• 한국경영과학회지
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• 제17권3호
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• pp.67-78
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• 1992

MODM (multiobjective decision-making) problem is very complex system for the analyst. The problem is more complex if the goals of each of the objective functions are expressed imprecisely. It requires suitable MODM method to deal with imprecisions. Therefore, we present a new interactive fuzzy decision making method for solving multiobjective nonlinear programming problems by assuming that the decision maker (DM) has imprecise goals that assume fuzzy linguistic variable for each of the objective functions. The imprecise goals of the DM are quantified by eliciting corresponding membership functions through the interactive with the DM out of six membership functions. After determining membership functions, in order to generate the compromise or satisficing solution which is .lambda.-pareto optimal, .lambda.-max problem is solved. The higher degree of membership is chosen to satisfy imprecise goals of all objective functions by combining the membership functions. Then, the values are the compromise or satisficing solution. On the basis of the proposed method, and interactive computer programming is written to implement man-machine interactive procedures. Our programming is a revised version of sequential unconstrained minimization technique. Finally, a numerical example illustrates various aspects of the results developed in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.12-17
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• 2004

This study is designed to grope for logical methods in the decision-making process of human beings such as creation and analysis. With this in mind, the paper worked with a process where the designers of a design team gather and analyze their opinions in a design process to decide on the HVAC system of buildings. The paper introduced the fuzzy theory, or one of the methods to quantitatively describe language values with ambiguous features, suggesting a method to determine the judgement and suggestion values of the HVAC designers with the characteristics of language variables as the values of design factors greatly influencing the HVAC system. As a result, the paper tested the possibility of the fuzzy system as a logical method to gather the judgement of HVAC designers in a stage of HVAC type selection exerting a great influence on the experience and judgement of the designers and having powerful linguistic features and to determine an appropriate HVAC type which can satisfy the suggested values of related design factors.

• 한국콘텐츠학회논문지
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• 제5권1호
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• pp.109-116
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• 2005

본 논문은 퍼지전문가회로망을 이용한 금융기관의 여신결정지원시스템이 기업의 다양한 의사결정영역에 활용될 수 있는가를 보이기 위하여, 원형시스템인 FENET-LG시스템을 개발한 후, 그 실행과 평가를 통해 유효성을 검토하였다. 여기서 퍼지전문가회로망을 이용한 여신결정 지원시스템의 원형인 FENET-LG시스템을 개발하기 위한 특정 의사결정문제영역은 금융기관의 대부결정으로 하였다. 따라서 본 논문은 금융기관의 대부결정담당자의 의사결정목적에 보다 효과적으로 이용될 수 있는 회계정보시스템을 개발하기 위하여, 퍼지이론을 바탕으로 한 대부결정 퍼지 신경회로망시스템의 원형인 FENET-LG 시스템을 개발하여 그 실행과 표본출력의 창출과정을 검토해 봄으로써, 향후 금융기관의 대부결정영역에 퍼지신경회로망을 이용한 여신결정 지원시스템이 보다 광범위하게 효과적으로 이용될 수 있음을 보여주었다.

• 한국수자원학회논문집
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• 제46권9호
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• pp.897-907
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• 2013

기후변화에 따른 도시하천의 건천화 현상은 앞으로 더욱더 심각해질 것으로 예상되고 있다. 따라서 본 연구에서는 건천화의 적응전략으로서 하수처리수 재이용을 선정하였고 어느 지영기 우선적으로 선정되어야 하는가를 결정할 수 있는 방법을 제시하였다. 평가기준은 수문학적인 요소뿐만 아니라 인문 사회적인 요소도 포함하였다. 평가치와 가중치의 불확실성을 고려하기 위해 퍼지 이론을 사용하여서 기후변화로 인해 변화된 평가치와 평가기준에 대한 가중치의 불확실성을 완화하고자 하였다. Fuzzy TOPSIS 방법을 이용하여 각 대안을 평가하였다. 또 한로 버스트한 의사결정을 위해서 통계적인 기법과 maximin, maximax, Hurwicz, equal likelihood criterion 방법을 사용하였다. 그 결과 Fuzzy TOPSIS를 통한 대안의 순위 선정과 로버스트 의사결정기법을 통해 불확실성과 순위의 애매모호함을 완화시켰다. 본 연구에서 제시한 방법은 하수처리수 재이용의 위치선정 뿐만 아니라 다양한 기후변화 시나리오를 고려한 수자원 사업의 우선순위를 결정하는데 사용될 수 있다.

