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中文摘要：
雾霾目前已成为严重的环境污染问题，因此需要预测雾霾天气，最小化雾霾的负面影响．文中提出基于萤火虫群优化算法的选择性集成学习方法，首先使用混合核SVM独立训练多个个体支持向量机，然后利用改进的离散型萤火虫群优化算法选择部分精度较高、差异度较大的个体分类器参与集成，最后通过多数投票法得到最终的分类预测结果．应用文中方法预测中国雾霾天气，实验表明方法的有效性和可行性．
英文摘要：
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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