• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.158-164
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• 2007

Supply Chain Management (SCM) system is a critical investment that can affect the competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper presents the characteristic factors of SCM system and a Fuzzy AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. This study focuses on quantitative factors, applying the fuzzy concept to various evaluative factors. The proposed model can systematically construct the objectives of SCM system selection to achieve the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.313-324
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• 2022

With the development of the economy, people's utilization of underground space are also improved, and a large number of cities have begun to build subways to relieve traffic pressure. The choice of subway station construction method is crucial. If an inappropriate construction method is selected, it will not only waste costs but also cause excessive deformation that may also threaten construction safety. In this paper, a subway station construction scheme selects model based on the AHP-fuzzy comprehensive evaluation. The rationality of the model is verified using numerical simulation and monitoring measurement data. Firstly, considering the economy and safety, a comprehensive evaluation system is established by selecting several indicators. Then, the analytic hierarchy process is used to determine the weight of the evaluation index, and the dimensionless membership in the fuzzy comprehensive evaluation method is used to evaluate the advantages and disadvantages of the construction method. Finally, the method is applied to Liaoyang east road station of Qingdao metro Line 2, and the results are verified by numerical simulation and monitoring measurement data. The results show that the model is scientific, practical and applicable.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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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.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1649-1656
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• 2017

This paper addresses the control problem of a laboratory-level 2 degree-of-freedom helicopter. The exact fuzzy model in a Takagi - Sugeno form is constructed by the sector nonlinearity technique, and is then represented as a set of uncertain linear systems. Output-tracking controller is designed in terms of linear matrix inequalities and the closed-loop stability is rigorously analyzed. Experimental evaluation shows that the proposed method is of benefit to many real industrial plants.

• Computers and Concrete
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• v.14 no.3
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• pp.233-245
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• 2014

In this paper, a rule based Mamdani type fuzzy logic model for prediction of slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes were discussed. In the model steel rebar diameters and development lengths were used as inputs. The FL model and experimental results, the coefficient of determination R2, the Root Mean Square Error were used as evaluation criteria for comparison. It was concluded that FL was practical method for predicting slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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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.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.95-101
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• 2002

This paper illustrates a new fuzzy effective load model for probabilistic and fuzzy production cost simulation of the load point of the composite power system. A model for reliability evaluation of a transmission system using the fuzzy set theory is proposed for considering the flexibility or ambiguity of capacity limitation and overload of transmission lines, which are subjective matter characteristics. A conventional probabilistic approach was also used to model the uncertainties related to the objective matters for forced outage rates of generators and transmission lines in the new model. The methodology is formulated in order to consider the flexibility or ambiguity of load forecasting as well as capacity limitation and overload of transmission lines. It is expected that the Fuzzy CMELDC (CoMposite power system Effective Load Duration Curve) proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems in a competitive environment in the future. The characteristics of this new model are illustrated by some case studies of a very simple test system.

• Journal of the Korean Institute of Navigation
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• v.12 no.2
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• pp.43-55
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• 1988

The amount of cargoes and fishery production have increased continuously during the last decade due to the great growth of the Korean economy. These increasements have made our coastal traffic congested, and the future coastal traffic is also expected to increase considerably. The increased traffic can be a cause of large sea pollution as well a s greater sea casualties us as properties and human lives, which could result in a big national loss. In order to prevent the sea casualties and promote the safety of coastal traffic, the Vessel Traffic Management System (VTMS) along the Korean coastal waterway is inevitably introduced. But, the precise evaluation is necessary required prior to the implementation of VTMS because this system necessitates a huge amount of budgets. This paper aims to propose the model of evaluation process, but the evaluation as to the urgency of establishment is not only very complicated and fuzzy but also affected by the subjectivity of human. Therefore, fuzzy integral is adopted as the mathematical model of evaluation in which decision-maker can intervence by making decision considering the calculated membership-function. Four aspects, namely, the frequency of sea-casualities, the traffic volume, the frequency fuzzy day, and the complexity of waterway are selected as the item of evaluation, and the fuzzy measure are applied to the evaluation of 8 candidated regions such as the adjacent area to the port Inchen, Kunsan, Mokpo, Wando, Yosu, Pusan, Pohang, Donghae. As a result of evaluation, the priority as to the candidated regions is obtained, and the following prior execution regions, namely, the adjacent area to the port Pusan, Yosu, Mokpo & Wando are selected by considering the present situation, but, in the long run, the VTMS should be executed in the whole coast of the nation, through the cost-effectiveness analysis.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.151-165
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• 2009

Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of its outstanding accuracy of control and forecasting area. We design a new classification model based on ANFIS and evaluate it in terms of classification accuracy. We identified ANFIS-based classification model has higher classification accuracy compared to existing classification model, C5.0 decision tree model by comparing their experimental results.

• Archives of design research
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• v.13 no.1
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• pp.131-138
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• 2000

The evaluation of design is one of the most important steps in design process. However, because in most cases, design evaluation has been disregarded in comparison with other steps and has been performed by designer's subjective judgment. there are few studies for the development of systematic methodology. In this study, we developed the method of design evaluation using the fuzzy theory and the multi-criteria dedsion making model. This method consists of two steps. The first step is to obtain relative importance weights of design evaluation criteria, and the second step is to obtain and integrate scores for design evaluation criteria. AHP(analytic hierarchy process) and fuzzy theory were applied to the first and the second step, respectively. We applied the developed method to the sensible evaluation of cellular phone design. As the result, we verified that the developed method could be effectively used in the evaluation of product design.