Automated quality control of tropical cyclone winds through data mining

N.C Carrasco; M.-L Shyu

doi:10.1109/IRI-05.2005.1506478

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Conference proceeding

Automated quality control of tropical cyclone winds through data mining

N.C Carrasco and M.-L Shyu

IRI -2005 IEEE International Conference on Information Reuse and Integration, Conf, 2005, Vol.2005, pp.229-234

2005

DOI: https://doi.org/10.1109/IRI-05.2005.1506478

Abstract

Aircraft

Clustering algorithms

Data mining

Hurricanes

Meteorology

Oceans

Quality control

Remote sensing

Sea measurements

Tropical cyclones

The analysis of tropical cyclones (TC) depends heavily on the quality of the incoming data set. With the advances in technology, the sizes of these data sets also increase. There is a great demand for an efficient and effective unsupervised quality control tool. Towards such a demand, data mining algorithms like spatial clustering and specialized distance measures can be applied to perform this task. This paper reports our findings on the studies on utilizing a density-based clustering algorithm with three different distance measures on a series of TC data sets.

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Title: Automated quality control of tropical cyclone winds through data mining
Creators: N.C Carrasco - Cooperative Inst. for Marine & Atmos. Studies, Miami Univ., Coral Gables, FL, USA
M.-L Shyu
Publication Details: IRI -2005 IEEE International Conference on Information Reuse and Integration, Conf, 2005, Vol.2005, pp.229-234
Publisher: IEEE
Academic Unit: College of Engineering; CoE - Electrical & Computer Engineering
Language: English
Resource Type: Conference proceeding
Record Identifier: 991031620095202976