Kaiyuan Yu
Biographic Data
| ID | 7936843 |
|---|---|
| NAME | Kaiyuan Yu |
| GIVEN NAMES | Kaiyuan |
| FAMILY NAME | Yu |
| SIGNATURE | YU K |
| AFFILIATIONS | City University of Hong Kong |
| ORCID | 0000-0003-1669-5348 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1996 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Application of a Machine Learning Method for Prediction of Urban Neighborhood-Scale Air Pollution
Urban air pollution has aroused growing attention due to its associated adverse health effects. A model which could promptly predict urban air quality with considerable accuracy is, therefore, important and will benefit the development of smart cities. However, only a computational fluid dynamics (CFD) model could better resolve the dispersion behavior within an urban canyon layer. A machine learning (ML) model using the Artificial Neural Network…
Multivariate Analysis of the Energy Dispersive X‐ray Fluorescence Results From Blue and White Chinese Porcelains
The energy dispersive X‐ray fluorescence technique was employed to study non‐destructively the surface of 66 samples of Chinese porcelain, of different periods and origins, and determine the contents of 13 chemical elements, namely, Ti, Mn, Fe, Co, Ni, Cu, Zn, Ga, Pb, Rb, Sr, Y and Zr. Principal components analysis was performed on these 13 variables, and scatter plots, incorporating the first, second and third principal components, used to study…
Non‐destructive Analysis of Jingdezhen Blue and White Porcelains
The energy dispersive X‐ray fluorescence method is used for the non‐destructive qualitative analysis of Jingdezhen blue and white porcelains, which include the imperial wares of the Yongle, Xuande, Chenghua, Jiajing and Wanli periods of the Ming dynasty, the imperial wares of the Kangxi, Yongzheng, Qianlong, Jiaqing, Daoguang and Guangxu periods of the Qing dynasty, and those of the Republic and the contemporary period. The distribution pattern o…
Non‐destructive Analysis of Jingdezhen Blue and White Porcelains
The energy dispersive X‐ray fluorescence method is used for the non‐destructive qualitative analysis of Jingdezhen blue and white porcelains, which include the imperial wares of the Yongle, Xuande, Chenghua, Jiajing and Wanli periods of the Ming dynasty, the imperial wares of the Kangxi, Yongzheng, Qianlong, Jiaqing, Daoguang and Guangxu periods of the Qing dynasty, and those of the Republic and the contemporary period. The distribution pattern o…
Non‐destructive Analysis of Jingdezhen Blue and White Porcelains
The energy dispersive X‐ray fluorescence method is used for the non‐destructive qualitative analysis of Jingdezhen blue and white porcelains, which include the imperial wares of the Yongle, Xuande, Chenghua, Jiajing and Wanli periods of the Ming dynasty, the imperial wares of the Kangxi, Yongzheng, Qianlong, Jiaqing, Daoguang and Guangxu periods of the Qing dynasty, and those of the Republic and the contemporary period. The distribution pattern o…
Multivariate Analysis of the Energy Dispersive X‐ray Fluorescence Results From Blue and White Chinese Porcelains
The energy dispersive X‐ray fluorescence technique was employed to study non‐destructively the surface of 66 samples of Chinese porcelain, of different periods and origins, and determine the contents of 13 chemical elements, namely, Ti, Mn, Fe, Co, Ni, Cu, Zn, Ga, Pb, Rb, Sr, Y and Zr. Principal components analysis was performed on these 13 variables, and scatter plots, incorporating the first, second and third principal components, used to study…
Application of a Machine Learning Method for Prediction of Urban Neighborhood-Scale Air Pollution
Urban air pollution has aroused growing attention due to its associated adverse health effects. A model which could promptly predict urban air quality with considerable accuracy is, therefore, important and will benefit the development of smart cities. However, only a computational fluid dynamics (CFD) model could better resolve the dispersion behavior within an urban canyon layer. A machine learning (ML) model using the Artificial Neural Network…
Chemistry (2 works) · Geography (2 works) · Materials Science (2 works) · Mineralogy (2 works) · Air pollution (1 work) · Air Quality and Health Impacts (1 work) · Air quality index (1 work) · Analytical Chemistry (journal) (1 work) · Archaeology (1 work) · Art (1 work)