An improved hybrid ARIMA and support vector machine model for water quality prediction

doi:10.1007/978-3-319-11740-9_38

CORC > 重庆绿色智能技术研究院 > 中国科学院重庆绿色智能技术研究院 > 大数据挖掘及应用中心

	An improved hybrid ARIMA and support vector machine model for water quality prediction
	Guo, Yishuai 1,2; Wang, Guoyin 2; Zhang, Xuerui2 ; Deng, Weihui 2
	2014
会议日期	October 24, 2014 - October 26, 2014
会议地点	Shanghai, China
DOI	10.1007/978-3-319-11740-9_38
页码	411-422
通讯作者	Wang, Guoyin
英文摘要	Traditionally, the hybrid ARIMA and support vector machine model has been often used in time series forecasting. Due to the unique variability of water quality monitoring data, the hybrid model cannot easily give perfect forecasting. Therefore, this paper proposed an improved hybrid methodology that exploits the unique strength in predicting water quality time series problems. Real data sets of water quality provided by the Ministry of Environmental Protection of People’s Republic of China during 2008-2014 were used to examine the forecasting accuracy of proposed model. The results of computational tests are very promising. © Springer International Publishing Switzerland 2014.
会议录	9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014
语种	英语
电子版国际标准刊号	16113349
ISSN号	03029743
内容类型	会议论文
源URL	[http://119.78.100.138/handle/2HOD01W0/4759]
专题	大数据挖掘及应用中心
作者单位	1.Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; 2.Institute of Electronic Information and Technology, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
推荐引用方式 GB/T 7714	Guo, Yishuai,Wang, Guoyin,Zhang, Xuerui,et al. An improved hybrid ARIMA and support vector machine model for water quality prediction[C]. 见:. Shanghai, China. October 24, 2014 - October 26, 2014.