Estimating 1-km PM2.5 concentrations based on a novel spatiotemporal parallel network STMSPNet in the Beijing-Tianjin-Hebei region DOI
Qiaolin Zeng,

Mingzheng Li,

Meng Fan

и другие.

Atmospheric Environment, Год журнала: 2024, Номер 338, С. 120796 - 120796

Опубликована: Сен. 5, 2024

Язык: Английский

IoT-based framework for digital twins in steel production: A case study of key parameter prediction and optimization for CSR DOI
Jingdong Li,

Xiaochen Wang,

Quan Yang

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер 250, С. 123909 - 123909

Опубликована: Апрель 4, 2024

Язык: Английский

Процитировано

11
CO2 emission characteristics of China VI hybrid vehicles DOI
Nan Yang, Jiaqiang Li, Chao He

и другие.

Transportation Research Part D Transport and Environment, Год журнала: 2024, Номер 135, С. 104377 - 104377

Опубликована: Сен. 4, 2024

Язык: Английский

Процитировано

5
A novel explainable stacking ensemble model for estimating design floods: A data-driven approach for ungauged regions DOI
Yousef Kanani‐Sadat, Abdolreza Safari, Mohsen Nasseri

и другие.

Advanced Engineering Informatics, Год журнала: 2025, Номер 66, С. 103429 - 103429

Опубликована: Май 8, 2025

Процитировано

0
Prediction of the viscosity of green deep eutectic solvents by constructing ensemble model based on machine learning DOI
Hai Liu,

Hongwei Xu,

Wenguang Zhu

и другие.

Chemical Engineering Science, Год журнала: 2024, Номер unknown, С. 120987 - 120987

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

3
Enhanced PM2.5 estimation across China: An AOD-independent two-stage approach incorporating improved spatiotemporal heterogeneity representations DOI Creative Commons

Q. Chen,

Kaiwen Shao,

Songlin Zhang

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 368, С. 122107 - 122107

Опубликована: Авг. 9, 2024

In China, population growth and aging have partially negated the public health benefits of air pollution control measures, underscoring ongoing need for precise PM

Язык: Английский

Процитировано

2
Estimation of PM2.5 Using Multi-Angle Polarized TOA Reflectance Data from the GF-5B Satellite DOI Creative Commons
Ruijie Zhang, Hui Chen, Ruizhi Chen

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(21), С. 3944 - 3944

Опубликована: Окт. 23, 2024

The use of satellite data to estimate PM2.5 is an appropriate approach for long-term, substantial monitoring and assessment. To PM2.5, the majority algorithms now in utilize top-of-atmosphere (TOA) reflectance or aerosol optical depth (AOD) derived from scalar data. However, there relatively little research on retrieval using multi-angle polarized With its directional polarimetric camera (DPC), Chinese new-generation Gaofen 5B (henceforth referred as GF-5B) offers a unique opportunity close this gap observation In research, we utilized TOA DPC payload applied gradient boosting machine method simulate impact angle, wavelength, polarization information accuracy retrieval. We identified optimal conditions effective estimation PM2.5. quantitative results indicated that, under these conditions, concentrations retrieved by GF-5B showed strong correlation with ground-based data, achieving R2 0.9272 RMSE 7.38 µg·m−3. By contrast, Himawari-8’s similar consisted 0.9099 7.42 µg·m−3, indicating that higher accuracy. Furthermore, study demonstrated 0.81 when compared CHAP dataset, confirming feasibility effectiveness providing support through

Язык: Английский

Процитировано

2
Development of a data-driven three-dimensional PM2.5 forecast model based on machine learning algorithms DOI Creative Commons
Zifeng Han, Tianyi Guan, Xinfeng Wang

и другие.

Environmental Technology & Innovation, Год журнала: 2024, Номер unknown, С. 103930 - 103930

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

2
Spatiotemporal continuous PM2.5 concentrations inversion based on multisource data and hybrid model DOI
Wang Li, Lili Xu, Zhiyong Li

и другие.

Опубликована: Июль 10, 2024

Язык: Английский

Процитировано

0
Estimating 1-km PM2.5 concentrations based on a novel spatiotemporal parallel network STMSPNet in the Beijing-Tianjin-Hebei region DOI
Qiaolin Zeng,

Mingzheng Li,

Meng Fan

и другие.

Atmospheric Environment, Год журнала: 2024, Номер 338, С. 120796 - 120796

Опубликована: Сен. 5, 2024

Язык: Английский

Процитировано

0