| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1997: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1996: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Research Abstract |
As well-known FEA (finite element analysis) programs, there are several general purpose codes (MARC,ABAQUS,NASTRAN,SAP etc.) implementing various multifunctionalities. In order to edit efficiently for beginners input data set for these general purpose codes, empirical knowledge support based on consulation systems, constituted with abstracted IF/THEN rules, is a method of solution, And there are recently weveral developments for expert system or design system based on the hypermedia. On the other hand, idiomatic templates of input case data are utilized as easy learning or instruction methods. Since there are various attributes related to FEA modeling, and also advanced customary knowledge is needed to sumplify or idealize physical conditions, we habe proposed a metric model of similarity based on the hamming distance, defined with vectorized attribute codes. In the interactive process of this case retrieval system, since the design of query menus is important for beginners, the synthe
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tic performance of the query process shoule be investigated. In this work, a query menu page described with the HTML and the CGI was designed and implemented. And actual retrieval, focused on selecting procedures of query keys and sorting of knowledge base, have been investigated experimentally. An retrieving model of error case was proposed based on the relation data model. The pertinence of the proposed relation table composed of the error status symbol, the contents of explanation, the reference grammar information was recognized experimentally through examples of output results for a general purpose finite element program. Moreover, since a proto-type error diagnosis system have been developed with the perl and the born-shell scripting, the advanced extendibility and the easy translatability could be performed. For knowledg aqcuisition of cases (learning model), a method of intelligent automatic generation of the retrieval menu based on the hierarchical neural network was proposed. Several examples were processed variously as the teaching patterns, and the possibility of automatic design for the user interface of retrieval system (menu pattern) was shown, and its verification was carried out. Less
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