1992 Fiscal Year Final Research Report Summary
Development of an Expert System for flood Control Supporting based on Co-operating Knowledge-based Systems
| Project/Area Number |
02555118
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| Research Category |
Grant-in-Aid for Developmental 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., Civil Eng., Professor, 工学部, 教授 (30025895)
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| Co-Investigator(Kenkyū-buntansha) |
HORI Tomoharu Kyoto Univ., Civil Eng., Instructor, 工学部, 助手 (20190225)
SHIIBA Michiharu Kyoto Univ., Civil Eng., Associate Professor, 工学部, 助教授 (90026352)
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| Project Period (FY) |
1990 – 1992
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| Keywords | Flood control / Reservoir Operation / Artificial Intelligence / Expert System / Fuzzy Set Theory / Cooperative Problem Solving / Dam For Flood Control / Decision Support |
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| Research Abstract |
A flood control support environment, which is based on cooperatin knowledge-based systems, is designed. The system proposed herein has two levels of cooperation among its subsystems.
On the upper level of cooperation, a procedural knowledge system, which processes quantitative data with mathematical algorithm, is linked with an inference system, which deals with qualitative information and knowledge expressed in the form of language. They synthetically support floow control work through information processing in each system and information interchange between them.
The lower level of cooperation takes place among knowledge-based systems in the inference system. The inference system proposed here is composed of several self-contained knowledge-based systems, each of which is an expert system with an inference engine, a knowledge base and a data base. Each knowledge-based system deals with a partial issue of a flood control problem. Flood control problems, such as how much water should be released from a storage reservoir, are solved through the inference process in each knowledge-based system and the communication among them. In this study, we adopt two types of knowledge-based systems according to the information types to be processed in each system : one with an inference process based on a production system and the other with a fuzzy inference process.
The way how to imprive an expert system designed as a prototype is also investigated and the hierachical structure of knowledge-based systems is proposed. In this framework, the knowledge-based system designed above is divided into several knowledge-based systems according to the type of data used as grounds of decision and the meta knowledge-based system is inroduced to manage these systems.
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Research Products
(8 results)
