지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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This paper presents an effective design method for a gas identification system. The design method adopted the sequential combination between the hybrid genetic algorithms and the TSK fuzzy logic system. First, the sensor grouping method by hybrid genetic algorithms led the effective dimensional reduction as well as effective pattern analysis from a large volume of pattern dimensions. Second, the fuzzy identification sub-models allowed handling the uncertainty of the sensor data extensively. By these advantages, the proposed identification model demonstrated high accuracy rates for identifying the five different types of gases; it was confirmed throughout the experimental trials.
목차
등록된 정보가 없습니다.
참고문헌 (26)
참고문헌 신청
A. Ortega / 2000 / New pattern recognition systems designed for electronic noses / Sens. Actuators B 69 : 302 ~ 307
B. Yea / 1994 / The discrimination of many kinds of odour species using fuzzy reasoning and neural networks / Sens. Actuators A 45 : 159 ~ 165
D. C. Swanson / 2000 / Signal Processing for Intelligent Sensor Systems / Marcel Dekker, Inc.
D. T. Pham / 1995 / Genetic algorithm using gradient-reproduction operator / Electronics Lett
D. Vlachos / 1996 / Fuzzy neural networks for gas sensing / Sens. Actuators B 33 : 77 ~ 82
B. Yea / 1994 / The discrimination of many kinds of odour species using fuzzy reasoning and neural networks / Sens. Actuators A 45 : 159 ~ 165
D. C. Swanson / 2000 / Signal Processing for Intelligent Sensor Systems / Marcel Dekker, Inc.
D. T. Pham / 1995 / Genetic algorithm using gradient-reproduction operator / Electronics Lett
D. Vlachos / 1996 / Fuzzy neural networks for gas sensing / Sens. Actuators B 33 : 77 ~ 82
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