As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimens...As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimension of influencing factors,and a reasonable and reliable prediction model of element yield is established.Based on the constraint conditions such as target cost function constraint,yield constraint and non-negative constraint,linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements.The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills,which is of positive significance for improving the market competitiveness of steel mills,reducing waste discharge and protecting the environment.展开更多
Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of tre...Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.展开更多
针对澧阳平原西部高硒低重金属天然绿色富硒土地的形成机制,运用绝对主成分得分-多元线性回归(absolute principal component score-multiple linear regression,APCS-MLR)模型,对表层土壤中Se和Cd等主要重金属元素的来源及其贡献率进...针对澧阳平原西部高硒低重金属天然绿色富硒土地的形成机制,运用绝对主成分得分-多元线性回归(absolute principal component score-multiple linear regression,APCS-MLR)模型,对表层土壤中Se和Cd等主要重金属元素的来源及其贡献率进行定量解析,并结合地统计学方法,深入分析不同来源元素的分布特征。结果表明:研究区域土壤整体呈现良好的环境质量特征;烟花爆竹、非金属建材工业活动及相关的交通运输业对土壤中As、Cd、Cr、Ni、Cu、Pb、Zn等元素的含量水平产生了提升作用,但是影响范围和程度可控;研究区西部物源区的高硒含量与高Se/Cd比值是本区形成全国硒含量最高的天然绿色富硒土壤的关键因素;研究区长期的水稻种植显著增加了土壤中的硒次生富集,成为维持全域高Se/Cd比的核心补充机制。展开更多
We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric...We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric and the nonparametric components proposed. In the final of this paper, as a result, we got the variance decomposition of the model and establish the asymptotic convergence rate for estimator.展开更多
High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters ...High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters analyzed were collected monthly from January 2021 to December 2021.Multivariate statistical techniques,such as the absolute principal component score-multiple linear regression model(APCS-MLR),correlation analysis,and analysis of variance were used to identify and quantify the potential sources or factors affecting water quality and to analyze the spatial-temporal variation in water quality.The water quality indices(WQIs),ranging from 67.96 to 70.67,showed that the water quality was at an intermediate level in the estuaries during both the flood and nonflood seasons.The concentrations of total phosphorus(TP),ammonia N(AN),and organic pollutants were greater in the Haihe River Basin than in the Liaohe River and Huanghe-Huaihe River Basins.The concentration of total nitrogen(TN)in the Haihe River Basin was lower than that in the Liaohe River and Huanghe-Huaihe River Basins.Heavy metal concentrations in the Liaohe River Basin were greater than those in the Haihe River and Huanghe-Huaihe River Basins.The annual mean concentrations of AN in the estuaries of the Haihe,Liaohe,and Huanghe(Yellow)rivers exhibited significant decreasing trends from 2013 to 2022,but no significant decreasing trends were found for permanganate index(COD_(Mn))or the TP.The concentrations of TN and AN were lower in the flood season than in the nonflood season,and the TP concentration was greater in the flood season than in the nonflood season.However,the concentrations of organic pollutants did not exhibit significant differences.Domestic sewage and industrial wastewater,substance exchange between air and water,nonpoint sources from rural and urban areas,and aquaculture wastewater were the major sources or factors responsible for water pollution in the estuaries.展开更多
文摘As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimension of influencing factors,and a reasonable and reliable prediction model of element yield is established.Based on the constraint conditions such as target cost function constraint,yield constraint and non-negative constraint,linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements.The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills,which is of positive significance for improving the market competitiveness of steel mills,reducing waste discharge and protecting the environment.
文摘Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.
文摘针对澧阳平原西部高硒低重金属天然绿色富硒土地的形成机制,运用绝对主成分得分-多元线性回归(absolute principal component score-multiple linear regression,APCS-MLR)模型,对表层土壤中Se和Cd等主要重金属元素的来源及其贡献率进行定量解析,并结合地统计学方法,深入分析不同来源元素的分布特征。结果表明:研究区域土壤整体呈现良好的环境质量特征;烟花爆竹、非金属建材工业活动及相关的交通运输业对土壤中As、Cd、Cr、Ni、Cu、Pb、Zn等元素的含量水平产生了提升作用,但是影响范围和程度可控;研究区西部物源区的高硒含量与高Se/Cd比值是本区形成全国硒含量最高的天然绿色富硒土壤的关键因素;研究区长期的水稻种植显著增加了土壤中的硒次生富集,成为维持全域高Se/Cd比的核心补充机制。
文摘We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric and the nonparametric components proposed. In the final of this paper, as a result, we got the variance decomposition of the model and establish the asymptotic convergence rate for estimator.
基金Supported by the National Natural Science Foundation of China(No.41571479)。
文摘High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters analyzed were collected monthly from January 2021 to December 2021.Multivariate statistical techniques,such as the absolute principal component score-multiple linear regression model(APCS-MLR),correlation analysis,and analysis of variance were used to identify and quantify the potential sources or factors affecting water quality and to analyze the spatial-temporal variation in water quality.The water quality indices(WQIs),ranging from 67.96 to 70.67,showed that the water quality was at an intermediate level in the estuaries during both the flood and nonflood seasons.The concentrations of total phosphorus(TP),ammonia N(AN),and organic pollutants were greater in the Haihe River Basin than in the Liaohe River and Huanghe-Huaihe River Basins.The concentration of total nitrogen(TN)in the Haihe River Basin was lower than that in the Liaohe River and Huanghe-Huaihe River Basins.Heavy metal concentrations in the Liaohe River Basin were greater than those in the Haihe River and Huanghe-Huaihe River Basins.The annual mean concentrations of AN in the estuaries of the Haihe,Liaohe,and Huanghe(Yellow)rivers exhibited significant decreasing trends from 2013 to 2022,but no significant decreasing trends were found for permanganate index(COD_(Mn))or the TP.The concentrations of TN and AN were lower in the flood season than in the nonflood season,and the TP concentration was greater in the flood season than in the nonflood season.However,the concentrations of organic pollutants did not exhibit significant differences.Domestic sewage and industrial wastewater,substance exchange between air and water,nonpoint sources from rural and urban areas,and aquaculture wastewater were the major sources or factors responsible for water pollution in the estuaries.
