Journal of Undergraduate Research
Evaluating hurricane intensity prediction techniques in real time
Publication Date
Fall 2011
Abstract
While the accuracy of hurricane track prediction has been improving, predicting intensity, the maximum sustained wind speed, is still a very difficult challenge. This is problematic because the destructive power of a hurricane is directly related to its intensity. In this paper, we present Prediction Intensity Interval model for Hurricanes (PIIH) which combines sophisticated data mining techniques to create an online real time model for accurate intensity predictions and we present a web-based framework to dynamically compare PIIH to operational models used by the National Hurricane Center (NHC). The created dynamic website tracks, compares, and provides visualization to facilitate immediate comparisons of prediction techniques. This paper is a work in progress paper reporting on both, new features of the PIIH model and online visualization of the accuracy of that model as compared to other techniques.
Document Type
Conference Proceeding
Keywords
Hurricane, intensity prediction, Prediction Interval, Markov chain
School or Division
Lyle School of Engineering
Disciplines
Engineering
Part of
IEEE archives pdf format
Format
DOI
10.1109/ICDMW.2011.78
Source
Third IEEE ICDM Workshop on Knowledge Discovery from Climate Data, Proceedings of the of the 2011 IEEE International Conference on Data Mining Workshops (ICDMW 2011)
Recommended Citation
Jovanovic, Vladimir; Dunham, Margaret; Hahsler, Michael; and Su, Yu, "Evaluating hurricane intensity prediction techniques in real time" (2011). Journal of Undergraduate Research. 6.
https://scholar.smu.edu/urajournal_research/6