Historical Typhoon Search Engine Based on Track Similarity

Meng-Han Tsai, Hao-Yung Chan, Chun-Mo Hsieh, Cheng-Yu Ho, Hung-Kai Kung, Yun-Cheng Tsai and I-Cheng Cho
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Meng-Han Tsai: Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei City 10607, Taiwan
Hao-Yung Chan: Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei City 10607, Taiwan
Chun-Mo Hsieh: Department of Economics, National Taiwan University, Taipei City 10617, Taiwan
Cheng-Yu Ho: Department of Geography, National Taiwan University, Taipei City 10617, Taiwan
Hung-Kai Kung: Department of Geography, National Taiwan University, Taipei City 10617, Taiwan
Yun-Cheng Tsai: School of Big Data Management, Waishuanghsi Campus, Soochow University, Taipei City 11102, Taiwan
I-Cheng Cho: Department of Civil Engineering, National Taiwan University, Taipei City 10617, Taiwan

IJERPH, 2019, vol. 16, issue 24, 1-14

Abstract: The potential effect of a typhoon track on the extent of damage makes the track a critical factor during the emergency response phase. Historical typhoon data may provide information for decision makers to anticipate the impact of an upcoming typhoon and develop prevention strategies to reduce the damage. In our preliminary work, we proposed a track similarity algorithm and implemented a real-time search engine for past typhoon events. However, the proposed algorithm was not discussed thoroughly in the preliminary work, and the great number of historical typhoon track records slowed down the similarity calculations. In addition, the tool did not feature the option of automatically importing upcoming typhoon track predictions. This research introduces the assumption of the recentness dominance principle (RDP), explores the details of the track similarity algorithm of the preliminary work, completes the discussion of parameter setting, and developed a method to improve the efficiency of the similarity calculation. In this research, we implemented the proposed advanced methodology by developing a new information display panel featuring the ability to auto-import forecast data. The results of this study provide decision makers and the public with a concise and handy search engine for searching similar historical typhoon records.

Keywords: decision support; typhoon track similarity; search engine; user interface design (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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