会议论文

Tang, XY

英文

PROCEEDINGS OF THE 2024 27 TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, CSCWD 2024

2835-639X

2024

2209-2214

27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

International Conference on Computer Supported Cooperative Work in Design

MAY 08-10, 2024

Tianjin, PEOPLES R CHINA

[Tang, Xiaoyong;Yang, Xiangyu;Liu, Wenzheng;Deng, Tan;Cao, RongHui;Tu, Zeyuan] Changsha Univ Sci & Technol, Coll Comp & Commun Engineer, Changsha, Peoples R China.^[Hu, XingJiang] Cent South Univ Forestry & Technol, Coll Environm Sci & Engn, Changsha, Peoples R China.

Shen, W Barthes, JP Luo, J Qiu, T Zhou, X Zhang, J Zhu, H Peng, K Xu, T Chen, N

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

979-8-3503-4918-4; 979-8-3503-4919-1

10.1109/CSCWD61410.2024.10580322

Natural Science Foundation of China [61972146, 62372064]

本校为其他机构

Predicting dust pollution is necessary to achieve good air quality and patient recovery. In the era of big data, there are already many machine learning algorithms for predicting the concentration of air pollutant PM2.5. However, these model methods perform poorly when dealing with massive air quality data sets and do not solve the impact of data distribution imbalance. Therefore, a multi-strategy collaborative feature selection method combining random forests and recursive feature elimination with adaptive boosting rotation forest (RFR-ABROF) algorithm is proposed. On this basis, multi-class ...