• 한국항만학회지
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• 제10권2호
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• pp.17-29
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• 1996

It is required to consider pricing and non-pricing factors and external economy in order to achieve the objects of physical distribution system in a port. Recently, among the three factors, much attention has been paid to non-pricing factor in the system. Although physical distribution service in a port(PDSP)has been frequently mentioned in documents and literature related to port and shipping studies, few study on it has not been systematically and scientifically made due to the following problems; $\circ$ there are not proper criteria to evaluate level and quality of PDSP and as a result it is difficult to set up a unified standard for doing so. $\circ$ algorithms to evaluate problems with complex and ambiguous attributes and multiple levels in PDSP are not available. This thesis aims to establish a paradigm to evaluate PDSP and to abvance existing decision making methods to deal with complex and ambiguous problems in PDSP. To tackle the first purpose, extensive and thorough literature survey was carried out on general physical distribution service, which is a corner stone to handle PDSp. In addition, through interviews and questionnaire to the expert, it have extracted 82 factors of physical distribution service in a port. They have been classified into 6 groups by KJ method and each group defined by the expert's advice as follows; a. Potentiality b. Exactness c. safety d. Speediness e. Convenience f. Linkage Prior to the service evaluation, many kinds of its attributes must be identified on the basis of rational decision owing to complexity and ambiguity inherent in PDSP. An analytical hierarchy process (AHP) is a method to evaluate them but it is not applicable to PDSP that have property of non-additivity and overlapped attributes. Therefore, probablility measure can not be used to evaluate PDSP but fuzzy measure is required. Hierarchical fuzzy integral method, which is merged AHP with fuzzy measure, is also not effective method to evaluate attributes because it has vary complicated way to calculate fuzzy measure identification coefficient of attributes. A new evaluation algorithm has been introduced to solve problems with multi-attribute and multi-level hierarchy, which is called hierarchy fuzzy process(HFP).Analysis on ambiguous aspects of PDSP under study which is not easy to be defined is prerequisite to evaluate it. HFP is different from algorithm existed in that it clarified the relationship between fuzzy measure and probability measure adopted in AHP and that it directly calculates the family of fuzzy measure from overlapping coefficient and probability measure to treat and evaluate ambiguous and complex aspects of PDSP. A new evaluation algorithm HFP was applied to evaluate level of physical distribution service in the biggest twenty container port in the world. The ranks of the ports are as follows; 1. Rotterdam Port, 2. Hamburg Port, 3. Singapore Port, 4. Seattle Port, 5. Yokohama Port, 6. Long beach Port, 7. Oakland Port, 8. Tokyo Port, 9. Hongkong Port, 10. Kobe Port, 11. Los Angeles Port, 12. New york Port, 13. Antwerp Port, 14. Felixstowe Port, 15. Bremerhaven Port, 16. Le'Havre Port, 17. Kaoshung Port, 18. Killung Port, 19. Bangkok Port, 20. Pusan Port

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products me classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem far disposal products. In this paper, a heuristic approach fuzzy ART neural network is suggested. The modified fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its ai is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. In this paper, a heuristic approach for fuzzy ART neural network is suggested. The modified Fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its aim is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• 전기전자학회논문지
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• 제1권1호
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• pp.93-100
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• 1997

칼라 영상 분할의 한 방법으로 fuzzy C-means를 이용한 방법이 많이 연구되었으나, 이 방법은 클러스터의 개수가 정해져야 사용할 수 있는 방법이다. 분할해야 할 데이터가 많은 경우 예비 분할을 수행하여 예비 분할 되지 않는 데이터들에 대해서 상세 분할을 fuzzy C-means를 사용하여 분할 하나 예비 분할된 데이터의 클러스터 중심과 상세 분할로 만들어진 클러스터의 중심과는 연계성이 없어진다. 본 연구에서는 이것을 보완하기 위하여 차감 클러스터링을 사용하여 칼라 영상의 클러스터의 개수와 중심을 구한 후, 이것을 이용하여 영상을 예비 분할하고 중력을 가진 fuzzy C-means를 사용하여 분할되지 않은 나머지 부분과 클러스터의 중심을 최적화 시켜 분할하는 알고리듬을 제안한다. 제안된 방법의 정성적인 평가를 수행하여 본 논문에서 제시된 방법이 우수함을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4952-4975
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• 2018

