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Authors: Kazuhiro Kohara and Ryo Hasegawa

Affiliation: Chiba Institute of Technology, Japan

Keyword(s): Typhoon Damage Forecasting, Self-Organizing Maps, Multiple Regression Analysis, Decision Trees.

Abstract: Damage caused by typhoons to both people and structures has decreased in Japan due to improvements of countermeasures against natural disasters, however, such damage still occurs. A typhoon warning that represents the risk posed by a typhoon with high accuracy should be issued appropriately. Thus, we propose a new typhoon warning system which forecasts the likely extent of damage associated with a typhoon towards humans and buildings. The relation between typhoon data and damage data is investigated and typhoon damage is forecast using typhoon data. Self-organizing maps (SOM), multiple regression analysis and decision trees were used for typhoon damage forecasting. We consider two types of forecasting: two-class (yes or no) and three-class (small, medium or large scale) damage forecasting. Experimental results on accuracy of two-class and three-class forecasting with SOM were 93.3% and 96.8%, respectively. The accuracy with SOM was much better than that with multiple regression and d ecision trees. We recommend a new typhoon damage forecasting method based on these results. (More)

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Paper citation in several formats:
Kohara, K. and Hasegawa, R. (2009). Typhoon Damage Forecasting with Self-Organizing Maps, Multiple Regression and Decision Trees. In Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP; ISBN 978-989-674-002-3, SciTePress, pages 106-111. DOI: 10.5220/0002254601060111

@conference{workshop anniip09,
author={Kazuhiro Kohara. and Ryo Hasegawa.},
title={Typhoon Damage Forecasting with Self-Organizing Maps, Multiple Regression and Decision Trees},
booktitle={Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP},
year={2009},
pages={106-111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002254601060111},
isbn={978-989-674-002-3},
}

TY - CONF

JO - Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP
TI - Typhoon Damage Forecasting with Self-Organizing Maps, Multiple Regression and Decision Trees
SN - 978-989-674-002-3
AU - Kohara, K.
AU - Hasegawa, R.
PY - 2009
SP - 106
EP - 111
DO - 10.5220/0002254601060111
PB - SciTePress

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