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| 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 |
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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.
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Received: 26 March 2015
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2016, Vol. 29 
