Name
Abstract | ||
|---|---|---|
In this paper we examine the use of Bayesian networks (BNs) for improving weather prediction, applying them to the problem of predicting sea breezes. We compare a pre-existing Bureau of Meteorology rule-based system with an elicited BN and others learned by two data mining programs, TETRAD II [Spirtes et al., 1993] and Causal MML [Wallace and Korb, 1999]. These Bayesian nets are shown to significantly outperform the rule-based system in predictive accuracy. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-45357-1_18 | PAKDD |
Keywords | Field | DocType |
pre-existing bureau,tetrad ii,bayesian net,causal mml,bayesian network,bayesian networks,elicited bn,meteorology rule-based system,predictive accuracy,rule-based system,data mining program,seabreeze prediction,rule based system | Data mining,Weather prediction,Computer science,Bayesian network,Artificial intelligence,Machine learning,Bayesian probability | Conference |
ISBN | Citations | PageRank |
3-540-41910-1 | 16 | 1.40 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Russell J. Kennett | 1 | 16 | 1.40 |
| Kevin B. Korb | 2 | 400 | 52.03 |
| Ann E. Nicholson | 3 | 692 | 88.01 |