Seabreeze prediction using Bayesian networks

Russell J Kennett; Kevin B Korb; Ann E Nicholson

doi:10.1007/3-540-45357-1_18

Seabreeze prediction using Bayesian networks

Russell J Kennett, Kevin B Korb, Ann E Nicholson

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

25 Citations (Scopus)

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.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining
Subtitle of host publication	5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings
Editors	David Cheung, Graham J. Williams, Qing Li
Place of Publication	Berlin Germany
Publisher	Springer
Pages	148-153
Number of pages	6
ISBN (Print)	3540419101
DOIs	https://doi.org/10.1007/3-540-45357-1_18
Publication status	Published - 2001
Event	Pacific-Asia Conference on Knowledge Discovery and Data Mining 2001 - Hong Kong, China Duration: 16 Apr 2001 → 18 Apr 2001 Conference number: 5th https://link.springer.com/book/10.1007/3-540-45357-1 (Proceedings)

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	2035
ISSN (Print)	0302-9743

Conference

Conference	Pacific-Asia Conference on Knowledge Discovery and Data Mining 2001
Abbreviated title	PAKDD 2001
Country/Territory	China
City	Hong Kong
Period	16/04/01 → 18/04/01
Internet address	https://link.springer.com/book/10.1007/3-540-45357-1 (Proceedings)

Access to Document

10.1007/3-540-45357-1_18

Cite this

Kennett, R. J., Korb, K. B., & Nicholson, A. E. (2001). Seabreeze prediction using Bayesian networks. In D. Cheung, G. J. Williams, & Q. Li (Eds.), Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings (pp. 148-153). (Lecture Notes in Artificial Intelligence; Vol. 2035). Springer. https://doi.org/10.1007/3-540-45357-1_18

Kennett, Russell J ; Korb, Kevin B ; Nicholson, Ann E. / Seabreeze prediction using Bayesian networks. Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings. editor / David Cheung ; Graham J. Williams ; Qing Li. Berlin Germany : Springer, 2001. pp. 148-153 (Lecture Notes in Artificial Intelligence).

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title = "Seabreeze prediction using Bayesian networks",

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.",

author = "Kennett, {Russell J} and Korb, {Kevin B} and Nicholson, {Ann E}",

year = "2001",

doi = "10.1007/3-540-45357-1_18",

language = "English",

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series = "Lecture Notes in Artificial Intelligence",

publisher = "Springer",

pages = "148--153",

editor = "David Cheung and Williams, {Graham J.} and Qing Li",

booktitle = "Advances in Knowledge Discovery and Data Mining",

note = "Pacific-Asia Conference on Knowledge Discovery and Data Mining 2001, PAKDD 2001 ; Conference date: 16-04-2001 Through 18-04-2001",

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Kennett, RJ, Korb, KB & Nicholson, AE 2001, Seabreeze prediction using Bayesian networks. in D Cheung, GJ Williams & Q Li (eds), Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings. Lecture Notes in Artificial Intelligence, vol. 2035, Springer, Berlin Germany, pp. 148-153, Pacific-Asia Conference on Knowledge Discovery and Data Mining 2001, Hong Kong, China, 16/04/01. https://doi.org/10.1007/3-540-45357-1_18

Seabreeze prediction using Bayesian networks. / Kennett, Russell J; Korb, Kevin B; Nicholson, Ann E.
Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings. ed. / David Cheung; Graham J. Williams; Qing Li. Berlin Germany: Springer, 2001. p. 148-153 (Lecture Notes in Artificial Intelligence; Vol. 2035).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

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N2 - 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.

AB - 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.

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DO - 10.1007/3-540-45357-1_18

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T3 - Lecture Notes in Artificial Intelligence

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EP - 153

BT - Advances in Knowledge Discovery and Data Mining

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A2 - Li, Qing

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T2 - Pacific-Asia Conference on Knowledge Discovery and Data Mining 2001

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Kennett RJ, Korb KB, Nicholson AE. Seabreeze prediction using Bayesian networks. In Cheung D, Williams GJ, Li Q, editors, Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings. Berlin Germany: Springer. 2001. p. 148-153. (Lecture Notes in Artificial Intelligence). doi: 10.1007/3-540-45357-1_18