模式识别与人工智能
Wednesday, Jan. 15, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2016, Vol. 29 Issue (2): 143-153    DOI: 10.16451/j.cnki.issn1003-6059.201602006
Papers and Reports Current Issue| Next Issue| Archive| Adv Search |
Haze Forecast Method of Selective Ensemble Based on Glowworm Swarm Optimization Algorithm
NI Zhiwei, ZHANG Chen, NI Liping
School of Management, Hefei University of Technology, Hefei 230009
Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education,Hefei University of Technology, Hefei 230009

Download: PDF (588 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  Haze is a kind of serious environmental pollution. Therefore, haze weather forecast is an effective way to minimize the negative influence of haze. A selective ensemble learning based on glowworm swarm optimization algorithm is proposed. Firstly, some individual support vector machines are trained by the mixed kernel support vector machine independently, and then some classifiers with high precision and diversity are selected by the improved discrete glowworm swarm optimization algorithm. Finally, the classification results are obtained by majority voting. The proposed algorithm is utilized to forecast haze weather in China. Experimental results show that it has higher effectiveness and feasibility.
Received: 26 March 2015     
ZTFLH: TP391  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Cite this article:   
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201602006      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2016/V29/I2/143
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn