Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICMLC.2010.5580923 | ICMLC |
Keywords | Field | DocType |
grey markov process,fuzzy set theory,grey statistical method,grey systems,grey features,markov process,random processes,fuzzy mathematics,water resources sustainable utilization,annual precipitation,baoding area,water resources,annual precipitation prediction,grey system theory,fuzzy features,fuzzy grey process,markov processes,precipitation,random process prediction,random process,water conservation,machine learning,probability,water | Water conservation,Markov process,Computer science,Fuzzy logic,Stochastic process,Fuzzy mathematics,Fuzzy set,Artificial intelligence,Water resources,Machine learning,Precipitation | Conference |
Volume | ISBN | Citations |
3 | 978-1-4244-6526-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li-Li Sheng | 1 | 0 | 0.68 |
| Wu-Qun Cheng | 2 | 0 | 0.34 |
| Hui Xia | 3 | 0 | 3.04 |
| Xian-Bing Wu | 4 | 0 | 0.34 |
| Xi-Ping Zhang | 5 | 0 | 0.34 |