Prediction of annual precipitation based on fuzzy and grey Markov process

Author

Sheng, Li-li ; Cheng, Wu-qun ; Xia, Hui ; Wu, Xian-bing ; Zhang, Xi-ping

Author_Institution

Dept. of Water Resources & Eng., Agric. Univ. of Hebei, Baoding, China

Volume

3

fYear

2010

fDate

11-14 July 2010

Firstpage

1136

Lastpage

1140

Abstract

A fuzzy and grey Markov process is established based on fuzzy mathematics and grey system theory to predict random process with fuzzy and grey features. An example of annual precipitation prediction is calculated based on the above method, and the results indicates that this method is reliable for forecasting the random process with fuzzy and grey features. The annual precipitation in Baoding area in 2007 is in the state 2, that is, the annual precipitation should be 445~664mm. The forecast result of annual precipitation provides some references for water resources sustainable utilization, meanwhile it also provides a new ideas for the research fields.

Keywords

Markov processes; fuzzy set theory; grey systems; precipitation; random processes; water resources; Baoding area; annual precipitation prediction; fuzzy features; fuzzy mathematics; grey Markov process; grey features; grey system theory; random process prediction; water resources sustainable utilization; Machine learning; Markov processes; Probability; Random processes; Water; Water conservation; Water resources; Annual precipitation; Fuzzy grey process; Grey statistical method; Markov process;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics (ICMLC), 2010 International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-6526-2

Type

conf

DOI

10.1109/ICMLC.2010.5580923

Filename

5580923