Tropical cyclone forecaster integrated with case-based reasoning

James N.K. Liu, Chi Keung Simon Shiu, Jia You

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


One of the major challenges for predicting tropical cyclone intensity is that we lack the understanding of coupling relationships of physical processes governing tropical cyclone intensification. This paper presents a Java-based case-based reasoning model to assist tropical cyclone forecasters to determine the intensity change of the tropical cyclone. Cases are constructed by using the data mining algorithms to uncover the hidden relationships between physical processes and tropical cyclone intensity. We specify the domain data, definitions of features from the data, tool for data exploration, and architecture of case-based reasoning model. Preliminary results are found to be useful to forecasters when faced with some unusual problem and under different weather situations.
Original languageEnglish
Title of host publicationProceedings of the European Computing Conference
Number of pages7
Publication statusPublished - 1 Dec 2009
EventEuropean Computing Conference - Athens, Greece
Duration: 25 Sept 200727 Sept 2007

Publication series

NameLecture Notes in Electrical Engineering
Volume28 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


ConferenceEuropean Computing Conference

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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