발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.5] Design and Implementation of Fuzzy Expert System for Skeletal Diagnosis Based on Korean Female Standard Body Shape |
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| 논문투고자 |
Seo-Young Lee, Kang-Hee Lee |
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| 논문내용 |
In this paper, a rule-based expert system and a fuzzy expert system for bone diagnosis are designed and implemented. Skeletal diagnosis is a method that classifies individuals according to the skin texture and characteristics of the body line. Rules are generated by analyzing the questions and answers for skeletal diagnosis studied by ICBI, Japan. The Mamdani method was used for designing rule-based expert system and fuzzy expert system. A fuzzy set is designed based on the Korean women's standards body surveyed by the National Institute of Technology and Standards of the Ministry of Trade, Industry and Energy. First, the rule-based expert system is implemented using SWISH Prolog. Second, the fuzzy expert system is designed in Python to draw conclusions. Through the final implementation of skeletal diagnosis as a fuzzy expert system, non-face-to-face diagnosis in the post-COVID era can be derived, and it is intended to help reduce errors that may occur in skeletal diagnosis. The results of a bone diagnosis provide opportunities for people who are interested in fashion and who express their identity through clothes. This paper examines related background studies and the design of expert systems for skeletal diagnosis. Based on the results, it verifies what is designed as an expert system by developing it into a fuzzy expert system. Finally, concluding remarks are followed. |
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