| Project/Area Number |
03452210
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Hydraulic engineering
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| Research Institution | KYOTO UNIVERSITY |
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Principal Investigator |
TAKASAO Takuma Kyoto Univ., Faculty of Eng., Professor, 工学部, 教授 (30025895)
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| Co-Investigator(Kenkyū-buntansha) |
TACHIKAWA Yasuto Kyoto Univ., Faculty of Eng., Instructor, 工学部, 助手 (40227088)
HORI Tomoharu Kyoto Univ., Faculty of Eng., Instructor, 工学部, 助手 (20190225)
SHIIBA Michiharu Kyoto Univ., Faculty of Eng., Assoc.Professor, 工学部, 助教授 (90026352)
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| Project Period (FY) |
1991 – 1993
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| Project Status |
Completed (Fiscal Year 1993)
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| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥5,200,000)
Fiscal Year 1993: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1992: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1991: ¥3,400,000 (Direct Cost: ¥3,400,000)
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| Keywords | Reservoir Control / Fuzzy Decision Making / Fuzzy Dynamic Programming / Drought / Long-term Forecast / Uncertainty / ファジイ理論 / ファジイシステム / ファジイ多段決定 / ファジ-理論 / ファジイDP / ファジイ回帰式 / 意思決定支援 |
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| Research Abstract |
The complexity of real time reservoir control during a drought consists of the following two aspects :
1.Long-term rainfall and runoff prediction, which is key information for drought control, is not provided with high accuracy.
2.The control strategy of the reservoir is defined by target releases and target pondages, and these two criteria become occasionally become both objective functions and constraints of the programming formulation.
In full consideration of these points, a drought control system based on fuzzy decision making is developed in this study. The system developed herein is a mathematical model of current decision making process of drought control based on mutual consent among those concerned for drought control. The characteristics of the system can be summerized as follows :
1.The transition process of the state of the reservoir is modeled as both stochastic system and fuzzy system according to the type of inflow prediction.
2.the target release and the target pondage of the reservoir are expressed by fuzzy sets because the acceptable level of the change of these criteria depends much on human subjective views.
Moreover, the relationship between the accuracy of inflow prediction and that of decision criteria is analyzed by the use of the system.
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