| Summary: | 碩士 === 國立交通大學 === 土木工程研究所 === 86 === Case-based reasoning (CBR) is the one of means of facilitating the development of computer program that attempts to solve problems by directly accessing the case base. The approach relies on the explicit symbolic representation of a case base based on experience. With a given case base, case-based reasoning uses a representation involving specific episodes of problem solving not only to solve a new problem, but also to learn how to solve the new problem. Based on the approach of case-based reasoning, several related research involved engineering problem solving have been studied. However, most CBR systems can only retrieve the nearest cases and can not adapt these cases to generate solution, so it is not really finish the episodes of the whole system float of CBR. In this work, a novel model is developed via integrating Esteem CBR with fuzzy synthesis approach and applied to the problem of steel structural preliminary design. Finally, a neural network based CBR, UFN, is also used to solve the problem. The results shown that the solutions generated through the novel CBR and UFN system are acceptable in engineering view.
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