An air quality prediction method based on LSA-SVR

摘要：

1.INTRODUCTION With the development of industry,urban air pollution has become increasingly serious.In the face of increasing air pollution,forecasts of air quality are particularly important.Air quality data is highly complex nonlinear time series,and traditional linear methods are difficult to obtain good prediction results.Support vector machine regression is based on statistical machine learning methods.

关键词： Air Quality Index Forecasting Support Vector Regression Lighting Search Algorithm

作者: Chunzhi WANG Shang PAN Heng SHI Zhiwei YE Linyu YAN

作者单位: School of Computer Science,Hubei University of Technology,28 Nan Li Road,Hongshan District,Wuhan,Hubei Province,China

会议类型: 国际会议

会议名称: The 17th International Conference on Sustainable Energy Technologies(SET2018)(第17届可持续能源技术国际会议暨2018世界著名科学家来鄂讲学武汉论坛)

会议地点: 武汉

会议语种:英文

页码: 458-467

在线出版日期: 2018-08-21（万方平台首次上网日期，不代表论文的发表时间）