With the rapid development of economy,air pollution caused by industrial expansion has caused serious harm to human health and social development.Therefore,establishing an effective air pollution concentration predict...With the rapid development of economy,air pollution caused by industrial expansion has caused serious harm to human health and social development.Therefore,establishing an effective air pollution concentration prediction system is of great scientific and practical significance for accurate and reliable predictions.This paper proposes a combination of pointinterval prediction system for pollutant concentration prediction by leveraging neural network,meta-heuristic optimization algorithm,and fuzzy theory.Fuzzy information granulation technology is used in data preprocessing to transform numerical sequences into fuzzy particles for comprehensive feature extraction.The golden Jackal optimization algorithm is employed in the optimization stage to fine-tune model hyperparameters.In the prediction stage,an ensemble learning method combines training results frommultiplemodels to obtain final point predictions while also utilizing quantile regression and kernel density estimation methods for interval predictions on the test set.Experimental results demonstrate that the combined model achieves a high goodness of fit coefficient of determination(R^(2))at 99.3% and a maximum difference between prediction accuracy mean absolute percentage error(MAPE)and benchmark model at 12.6%.This suggests that the integrated learning system proposed in this paper can provide more accurate deterministic predictions as well as reliable uncertainty analysis compared to traditionalmodels,offering practical reference for air quality early warning.展开更多
Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global...Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global information of high-resolution remote sensing images.However,the diversity of detailed and edge features within the same class of ground objects in high-resolution remote sensing images leads to a dispersed embedding distribution.The dispersed feature distribution enlarges feature vector angles and reduces cosine similarity,weakening the attention mechanism’s ability to identify the same class of ground objects.To address this challenge,remote sensing image information granulation transformer for semantic segmentation is proposed.The model employs adaptive granulation to extract common semantic features among objects of the same class,constructing an information granule to replace the detailed feature representation of these objects.Then,the Laplacian operator of the information granule is applied to extract the edge features of the object as represented by the information granule.In the experiments,the proposed model was validated on the Beijing Land-Use(BLU),Gaofen Image Dataset(GID),and Potsdam Dataset(PD).In particular,the model achieves 88.81%for mOA,82.64%for mF1,and 71.50%for mIoU metrics on the GID dataset.Experimental results show that the model effectively handles high-resolution remote sensing images.Our code is available at https://github.com/sjmp525/RSIGT(accessed on 16 April 2025).展开更多
The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This techniqu...The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This technique,adapted for blast furnace slag granulation using a circular seam nozzle,typically aims to produce solid slag particles sized 30–140μm,thereby allowing the utilization of slag as a resource.This study explores the atomization dynamics of liquid blast furnace slag,focusing on the effects of atomization pressure.Primary atomization is simulated using a combination of the Volume of Fluid(VOF)method and the Shear Stress Transport k-ωturbulence model,while secondary atomization is analyzed through the Discrete Phase Model(DPM).The results reveal that primary atomization progresses in three stages:the slag column transforms into an umbrella-shaped liquid film,whose leading edge fragments into particles while forming a cavity-like structure,which is eventually torn into ligaments.This primary deformation is driven by the interplay of airflow velocity in the recirculation zone and the guide tube outlet pressure(Fp).Increasing the atomization pressure amplifies airflow velocity,recirculation zone size,expansion and shock waves,though the guide tube outlet pressure variations remain irregular.Notably,at 4.5 MPa,the primary deformation is most pronounced.Secondary atomization yields finer slag particles as a result of more vigorous primary atomization.For this pressure,the smallest average particle size and the highest yield of particles within the target range(30–140μm)are achieved.展开更多
Suitable water content plays a decisive role in the granulation of sintering mixtures.Herein,a method was proposed to predict the suitable water content for effective granulation on the basis of Litster's granulat...Suitable water content plays a decisive role in the granulation of sintering mixtures.Herein,a method was proposed to predict the suitable water content for effective granulation on the basis of Litster's granulation model.The granulation effectiveness of a sintering mixture was predicted by the model,with the allowance error of±10%.The effects of the water absorption properties,particle size composition and content of adhesive particles on the suitable water content were studied.The results showed that the allowable error of prediction was within±0.5%compared to the experimentally determined suitable water content.With an increase in adhesive powder content of mixtures with higher water absorption,the suitable water content increased to achieve similar granulation effectiveness.Moreover,as the amount of concentrates increased,the suitable water content first increased and then remained steady.The influence of the water absorption characteristics of the adhesive particles on the suitable water content was less than that of their particle size composition in the mixture.展开更多
