Prediction of Precipitation Based on Sliding Grey Theory and Weighted Markov Chain

被引：0

作者：

Gui, Yiqi ^{[1
]}

Choi, Hwangkyu ^{[2
]}

机构：

[1] Yangzhou Univ, Dept Comp Sci, Yangzhou, Jiangsu, Peoples R China

[2] Kangwon Natl Univ, Dept Comp Sci, Chunchon, South Korea

来源：

2018 4TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE & COMMUNICATION TECHNOLOGY (CICT) | 2018年

基金：

中国国家自然科学基金;

关键词：

weighted Markov chain; Grey theory;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Precipitation forecasting has become an important issue in our life. The purpose of this paper is to predict the precipitation in Yangzhou using Grey Theory and Weighted Markov Chain to help people in industry and life. Firstly the original data are averaged sequence for GM (1,1) and Sliding Grey Weighted-Markov model is established. Then we apply the proposed model to predict the annual precipitation from 2011 to 2015, based on annual precipitation in Yangzhou during 1981-2015. The results show that this paper proposes the model improving the accuracy of prediction.

引用

页数：5

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