• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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• pp.246-249
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• 2001

In this study we propose a technology selection model, which captures technology seeds for new business area by a fuzzy structural modeling method and then, design a model, which evaluates the validity of New Business Development plans for the selected technology seeds with regard to the properties of manufacturing, product, market, and economy as well. Finally, a fuzzy inference system is designed in order to decide the degree of success of New Business Development plans based on the preceding validity evaluation.

• Industrial Engineering and Management Systems
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• 제13권1호
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• pp.15-28
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• 2014

Evaluation of the implementation and performance of a firm's green supply chain management (GSCM) is an ongoing process. Balanced scorecard is a multi-criteria evaluation concept that highlights implementation and performance measures. The literature on the framework is abundant literature but scarce on how to build a hierarchical framework under uncertainty with dependence relations. Hence, this study proposes a hybrid approach, which includes applied interpretive structural modeling to build a hierarchical structure and uses the analytic network process to analyze the dependence relations. Additionally, this study applies the fuzzy set theory to determine linguistic preferences. Twenty dependence criteria are evaluated for a GSCM implemented firm in Taiwan. The result shows that the financial aspect and life cycle assessment are the most important performance and weighted criteria.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.720-724
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• 2009

본 논문에서는 FSM을 이용하여 기업프로젝트의 성공요인에 대한 의식구조를 분석한다. FSM은 ISM에 퍼지이론을 도입한 것으로서 다원적 가치가 복합되어 있는 시스템의 구조 인식에 보다 유효하다고 알려져 있으며, parameter p와 $\lambda$에 의해 변화되는 구조모형을 현실에 맞는 것으로 선택하도록 되어있다. 이것은 구조모형으로서의 객관적인 적합성평가를 실시하지 않은 상태에서 선택하는 것이기 때문에 선택된 구조모형이 현실에 적합하다고 판단된다 하더라도 보완적인 차원에서 구조 모형의 적합성평가를 실시하는 것이 바람직하다고 할 수 있다. 따라서 본 논문에서는 FSM을 이용하여 구한 기업프로젝트 달성을 위한 성공요인에 대한 구조모형에 대하여 구조방정식 모형분석을 이용한 적합성을 평가하여 보다 객관성 있는 구조모형을 제시하고 그 구조모형에 따라 의식구조를 분석한다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.877-884
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• 2002

This paper deals with a multi-stage TSK fuzzy modeling method by using Genetic Programming (GP). Based on the time sequence of sampling data the best structural change points of complex systems are detemined by using GP, and also the moving window is simultaneously introduced to overcome the excessive amount of calculation during the generating procedure of GP tree. Therefore, a multi-stage TSK fuzzy model that attempts to represent a complex problem by decomposing it into multi-stage sub-problems is addressed and its learning algorithm is proposed based on the Radial Basis Function (RBF) network. This approach allows us to determine the model structure and parameters by stages so that the problems ran be simplified.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.322-324
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• 2005

In this paper, we introduce the advanced Self-Organizing Fuzzy Polynomial Neural Network based on optimized FPN by evolutionary algorithm and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed model gives rise to a structurally and parametrically optimized network through an optimal parameters design available within Fuzzy Polynomial Neuron(FPN) by means of GA. Through the consecutive process of such structural and parametric optimization, an optimized and flexible the proposed model is generated in a dynamic fashion. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• 한국항해항만학회지
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• 제27권5호
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• pp.569-576
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• 2003

우리나라가 속해 있는 동북아지역은 동남아시아와 더불어 세계 물류의 중심지 및 생산공장의 역할을 수행하고 있다. 특히 동북아시아를 선도하고 있는 한국, 중국, 일본의 경우 동아시아의 물류 거점역활 선점과 글로벌기업 유치를 위하여 다양한 Free Zone제도를 제정 도입하여 활성화에 노력을 기울이고 있다. 이러한 상황에서 동 제도의 시행초기 단계에 있는 우리나라의 경우, 주변국을 벤치마킹하여 성공요인을 찾는 것이 시행착오를 줄이고 경쟁의 우위를 확보하는 지름길이 될 것이다. 한편, 주변국의 Free Zone들은 다양한 전략을 가지고 경쟁을 하고 있으나, 우리나라의 경우 자유무역지대 활성화 전략에 포함되는 구성요소간의 종속관계, 계층파악 등의 시스템 적인 차원에서의 접근은 전무한 실정이다. 따라서 본 논문은 이러한 점에 착안하여, 군산 자유무역지대(Free Trade Zone) 성공요인을 파악하고, 이를 바탕으로 하여 군산자유무역지대 활성화를 위한 구조모델을 FSM법을 사용하여 구축하는 것을 연구의 목적으로 하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.519-521
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• 1998

Fuzzy inference systems have found many applications in recent years. The fuzzy inference system design procedure is related to an expert or a skilled human operator in many fields. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. The messy genetic algorithm is used to obtain structurally optimized fuzzy neural network models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the problem of a time series estimation.

• 콘크리트학회논문집
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• 제17권6호
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• pp.1045-1051
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• 2005

For critical structures and application, where a given reliability must be met, it is necessary to account for uncertainties and variability in material properties, structural parameters affecting the corrosion process, in addition to the statistical and decision uncertainties. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters and the fuzziness of the corrosion time is determined by the fuzzy arithmetic of interval arithmetic and extension principle

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.297-300
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• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• Advances in aircraft and spacecraft science
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• 제2권3호
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• pp.263-273
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• 2015

Carbon nanotube strain sensors, or so called "fuzzy fiber" sensors have not yet been studied sufficiently. These sensors are composed of a bundle of fiberglass fibers coated with CNT through a thermal chemical vapor deposition process. The characteristics of these fuzzy fiber sensors differ from a conventional nanocomposite in that the CNTs are anchored to a substrate fiber and the CNTs have a preferential orientation due to this bonding to the substrate fiber. A numerical model was constructed to predict the strain response of a composite with embedded fuzzy fiber sensors in order to compare result with the experimental results obtained in an earlier study. A comparison of the numerical and experimental responses was conducted based on this work. The longitudinal sensor output from the model matches nearly perfectly with the experimental results. The transverse and off-axis tests follow the correct trends; however the magnitude of the output does not match well with the experimental data. An explanation of the disparity is proposed based on microstructural interactions between individual nanotubes within the sensor.