In this study,we explore the elongated granulations and stretched dark lanes within the emerging anti-Hale active region NOAA AR 12720.Utilizing high-resolution observations from the New Vacuum Solar Telescope,we disc...In this study,we explore the elongated granulations and stretched dark lanes within the emerging anti-Hale active region NOAA AR 12720.Utilizing high-resolution observations from the New Vacuum Solar Telescope,we discern a prevalence of elongated granules and stretched dark lanes associated with the emergence of new magnetic flux positioned between two primary opposing magnetic polarities.These elongated granulations and stretched dark lanes exhibit an alignment of strong transverse fields and a significant inclination angle.The endpoints of these features separate from each other,with their midpoints predominantly characterized by blueshifted signals in the photosphere.This suggests a close association between elongated granules and stretched dark lanes with the newly emerging flux.Additionally,we find that the stretched dark lanes display a more pronounced correlation with strong blueshifts and photospheric transverse magnetic fields compared to the elongated granulations.The transverse magnetic field within these stretched dark lanes reaches magnitudes of approximately 300-400 G,and the inclination angle demonstrates an“arch-like”pattern along the trajectory of the stretched dark lane.Based on these observed characteristics,we infer the presence of an emerging flux tube with an“arch-like”shape situated along the stretched dark lane.Consequently,we conclude that the stretched dark lanes likely represent manifestations of the emerging flux tube,while the elongated granulations may correspond to the gaps between the emerging flux tubes.展开更多
基金supported by General Scientific Research Funding of the Science and Technology Development Fund(FDCT)in Macao(No.0150/2022/A)the Faculty Research Grants of Macao University of Science and Technology(No.FRG-22-074-FIE).
文摘With the rapid development of economy,air pollution caused by industrial expansion has caused serious harm to human health and social development.Therefore,establishing an effective air pollution concentration prediction system is of great scientific and practical significance for accurate and reliable predictions.This paper proposes a combination of pointinterval prediction system for pollutant concentration prediction by leveraging neural network,meta-heuristic optimization algorithm,and fuzzy theory.Fuzzy information granulation technology is used in data preprocessing to transform numerical sequences into fuzzy particles for comprehensive feature extraction.The golden Jackal optimization algorithm is employed in the optimization stage to fine-tune model hyperparameters.In the prediction stage,an ensemble learning method combines training results frommultiplemodels to obtain final point predictions while also utilizing quantile regression and kernel density estimation methods for interval predictions on the test set.Experimental results demonstrate that the combined model achieves a high goodness of fit coefficient of determination(R^(2))at 99.3% and a maximum difference between prediction accuracy mean absolute percentage error(MAPE)and benchmark model at 12.6%.This suggests that the integrated learning system proposed in this paper can provide more accurate deterministic predictions as well as reliable uncertainty analysis compared to traditionalmodels,offering practical reference for air quality early warning.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)+2 种基金the Major Science and Technology Projects in Yunnan Province(202202AD080013)Sichuan Provincial Key Laboratory of Philosophy and Social Science Key Program on Language Intelligence Special Education(YYZN-2024-1)the Photosynthesis Fund Class A(ghfund202407010460).
文摘Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global information of high-resolution remote sensing images.However,the diversity of detailed and edge features within the same class of ground objects in high-resolution remote sensing images leads to a dispersed embedding distribution.The dispersed feature distribution enlarges feature vector angles and reduces cosine similarity,weakening the attention mechanism’s ability to identify the same class of ground objects.To address this challenge,remote sensing image information granulation transformer for semantic segmentation is proposed.The model employs adaptive granulation to extract common semantic features among objects of the same class,constructing an information granule to replace the detailed feature representation of these objects.Then,the Laplacian operator of the information granule is applied to extract the edge features of the object as represented by the information granule.In the experiments,the proposed model was validated on the Beijing Land-Use(BLU),Gaofen Image Dataset(GID),and Potsdam Dataset(PD).In particular,the model achieves 88.81%for mOA,82.64%for mF1,and 71.50%for mIoU metrics on the GID dataset.Experimental results show that the model effectively handles high-resolution remote sensing images.Our code is available at https://github.com/sjmp525/RSIGT(accessed on 16 April 2025).
