Daily PM2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm.

@article{Sun2017DailyPC,
  title={Daily PM2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm.},
  author={Wei Sun and Jingyi Sun},
  journal={Journal of environmental management},
  year={2017},
  volume={188},
  pages={144-152}
}
Increased attention has been paid to PM2.5 pollution in China. Due to its detrimental effects on environment and health, it is important to establish a PM2.5 concentration forecasting model with high precision for its monitoring and controlling. This paper presents a novel hybrid model based on principal component analysis (PCA) and least squares support vector machine (LSSVM) optimized by cuckoo search (CS). First PCA is adopted to extract original features and reduce dimension for input… CONTINUE READING

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