• 한국산학기술학회논문지
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• 제16권11호
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• pp.7971-7977
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• 2015

본 논문은 기업의 일자리 창출 평가체계 개발을 위한 평가항목 선정과 각 평가항목의 가중치를 구함으로써 정부의 기업 일자리 창출 지원과 관련된 정책의 효과를 정량적으로 평가할 수 있는 기초 자료를 제공하고 정책수립의 객관적인 방향을 제시하고자 한다. 이를 위하여 본 연구는 응답자들의 응답에 대한 모호성을 반영하는 퍼지 다지준 의사결정법을 적용한다. 연구결과 고용의 양적 측면과 고용의 질적 측면의 가중치가 비슷하였으며, 세부적으로는 최근 3년간 연간 고용증가율, 연간 순고용규모, 전체 근로자 중 비정규직의 비율, 전체 근로자의 평균고용기간, 전체 근로자의 월평균 임금, 매출액증가율 대비 고용증가율 순으로 가중치가 높은 것으로 나타났다.

• 산업경영시스템학회지
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• 제20권43호
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• 한국멀티미디어학회논문지
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• 제16권4호
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• pp.502-509
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• 2013

정보화시대에 대학에서의 교양 컴퓨터교육과정은 컴퓨터에 대한 소양을 쌓고 정보화 사회에 능동적으로 대처할 수 있는 능력을 배양하여 생산성 향상은 물론 국가 간의 경쟁력에서 뒤지지 않게 하는데 목표를 두고 있다. 본 논문에서는 대학생을 대상으로 컴퓨터교육 만족도에 영향을 미치는 결정적인 변인의 발견 및 만족도를 분석한다. 전처리과정으로 자바 기반의 기계 학습 도구인 상관에의한 특성선택을 사용하여 최적의 변인을 선택한다. 그리고 퍼지의사결정법에 기반하여 각 변인의 가중치를 사용하여 최적의 변인을 생성하였다. 본 논문의 연구결과는 컴퓨터교육 만족도 자료의 분석에서 퍼지의사결정법을 제안하고, 재현율과 정밀도 분석에 의해 만족도 평가에 대한 정확성을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.249-254
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• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• 대한전기학회논문지:전력기술부문A
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• 제48권12호
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• pp.1479-1485
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• 1999

This paper proposes a fuzzy decision making method for power transformer protection to identify an internal fault from other transient states such as inrush, over-excitation and an external fault with current transformer (CT) saturation. In this paper, analyzing over 300 EMTP simulations of disturbances, four input variables are selected and fuzzified. At every sampling interval from half to one cycle after a disturbance, from the EMPT simulations, different fuzzy rule base is composed of twelve if-then fuzzy rules associated with their basic probability assignments for singleton- or compound-support hypotheses. Dempster's rule of combination is used to process the fuzzy rules and get the final decision. A series of test results clearly indicate that the method can identify not only an internal fault but also the other transients. The average of relay operation times is about 12(ms). The proposed method is implemented into a Digital Signal Processor (TMS320C31) and tested.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1994년도 춘계학술발표회
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• pp.55-67
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• 1994

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics ar low speed. In this paper the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's decision-making by using the FNN(Fuzzy neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS90 MK III) and represent the ship motion characteristics internally According to learning procedure both FNN controllers can tune membership functions and identify fuzzy control rules automatically The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.