An induced hesitant linguistic aggregation operator is investigated in the paper, in which, hesitant fuzzy linguistic evaluation values are associated with probabilistic information. To deal with these hesitant fuzzy linguistic information, an induced hesitant fuzzy linguistic probabilistic ordered weighted averaging (IHFLPOWA) operator is proposed, monotonicity, boundary and idempotency of IHFLPOWA are proved. Then andness, orness and the entropy of dispersion of IHFLPOWA are analyzed, which are used to characterize the weighting vector of the operator, these properties show that IHFLPOWA is extensions of the induced linguistic ordered weighted averaging operator and linguistic probabilistic aggregation operator. In this paper, IHFLPOWA is utilized to gather linguistic information and create fuzzy ontologies, and a movie fuzzy ontology as an illustrative case study is used to show the elaboration of the proposed method and comparison with the existing linguistic aggregation operators, it seems that the IHFLPOWA operator is an useful and alternative operator for dealing with hesitant fuzzy linguistic information with probabilistic information.

• 대한공간정보학회지
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• 제15권2호통권40호
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• pp.43-49
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• 2007

본 연구는 퍼지개념을 적용한 GIS 공간분석법을 도입하고 이를 통해 쓰레기 매립장 입지 평가를 수행하였다. 기존 연구는 GIS의 공간 중첩 분석법을 적용하여 입지분석이나 적지선정 등을 수행하였으나 공간 중첩분석은 보통집합의 불린 논리를 바탕으로 공간자료를 처리하였기 때문에 공간자료의 불확실성과 자료분류 기준의 부적합성을 고려하여 분석할 수 없었다. 그러므로 신뢰할 수 있는 분석결과를 제시할 수 없어 실제 문제에서 적극 활용되지 못하였다. 본 연구는 쓰레기 매립장을 대상 시설로 선정하고 객관적인 접근법으로 퍼지 공간분석 법을 적용하였으며, 구체적인 적용과정으로서 연속형 공간자료에 대한 소속함수의 정의방법과 퍼지분석을 위한 퍼지입력값의 생성, 그리고 쓰레기 매립장 입지평가를 위한 분석인자의 선정기준 및 자료분류기준을 검토하여 이것으로부터 소속함수를 결정하는 매개변수를 추출하는 방법을 제시하였다.

• 인터넷정보학회논문지
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• 제4권2호
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• pp.61-67
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• 2003

최근 섭취열량의 증가 및 운동부족으로 인한 비만이 사회적인 문제로 되었으며, 여러 가지 성인병의 위험인자로 알려져있다. 비만을 예방하고 치료하기 위해서는 우선적으로 비만평가가 이루어져야 하며, 이러한 평가에는 BMI, WHR, 허리둘레 등이 이용되고 있다. 본 논문에서는 제안되는 비만평가 시스템에서는 BMI와 허리둘레를 가지고 퍼지추론을 하여 비만을 평가하였다. 이를 위하여 BMI와 허리둘레에 대한 소속함수와 추론규칙을 결정하였으며, 추론 결과는 서술식 문장으로 나타냈다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.413-420
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• 2006

There are many Korean traditional wooden structures that have resisted successfully over more than several hundred years. However, their structural behavior is not known in engineering context yet. It is then difficult to predict how they behave against various loadings if they face. This paper is to attempt to investigate structural performance of the wooden structures using fuzzy concepts rather than definitely defined engineering formula. The fuzzy synthetic theory to a scoring method enables us to draw a representative and comprehensive value from individual quantity.

• 한국정밀공학회지
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• 제16권6호
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• pp.166-175
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• 1999

This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).

• 대한조선학회논문집
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• 제45권2호
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• pp.213-220
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• 2008

The aim of this paper is to build up the design model using ASMOD(Adaptive Spline Modeling of Observation Data) for the optimum scale of fleet, ship particulars and ship speed, etc. ASMOD, which define membership functions of fuzzy rule as B-spline basis function, represents a whole system as the sum of the sub-model. As it reduces the number of division of the space generated by the fuzzy set of input variables, it has a advantage of simplification to model structure and is efficient to represent the non-linear model.