM) and ExtraTrees Regressor have been done to predict the viscosity, liquidus temperature, and other thermodynamic properties of blast furnace type slag in the high alumina regime, i.e. Al 2 O 3 varying from 18 to 22 wt-%. The minimization of detrimental effects of high alumina slag has been studied by varying the MgO content and CaO/SiO 2 ratio in the range of 8-12 wt-% and 0.8-1.2, respectively. The accuracy of models has been tuned to be fairly high and the results of the prediction have been discussed with possible solutions to operate under the high alumina regime of blast furnace slag.

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Section: Resultsmentioning

confidence: 99%

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Pal,

Sahoo,

Biswajeet

et al. 2023

Ironmaking & Steelmaking

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“…According to data issued by the National Bureau of Statistics of China, Zhejiang, a province located in Eastern China, ranked fourth among all 34 administrative regions regarding regional total gross domestic product (GDP) and eighth in GDP per capita in 2022. It has the best medical resources and public health services among the 28 provinces and autonomous regions in the country, excluding the other 6 administrative regions including Beijing, Shanghai, and Hong Kong due to the incomparable size of the targeted service population [10]. However, with the epidemiological transition of the death-cause pattern from infectious diseases to noncommunicable diseases across the whole society [11], little is known about the survival burden of CAs in children younger than 5 years in Zhejiang.…”

Section: Introductionmentioning

confidence: 99%

Trend of Mortality Due to Congenital Anomalies in Children Younger Than 5 Years in Eastern China, 2012-2021: Surveillance Data Analysis

Dong,

Guo,

Wang

et al. 2024

JMIR Public Health Surveill

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Background As one of the leading causes of child mortality, deaths due to congenital anomalies (CAs) have been a prominent obstacle to meet Sustainable Development Goal 3.2. Objective We conducted this study to understand the death burden and trend of under-5 CA mortality (CAMR) in Zhejiang, one of the provinces with the best medical services and public health foundations in Eastern China. Methods We used data retrieved from the under-5 mortality surveillance system in Zhejiang from 2012 to 2021. CAMR by sex, residence, and age group for each year was calculated and standardized according to 2020 National Population Census sex- and residence-specific live birth data in China. Poisson regression models were used to estimate the annual average change rate (AACR) of CAMR and to obtain the rate ratio between subgroups after adjusting for sex, residence, and age group when appropriate. Results From 2012 to 2021, a total of 1753 children died from CAs, and the standardized CAMR declined from 121.2 to 62.6 per 100,000 live births with an AACR of –9% (95% CI –10.7% to –7.2%; P<.001). The declining trend was also observed in female and male children, urban and rural children, and neonates and older infants, and the AACRs were –9.7%, –8.5%, –8.5%, –9.2%, –12%, and –6.3%, respectively (all P<.001). However, no significant reduction was observed in children aged 1-4 years (P=.22). Generally, the CAMR rate ratios for male versus female children, rural versus urban children, older infants versus neonates, and older children versus neonates were 1.18 (95% CI 1.08-1.30; P<.001), 1.20 (95% CI 1.08-1.32; P=.001), 0.66 (95% CI 0.59-0.73; P<.001), and 0.20 (95% CI 0.17-0.24; P<.001), respectively. Among all broad CA groups, circulatory system malformations, mainly deaths caused by congenital heart diseases, accounted for 49.4% (866/1753) of deaths and ranked first across all years, although it declined yearly with an AACR of –9.8% (P<.001). Deaths due to chromosomal abnormalities tended to grow in recent years, although the AACR was not significant (P=.90). Conclusions CAMR reduced annually, with cardiovascular malformations ranking first across all years in Zhejiang, China. Future research and practices should focus more on the prevention, early detection, long-term management of CAs and comprehensive support for families with children with CAs to improve their survival chances.

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“…For example, the comprehensive carbon ratio (CCR) is used as a metric for the carbon efficiency [15][16][17]. The sintering parameters were analyzed using the principal component analysis (PCA) method, and then the back propagation neural network (BPNN) was used to predict the CCR [16]. A discrete wavelet transfer based on BPNN was built to predict the CCR [17].…”

Section: Introductionmentioning

confidence: 99%

A Cascade Prediction Model of CO/CO₂in the Sintering Process

Chen

et al. 2017

JACIII

Self Cite

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Sintering is an important production process in iron and steel metallurgy. Carbon fuel consumption accounts for about 80% of the total energy consumption in the sintering process. To enhance the efficiency of carbon fuel consumption, we need to determine the factors affecting carbon efficiency and build a model of it. In this paper, the CO/CO 2 is taken to be a measure of carbon efficiency, and a cascade predictive model is built to predict it. This model has two parts: the key state parameter submodel and the CO/CO 2 submodel. The submodels are built using particle swarm optimization-based back propagation neural networks (PSO-BPNNs). Based on the mechanism analysis, spearman's rank correlation coefficient (SRCC) and stepwise regression analysis (SRA) are used to determine the relationship between the process parameters, in order to determine the inputs of each submodel. Finally, the results of a simulation show the feasibility of the cascade model, which will serve as the basic model for the optimization and control of the carbon efficiency of the sintering process.

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Prediction model of comprehensive coke ratio based on principal component analysis for sintering process

Cited by 6 publications

References 16 publications

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Trend of Mortality Due to Congenital Anomalies in Children Younger Than 5 Years in Eastern China, 2012-2021: Surveillance Data Analysis

A Cascade Prediction Model of CO/CO₂in the Sintering Process

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Prediction model of comprehensive coke ratio based on principal component analysis for sintering process

Cited by 6 publications

References 16 publications

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects

Trend of Mortality Due to Congenital Anomalies in Children Younger Than 5 Years in Eastern China, 2012-2021: Surveillance Data Analysis

A Cascade Prediction Model of CO/CO2in the Sintering Process

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A Cascade Prediction Model of CO/CO₂in the Sintering Process