Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580923