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퍼지 전문가 시스템에서 적응력 있는 객체의 동적 정보처리에 관한 연구
鄭丸默 대구효성가톨릭대학교 1995 연구논문집 Vol.51 No.1
Boole 함수의 미분 및 전개 방법을 확장하고, 법-M(Modulus-M)의 수체계를 바탕으로 하여 무한다치 논리로서의 퍼지 논리함수에 대한 MacLaurin 전개의 구조적 성질을 분석한. 이러한 이론과 성질을 이용하여 전문가 시스템의 자동추론장치의 설계 및 개발에 적용될 수 있는 방법을 제안한다. In this paper, with the use of the derivatives and expansions of Boolean functions and also on the basis of the number system of Modulus-M, we propose the MacLaurin series expansions about the fuzzy logic function as infinite multivalued logic and analyze its structural properties. The theory and properties can be available in the design and development of the expert system.
러프 집합을 이용한 관계데이터베이스 모델의 구성 및 해석
정환묵,정구범 대구효성가톨릭대학교 응용과학연구소 1997 응용과학연구논문집 Vol.5 No.-
In this paper, we construct rough relational database model using approximation concepts of rough set. Also, we analyze the relation between objects, attributes and attribute values and, propose the method that can generate flexible retrieval results.
정환묵,박미경 대구효성가톨릭대학교 응용과학연구소 1998 응용과학연구논문집 Vol.6 No.2
Since the multiple valued logic is compare with two-valued logic, it is PC high speed processing and increasing information density greatly in logic networks. In this paper, we represent the multiple-valued that gray level necessary image process the benefit of multiple-valued logic.
鄭丸默,卞成熙 대구효성가톨릭대학교 1993 연구논문집 Vol.46 No.1
The fuzzy input information is determined interval values using fuzzy threshold functions. In this paper, we present truth table that is a set of values from fuzzy threshold function. The truth table which derived from a rule table is represented by the fuzzy logic function. We propose an inference method that use variations of fuzzy logic function.
鄭丸默 대구효성가톨릭대학교 1987 연구논문집 Vol.35 No.1
Using the concepts of the differential of Boolean functions, we are going to analyze the structure of Boolean function and to expand the integer multiple valued logic functon and symbolic multiple valued logic functions in this thesis. The derivatives and expansions of Boolean functions are quite often used in many field, especially, in the design of networks and fault detection of computers. We analyze the expansion methods of Boolean functions and do preparation for the differential and ezpansion of multiple valued logic functions. Based on the number system of Modulus-M, we study the behavior and the eapansion methods of multiple valued logic functions. Finally, we symbolize the behavior and study the expansion methods of multiple valued logic functions.
최성혜,정환묵 대구효성가톨릭대학교 응용과학연구소 1993 응용과학연구논문집 Vol.2 No.-
In this paper, we study the fuzzy logic function that are represent a infinite multi-valued logic function. The infinite multi-valued logic function takes a truth value of proposition in fuzzy set of close interval[0,1]. Assuming that the Boolean function is the number system of modulus-2, the infinite multi-valued logic fouction is expanded the number system of modulus-M. Using the concept off the differential of extended Boolean function, we study of the properties and differentiations of fuzzy logic function, the structure of the function is analyzed. Finally, it shown that the proposed fuzzy logic function is an efficient rule selection method for fuzzy reasoning.
정환묵(Hwan-Mook Chung) 한국지능시스템학회 2009 한국지능시스템학회논문지 Vol.19 No.1
인간의 감성은 애매하고 외부로 부터의 지극에 따리 다양하게 변화한다. Plutchik은 기본적인 패턴을 8가지 행동 패턴으로 분류한 감성 모델을 제시하고, 또 순수감성의 조합으로부터 혼합 감성을 추론하였다. 본 논문에서는 다치 논리함수의 차분의 성질을 이용한 다치 논리 오토마타 모델을 이용하여 Plutchik의 감성 모델을 처리할 수 있는 방법을 제안한다. 여기서 제안된 감성처리 모델은 감성 데이터 해석과 처리에 널리 활용될 수 있을 것이다. Usually, human emotions are vague and change diversely on the basis of the stimulus [Tom the outside. Plutchik classified the fundamental behavioral patterns into eight patterns, named each of them a genuine emotion, and furthermore suggested mixed emotions using a combination of genuine emotions. In this paper, we propose a method for processing Plutchik's emotion model using Multiple Valued Logic(MVL) Automata Model which utilizes the properties of difference in Multiple Valued Logic functions. This proposed emotion processing model can be widely applied to the analysis and processing of emotion data.
러프-신경망과 x² 검정에 의한 효율적인 의사결정지원시스템
정환묵(Chung Hwan Mook),피수영(Pi Su Young),최경옥(Choi Kyoung Oak) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.8
In decision-making, information is the thing manufactured as the useful type for decision-making. We can improve the efficiently of decision-making by elimination of unnecessary information. Rough set is the theory that can classify and reduce the unnecessary attributes. But the reduction process of rough set becomes more complex according to the number of attribute and tuple. After elimination of the dispensable attributes using x^2 and rough set, the indispensable attributes are used for the units of input layers in neural network. This rough-neural network can support mpre correct decision-making of neural network.