• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.789-799
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• 2014

This study presented how to evaluate the inland inundation risk considering the characteristics of inland flood. Fuzzy AHP (Analytic Hierarchy Process), which can deal with the uncertainty or ambiguousness of the decision-making process, was used to estimate the inundation risk. The criteria used for inland inundation risk include the physical index, social index and inland flood. Each index contains three detailed indicators then total nine indicators were employed in this study. The inundation risk evaluation was carried out for each node (manhole) within the drainage system, not to the administrative extent, which enabled us to point out nodes with high risk. The proposed Fuzzy AHP was applied to Geoje district in Busan. The results indicated that the junction of Oncheoncheon and Geojecheon has high risk which is consistent with the fact that this junction has already experienced floods in the past. The proposed method can be used for evaluating inland inundation risk and preparing flood prevention plans in inland flood-prone urban areas.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.275-285
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• 2004

This paper aims to construct an effective decision making model on selection of product design in product development using fuzzy AHP technique. It is expected that this paper contributes to enhancement of company's market competitiveness by shortening the lead time to develop a new product and minimize initial investment. The proposed model using fuzzy AHP enables quick decision making by integrating and analyzing all customer requirements related to a product. In addition, it can deal with vagueness and uncertainty of decision making process using fuzzy set theory. Decision making processes for evaluating the best selection of product design are also constructed to describe the exact concept of development. A tennis racket is shown as an example. The proposed model is expected to be applied in various fields of managerial decision making processes as well as of product development process.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.347-353
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• 2019

Recent recommendation systems are developing toward the utilization of high-dimensional data. However, high-dimensional data can increase algorithm complexity by expanding dimensions and be lower the accuracy of recommended items. In addition, it can cause the problem of data sparsity and make it difficult to provide users with proper recommended items. This study proposed an algorithm that classify users' subjective data with objective criteria with fuzzy-AHP and make use of rules with repetitive patterns through fuzzy association rules. Trying to check how problems with high-dimensional data would be mitigated by the algorithm, we performed 5-fold cross validation according to the changing number of users. The results show that the algorithm-applied system recorded accuracy that was 12.5% higher than that of the fuzzy-AHP-applied system and mitigated the problem of data sparsity.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.212-217
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• 2009

There are rule-based learning method and statistic based learning method and so on which represent learning method for hierarchy relation between domain term. In this paper, we propose to leveling and similarity measure using the extended AHP of fuzzy term in Information system. In the proposed method, we extract fuzzy term in document and categorize ontology structure about it and level priority of fuzzy term using the extended AHP for specificity of fuzzy term. the extended AHP integrates multiple decision-maker for weighted value and relative importance of fuzzy term. and compute semantic similarity of fuzzy term using min operation of fuzzy set, dice's coefficient and Min+dice's coefficient method. and determine final alternative fuzzy term. after that compare with three similarity measure. we can see the fact that the proposed method is more definite than classification performance of the conventional methods and will apply in Natural language processing field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1060-1064
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• 2009

This paper proposes a fuzzy AHP based decision-making model to select a telecommunication company and the target of the proposed model is university students in the capital area. When customers select a telecommunication company, they have difficulty in decision-making because there are many competitive and complementary factors of telecommunication companies. To select a best telecommunication company, customers need to consider a number of different quantitative and qualitative factors such as fare, various services, additional function, etc. In this study, we suggest a fuzzy AHP based decision-making model to select a telecommunication company considering various quantitative and qualitative factors. Especially, fuzzy theory is applied to deal with the unclear or ambiguous problems, and a linear normalization model is developed to convert the value of quantitative factors to fuzzy number. A empirical example which is the target of the university students in the capital area shows the feasibility of the proposed model and it can help customers to make better decision-making for their benefits.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.363-371
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• 2016

Technology evaluation for technology innovation of venture firms should take the rapidly changing corporate environment, the ambiguity of language used in evaluation, and the inaccuracy of evaluation index into consideration. In this paper, targeting the absorptive capacity and technological entrepreneurship which are typical evaluation factors of venture firms, an ACTEM model to calculate the importance, priority, and dynamic capability of factors, applying Fuzzy-AHP was proposed. The fuzzy theory was introduced to compensate for the ambiguity of cognitive judgments when calculating weighted values for the factors that made up an assessment scale. An assessment criteria framework for absorptive capacity, technological entrepreneurship, and dynamic capability, which were not considered in previous studies on the evaluation and measurement of technological prowess, so that the users could have a realistic alternative to choose. The study compared the ACTEM model with the old AHP assessment method and found that "knowledge acquisition" and "producing ability" were the highest in absorptive capacity and technological entrepreneurship, respectively, thus demonstrating its validity.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.149-159
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• 2019

Six sigma is an innovative management movement which provides improved business process by adapting the paradigm and the trend of market and customers. Suitable selection of six sigma project could highly reduce the costs, improve the quality, and enhance the customer satisfaction. There are existing studies on the selection of Six Sigma projects, but few studies have been conducted to select the correct project under an incomplete information environment. The purpose of this study is to propose the application of integrated MCDM techniques for correct project selection under incomplete information. The project selection process of six sigma involves four steps as follows: 1) determination of project selection criteria 2) calculation of relative importance of team member's competencies 3) assessment with project preference scale 4) finalization of ranking the projects. This study proposes the combination methods by applying group fuzzy Analytical Hierarchy Process (AHP), an easy defuzzified number of Trapezoidal Fuzzy Number (TrFN) and Grey Relational Analysis (GRA). Both of the weight of project selection criteria and the relative importance of team member's competencies can be evaluated by group fuzzy AHP. Project preferences are assessed by easy defuzzified scale of TrFN in case of incomplete information.)

• 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.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.67-73
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• 2008

National Education Information System (NEIS) is an ambitious reform project that can improve the competitiveness and performance of education field and to link administrational work of between schools and their senior administration offices via internet. NEIS is introduced to lighten the teachers' overburden, to standardize the work process and to bring better quality education to each classroom and make it possible for those involved in education to resolve any related educational problem on line. This paper aims to construct a hierarchy model consisting of key factors such as technological and administrative factors for the effective use of NEIS and to evaluate the relative importance among key factors using fuzzy AHP technique included fuzzy concepts. Eventually, the analysis results can be utilized to develop the future improvement strategy of NEIS and to satisfy the users.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).