基金the Tangshan University Doctor Innovation Fund(Project Number:1402306).
文摘The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This technique,adapted for blast furnace slag granulation using a circular seam nozzle,typically aims to produce solid slag particles sized 30–140μm,thereby allowing the utilization of slag as a resource.This study explores the atomization dynamics of liquid blast furnace slag,focusing on the effects of atomization pressure.Primary atomization is simulated using a combination of the Volume of Fluid(VOF)method and the Shear Stress Transport k-ωturbulence model,while secondary atomization is analyzed through the Discrete Phase Model(DPM).The results reveal that primary atomization progresses in three stages:the slag column transforms into an umbrella-shaped liquid film,whose leading edge fragments into particles while forming a cavity-like structure,which is eventually torn into ligaments.This primary deformation is driven by the interplay of airflow velocity in the recirculation zone and the guide tube outlet pressure(Fp).Increasing the atomization pressure amplifies airflow velocity,recirculation zone size,expansion and shock waves,though the guide tube outlet pressure variations remain irregular.Notably,at 4.5 MPa,the primary deformation is most pronounced.Secondary atomization yields finer slag particles as a result of more vigorous primary atomization.For this pressure,the smallest average particle size and the highest yield of particles within the target range(30–140μm)are achieved.
基金supported in part by the National Natural Science Foundation of China under Grant No.51804347.
文摘Suitable water content plays a decisive role in the granulation of sintering mixtures.Herein,a method was proposed to predict the suitable water content for effective granulation on the basis of Litster's granulation model.The granulation effectiveness of a sintering mixture was predicted by the model,with the allowance error of±10%.The effects of the water absorption properties,particle size composition and content of adhesive particles on the suitable water content were studied.The results showed that the allowable error of prediction was within±0.5%compared to the experimentally determined suitable water content.With an increase in adhesive powder content of mixtures with higher water absorption,the suitable water content increased to achieve similar granulation effectiveness.Moreover,as the amount of concentrates increased,the suitable water content first increased and then remained steady.The influence of the water absorption characteristics of the adhesive particles on the suitable water content was less than that of their particle size composition in the mixture.
基金supported by the National Key R&D Program of China(2019YFA0405000)the Strategic Priority Research Program of the Chinese Academy of Sciences,grant No.XDB0560000+4 种基金the National Natural Science Foundation of China(NSFC,Grant Nos.12473059,12003064,12325303,11973084,12203020,12203097,12273110,and 12003068)the Yunnan Key Laboratory of Solar Physics and Space Science(202205AG070009)the Yunnan Science Foundation of China under Nos.202301AT070347,202201AT070194,202001AU070077Yunnan Science Foundation for Distinguished Young Scholars No.202001AV070004the grant associated with a project of the Group for Innovation of Yunnan province。
文摘In this study,we explore the elongated granulations and stretched dark lanes within the emerging anti-Hale active region NOAA AR 12720.Utilizing high-resolution observations from the New Vacuum Solar Telescope,we discern a prevalence of elongated granules and stretched dark lanes associated with the emergence of new magnetic flux positioned between two primary opposing magnetic polarities.These elongated granulations and stretched dark lanes exhibit an alignment of strong transverse fields and a significant inclination angle.The endpoints of these features separate from each other,with their midpoints predominantly characterized by blueshifted signals in the photosphere.This suggests a close association between elongated granules and stretched dark lanes with the newly emerging flux.Additionally,we find that the stretched dark lanes display a more pronounced correlation with strong blueshifts and photospheric transverse magnetic fields compared to the elongated granulations.The transverse magnetic field within these stretched dark lanes reaches magnitudes of approximately 300-400 G,and the inclination angle demonstrates an“arch-like”pattern along the trajectory of the stretched dark lane.Based on these observed characteristics,we infer the presence of an emerging flux tube with an“arch-like”shape situated along the stretched dark lane.Consequently,we conclude that the stretched dark lanes likely represent manifestations of the emerging flux tube,while the elongated granulations may correspond to the gaps between the emerging flux tubes.
