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All Journal Jurnal Teknik ITS Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science PROZIMA (Productivity, Optimization and Manufacturing System Engineering)
Budi Santosa
Departemen Teknik Sistem Dan Industri Institut Teknologi Sepuluh Nopember Surabaya
Arts Humanities Computer Science & IT Engineering Industrial & Manufacturing Engineering

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Journal : IPTEK The Journal for Technology and Science

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Feature Selection with Support Vector Machines Applied on Tornado Detection Budi Santosa
IPTEK The Journal for Technology and Science Vol 18, No 1 (2007)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v18i1.178

Abstract

In this paper, a linear programming support vector machine which is based on L1-norm is applied to do feature selection in the tornado data set. The data is the ouputs of Weather Surveillance Radar 1998 Doppler (WSR-88D). The approach is evaluated based on the indices of probability of detection, false alarm rate, bias and Heidke skill. Tornado circulation attributes/variables derived largely from the National Severe Storms Laboratory Mesocyclone Detection Algorithm (MDA) have been investigated for their efficacy in distinguishing between mesocyclones that become tornadic from those which do not.
Co-Authors Defa Ihsan Ramadhan Dwi Smaradahana Indraloka Faldy Maulana Yuantoro Hasan Aji Prawira Jasmine Athifa Azzahra Maulana Mufti Muhamamd Merisa Khristanti Febriana Hanka