Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks

doi:10.1109/ICIST.2016.7483440

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

	Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks
	Wang, Xu 1,2; Wang, Guoyin 1,2; Zhang, Xuerui2
	2016
会议日期	May 6, 2016 - May 8, 2016
会议地点	Dalian, China
DOI	10.1109/ICIST.2016.7483440
页码	366-371
通讯作者	Wang, Xu
英文摘要	Eutrophication has become a serious environment problem in many parts of the world and Chlorophyll-a concentration is one of the important parameters for the characterization of water quality, which reflects the degree of eutrophication and algae content in the water body. So establishing a forecasting model to predict the chlorophyll-a concentration in evaluation of eutrophication become more urgent. In this paper, a hybrid model of least squares support vector regression optimized by improved particle swarm optimization and radial basis function neural networks (IPSO-LSSVR-RBFNN) was proposed, which effectively modifying the forecasting accuracy by extracting the useful information in the error term of the traditional methods. A real monthly dataset that collected from a typical reservoir in China during 2010-2012 and two public datasets were used to evaluate the performance of the proposed hybrid model. From the experiment results, we can see that the proposed model of IPSO-LSSVR-RBFNN achieve a higher accuracy rate compared with other models. © 2016 IEEE.
会议录	6th International Conference on Information Science and Technology, ICIST 2016
语种	英语
内容类型	会议论文
源URL	[http://119.78.100.138/handle/2HOD01W0/4653]
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.Big Data Mining and Applications Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
推荐引用方式 GB/T 7714	Wang, Xu,Wang, Guoyin,Zhang, Xuerui. Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks[C]. 见:. Dalian, China. May 6, 2016 - May 8, 2016.