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개선된 콤플렉스 방법을 이용한 정보 Granule 기반 퍼지 시스템의 최적화
박건준,오성권 원광대학교 2003 論文集 Vol.31 No.-
본 논문은 비선형 시스템의 퍼지모델을 위해 개선된 컴플렉스 방법을 이용한 정보 Granule 기반 퍼지 시스템의 최적화를 제시한다. 퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화될 필요성이 요구된다. 제안된 퍼지모델은 HCM 클러스터링 알고리즘, 개선된 컴플렉스 방법 및 퍼지추론 방법을 이용하여 시스템 구조와 파라미터 동정을 수행한다. 세 가지 형태의 퍼지모델 추론 방법은 간략추론, 선형추론 그리고 회귀다항식에 의해 시행된다. 본 논문에서는 퍼지모델의 입력변수와 퍼지 입력 공간 분할 및 입출력 데이터의 중심값을 이용하여 후반부 다항식함수에 의한 정보 Granules 기반 구조 동정과 파라미터 동정을 통해 비선형 시스템을 표현한다. 전반부 파라미터의 동정에는 HCM 클러스터링 방법과 개선된 컴플렉스 방법을 사용하고, 후반부는 표준 HCM 클러스터링과 표준 최소자승법을 사용하여 동정한다. 그리고 학습 및 테스트 데이터의 성능결과의 상호균형을 얻기 위한 하중값을 가진 성능지수를 제시함으로써 근사화와 예측성능의 향상을 꾀한다. 제안된 비선형 모델의 성능평가를 통해 그 우수정을 보인다.
김건우,송근호,김덕환,박성준 충남대학교 수의과대학 동물의과학연구소 2004 動物醫科學硏究誌 Vol.12 No.-
A 5.2kg, 5month-old castrated male Cocker spaniel dog with 1 month history of generalized scaling, alopecic skin disease was referred to the Veterinary Medical Teaching Hospital of Chungnam National University. On physical examination, lesions were observed on entire cutaneous surface and were characterized by pustules, scales, and generalized alopecia. Skin scraping and tape strip tests of skin lesions revealed cocci and Malassezia infection was detected on external ear canal. Masses of dermatophyte spores surrounding the hair shafts were found by direct microscopic examination. Based on the result of examination and clinical signs above, generalized dermatophytosis with superficial pyoderma and Malassezia otitis externa were diagnosed. Treatment with administration of antibiotic and antifungals combined with topical antifungal cream and shampoo for more than 8weeks had a good result of controlling dermatophytosis.
편영식,이건범,박정현,요꼬이 요시유끼,여진욱,안건준,곽철훈 한국공작기계학회 2003 한국생산제조학회지 Vol.12 No.3
Any one of the high precision spindle systems and guide way systems, the high stiffness of structure, the error compensation during assembly, high accuracy control system is inevitable technology for development of high precision machine tools. Especially, among these, design of spindle system is one of the most important technologies leading high precision of machine tool and high quality of manufactured products. A high speed and high precision spindle system which will be used for final machining of ferrule, is designed considering the effect of heat, cutting torque, cutting force, and work-piece materials. The detailed design and analysis process are presented.
심재현,김유수,김건우,이병희,김지용,박성준,송근호 충남대학교 수의과대학 동물의과학연구소 2004 動物醫科學硏究誌 Vol.12 No.-
A 4-years old pointer dog was referred to the Veterinary Teaching Hospital of Chungnam National University with chief compliment of anorexia, exercise intolerance, hemoptysis, coughing and ascites. It was diagnosed as heartworm disease (class 3) by physical and laboratory examination, radiography, ultrasonography and electrocardiography. This dog was undertaken by adulticidal therapy. Normal conditions and good appetite after therapy were observed.
Design of Hard Partition-based Non-Fuzzy Neural Networks
Park, Keon-Jun,Kwon, Jae-Hyun,Kim, Yong-Kab The Institute of Internet 2012 Journal of Advanced Smart Convergence Vol.1 No.2
This paper propose a new design of fuzzy neural networks based on hard partition to generate the rules of the networks. For this we use hard c-means (HCM) clustering algorithm. The premise part of the rules of the proposed networks is realized with the aid of the hard partition of input space generated by HCM clustering algorithm. The consequence part of the rule is represented by polynomial functions. And the coefficients of the polynomial functions are learned by BP algorithm. The number of the hard partition of input space equals the number of clusters and the individual partitioned spaces indicate the rules of the networks. Due to these characteristics, we may alleviate the problem of the curse of dimensionality. The proposed networks are evaluated with the use of numerical experimentation.
The Design of Genetically Optimized Multi-layer Fuzzy Neural Networks
Park, Byoung-Jun,Park, Keon-Jun,Lee, Dong-Yoon,Oh, Sung-Kwun Korean Institute of Intelligent Systems 2004 한국지능시스템학회논문지 Vol.14 No.5
In this study, a new architecture and comprehensive design methodology of genetically optimized Multi-layer Fuzzy Neural Networks (gMFNN) are introduced and a series of numeric experiments are carried out. The gMFNN architecture results from a synergistic usage of the hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). FNN contributes to the formation of the premise part of the overall network structure of the gMFNN. The consequence part of the gMFNN is designed using PNN. The optimization of the FNN is realized with the aid of a standard back-propagation learning algorithm and genetic optimization. The development of the PNN dwells on the extended Group Method of Data Handling (GMDH) method and Genetic Algorithms (GAs). To evaluate the performance of the gMFNN, the models are experimented with the use of a numerical example.