| Project/Area Number |
08458099
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Natural disaster science
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| Research Institution | KYOTO UNIVERSITY (1997)
Gifu University (1996) |
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Principal Investigator |
KOJIRI Toshiharu KYOTO UNIVERSITY,Disaster Prevention Research Institute Water Resources Research Center Professor, 防災研究所, 教授 (00026353)
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| Co-Investigator(Kenkyū-buntansha) |
HONJO Yusuke Gifu University Faculty of Engineering Civil Engineering Associate Professor, 工学部, 助教授 (10251852)
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| Project Period (FY) |
1996 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 1997: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1996: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | Pattern classification / Drought / Meteorological choracteristics / Hydrogical characteristics / Fuzzy set / Neural network / Equivalent variation / Drought probobility / ファジイ理論 / 多変数自己回帰モデル / ファジイ推論 |
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| Research Abstract |
In this Grant, we proposed the objective function suite to pattern classification on hydrological and meteorological events. The following results are obtained ;
i) ISODATA was introduced to classify the hydrological and metetrological data of spacial distribution of air pressure, air temperature and sea surface temperature. Similarity between feature pattern and sample one is formulated with fuzzy set, fractal and image processing theories.
ii) Relation between above events and drought situation in Japan was analyzed through fitness rate.
iii) Precipitation of drought season in Japan was estimated with fuzzy-neural network whose units were optimized by genetic algorithm (GA). Moreover GA classified Gauging stations of precipitation into several zones with same meteorological characteristics.
iv) For real-time prediction of drought situation was taken with recurrent typed-neural network to operate reservoir against severe disaster. One reservoir was applied for the data of 1994 to verify the proposed methodologies.
v) Drought damage due to global warming was estimated with the equivalent variation method by considering spatial and timely correlation with multi-point simulation method and.
vi) New approach for occurrence probability of drought event was proposed by evaluating not only total volume but also feature pattern of precipitation with pattern recognition concept.
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