Ensemble Learning Applications in Multiple Industries: A Review DOI Creative Commons
Kuo-Yi Lin,

Chancy Huang

Information Dynamics and Applications, Journal Year: 2022, Volume and Issue: 1(1), P. 44 - 58

Published: Dec. 27, 2022

This study proposes a systematic review of the application Ensemble learning (EL) in multiple industries. aims to prevailing industries guide for future landing application. also research method based on Systematic Literature Review (SLR) address EL literature and help advance our understanding optimization. The is divided three categories by National Bureau Statistics China (NBSC): primary industry, secondary industry tertiary industry. Among existing problems industrial management systems, frequently discussed are quality control, prediction, detection, efficiency satisfaction. In addition, given huge potential various fields, gap further directions suggested. essential managers cross-disciplinary scholars lead guideline solve issues practical work, as it provided panorama domains current problems. first literature. paper has values broaden area EL, proposed novel SLR sort out

Language: Английский

Tracking hourly PM2.5 using geostationary satellite sensor images and multiscale spatiotemporal deep learning DOI Creative Commons
Zhige Wang, Ce Zhang, Su Ye

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2024, Volume and Issue: 134, P. 104145 - 104145

Published: Sept. 12, 2024

Language: Английский

Citations

0

Multiresolution Analysis of HRRR Meteorological Parameters and GOES-R AOD for Hourly PM2.5 Prediction DOI Creative Commons
Dimple Pruthi, Qingyang Zhu, Wenhao Wang

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(45), P. 20040 - 20048

Published: Nov. 1, 2024

High-resolution, comprehensive exposure data are crucial for accurately estimating the human health impact of PM

Language: Английский

Citations

0

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China DOI
Yun Hang, Qiang Pu, Qiao Zhu

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 177883 - 177883

Published: Dec. 7, 2024

Language: Английский

Citations

0

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China DOI Creative Commons
Yun Hang, Qiang Pu, Qiao Zhu

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 12, 2023

Abstract Ambient PM 2.5 pollution is recognized as a leading environmental risk factor, causing significant mortality and morbidity in China. However, the specific contributions of individual constituents remain unclear, primarily due to lack comprehensive ground monitoring network for constituents. This issue particularly critical carbonaceous species such organic carbon (OC) elemental (EC), which are known their health impacts, understanding OC/EC ratio crucial identifying sources. To address this, we developed Super Learner model integrating Multi-angle Imaging SpectroRadiometer (MISR) retrievals predict daily OC concentrations across China from 2003 2019 at 10-km spatial resolution. Our demonstrates robust predictive accuracy, evidenced by random cross-validation R² 0.84 an RMSE 4.9 μg/m³, level. Although MISR polar-orbiting instrument, its fractional aerosol data make contribution exposure model. We then use explore spatiotemporal distributions further calculate EC/OC compared regional discrepancies source over three selected regions: Beijing-Tianjin-Hebei, Fenwei Plain, Yunnan Province. observes that levels elevated Northern industrial operations central heating during season, while Yunnan, mainly contributed local forest fires fire seasons. Additionally, found likely influenced climate phenomena El Niño-Southern Oscillation. Considering change increasing severity with more frequent events, influence on formation dispersion, suggest emphasizing role future control policies. believe this study will contribute epidemiological studies OC, aiding refining public guidelines enhancing air quality management

Language: Английский

Citations

1

Ensemble Learning Applications in Multiple Industries: A Review DOI Creative Commons
Kuo-Yi Lin,

Chancy Huang

Information Dynamics and Applications, Journal Year: 2022, Volume and Issue: 1(1), P. 44 - 58

Published: Dec. 27, 2022

This study proposes a systematic review of the application Ensemble learning (EL) in multiple industries. aims to prevailing industries guide for future landing application. also research method based on Systematic Literature Review (SLR) address EL literature and help advance our understanding optimization. The is divided three categories by National Bureau Statistics China (NBSC): primary industry, secondary industry tertiary industry. Among existing problems industrial management systems, frequently discussed are quality control, prediction, detection, efficiency satisfaction. In addition, given huge potential various fields, gap further directions suggested. essential managers cross-disciplinary scholars lead guideline solve issues practical work, as it provided panorama domains current problems. first literature. paper has values broaden area EL, proposed novel SLR sort out

Language: Английский

Citations

2