Daily PM_2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm

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• 作者：Wei Sun ^{bdsunwei@126.com} ; Jingyi Sun ; ^{sunjingyi0224@126.com}
• 关键词：PM2.5 ; Concentration forecasting ; PCA ; LSSVM ; CS
• 刊名：Journal of Environmental Management
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：188
• 期：Complete
• 页码：144-152
• 全文大小：1233 K
• 卷排序：188

文摘

PCA is adopted to extract original features and reduce dimension for input selection. LSSVM model is firstly proposed for PM2.5 concentration prediction. The novel hybrid model PCA-CS-LSSVM outperforms single LSSVM and GRNN models in terms of prediction precision. The model presents strong potential to be applied to air quality forecasting systems.