• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.143-156
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• 2010

Faced with an increase of malicious threats from the Internet as well as local area networks, many companies are considering deploying a security system. To help a decision maker select a suitable security tool, this paper proposed a three-step integrated framework using linear fuzzy regression (LFR) and physical programming (PP). First, based on the experts' estimations on security criteria, analytic hierarchy process (AHP) and quality function deployment (QFD) are employed to specify an intermediate score for each criterion and the relationship among these criteria. Next, evaluation value of each criterion is computed by using LFR. Finally, a goal programming (GP) method is customized to obtain the most appropriate security tool for an organization, considering a tradeoff among the multi-objectives associated with quality, credibility and costs, utilizing the relative weights calculated by the physical programming weights (PPW) algorithm. A numerical example provided illustrates the advantages and contributions of this approach. Proposed approach is anticipated to help a decision maker select a suitable security tool by taking advantage of experts' experience, with noises eliminated, as well as the accuracy of mathematical optimization methods.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.127-137
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• 2014

Project Financing (PF) development project is the type which influences national economy and building industry largely because it is exerted by using borrowed money from many kinds of investors and huge amount of financial raising. Many domestic PF projects are focused mainly on the profit maximization lacking in a sufficient feasibility study. Nowadays many projects are suspending due to the global finance debacle and stagnation of real estate industry. Therefore, in this paper, risk factors of PF project are deducted and Key Success Factors (KSFs) are derived through Factor-Analysis and qualified using Fuzzy-AHP method. And through the evaluation of the derived success factors in real projects, a strong correlationship has been identified between the score of each PF success factor and the level of success and/or expected rate of return (ROR). So, the result of this paper can help decision makers of the PF projects make a better decision and give a meaningful guidance in achieving successful PF projects.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.77-90
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• 2012

As the influence of service industry into domestic economy is increasing, it also has been influenced more powerfully at the domestic GDP(Gross Domestic Product) relative importance and employment relative importance continuously. By means of these reason, the Korean government announced the synthetic countermeasure for strengthening the competitive power of service industry in December, 2006. After then, it announced phase I of 'service industry advancing plan' which is concrete execution plan in April, 2008. Also, it is announced to announce phase II plans in september, 2008 and phase III plan in December, 2008 additionally. Service quality is the most powerful competitive means at service marketing and a key point for improving service productivity. The improvement of service quality has considerable influence on survival and profitability of service industry. Therefore, the study of objective service quality measurement in service industry is very important issue. The purpose of this study is to suggest a measurement model of service quality using fuzzy theory and AHP which measuring service quality objectively in subjective environment. It is expected that this study will help the improvement of competition power of service industry as well as establishment of effective decision-making.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.107-117
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• 2011

Smartphones are widely used as a mobile communication devices with more advanced computing ability and connectivity than a contemporary feature phone. As the market expands, many brand-new smartphones are released and chosen by (potential) smartphone users. In spite of smartphone's popularity, little research of the factors affecting the evaluation of smartphones and their influences on smartphone choice have been performed. Therefore, we aim to analyze evaluation factors of smartphone selection and use in this research. We use Fuzzy Analytic Hierarchy Process method, a Multi-Criteria Decision Making (MCDM) model, to find the relative importance among the factors considering the fuzziness of pair-wise comparison using AHP. After reviewing related works and interviewing the focus group, we extract the five independent factors influencing the choice and use of a smartphone. Pair-wise comparison and triangle fuzzy numbers are used to calculate the relative importance of factors. We analyze not only the whole interviewees' responses, but the differences between smartphone users and non-users. Practical implications are delivered in concluding remarks.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.52-56
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• 2004

The Information of classification and estimate about KOSPI200 index`s up and down in the stock market becomes an important standard of decision-making in designing portofolio in futures and option market. Because the coming trend of time series patterns, an economic indicator, is very subordinate to the most recent economic pattern, it is necessary to study the recent patterns most preferentially. This paper compares classification and estimated performance of SVM(Support Vector Machine) and Fuzzy SVM model that are getting into the spotlight in time series analyses, neural net models and various fields. Specially, it proves that Fuzzy SVM is superior by presenting the most suitable dimension to fuzzy membership function that has time series attribute in accordance with learning Data Base.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.730-736
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• 2011

In this paper, we designed the models for pattern classification which can reflect the latest trend in time series. It has been shown that fusion models based on statistical and AI methods are superior to traditional ones for the pattern classification model supporting decision making. Especially, the hit rates of pattern classification models combined with fuzzy theory are relatively increased. The statistical SVM models combined with fuzzy membership function, or the models combining neural network and FCM has shown good performance. BPN, PNN, FNN, FCM, SVM, FSVM, Decision Tree, Time Series Analysis, and Regression Analysis were used for pattern classification models in the experiments of this paper. The economical indices DB with time series properties of the financial market(Korea, KOSPI200 DB) and the electrocardiogram DB of arrhythmia patients in hospital emergencies(USA, MIT-BIH DB) were used for data base.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.541-547
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• 2010

Marine accidents do not correspond with another accidents because of a serious loss of lives and property. The many marine accidents can be attributed to human error like as carelessness and decision faults, and hence there is a strong need for decision-support tools for marine navigation. Much of researchers have introduced the techniques about the tools, but they hardly consider environmental factors (water depth, the width of waterway, a fishing ground, a current, the number of surrounding marine accidents, marine obstacles, etc), which are very important to the decision making of officers. In a previous research, we proposed the conceptual model of environmental risk assessment of ship navigation using fuzzy. This paper describes the detailed design of the environmental factors based on the opinion of navigation experts, and shows the validity of the conceptual model through a prototype system.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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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.

• Korean Management Science Review
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• v.24 no.2
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• pp.157-176
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• 2007

Fuzzy cognitive map(FCM) has long been used as an effective way of constructing the human's decision making process explicitly. By taking advantage of this feature, FCM has been extensively used in providing what-if solutions to a wide variety of business decision making problems. In contrast, the goal-seeking analysis mechanism by using the FCM is rarely observed in literature, which remains a research void in the fields of FCM. In this sense, this study proposes a new type of the FCM-based goal-seeking analysis which is based on utilizing the genetic algorithm. Its main recipe lies in the fact that the what-if analysis as well as goal-seeking analysis are enabled very effectively by incorporating the genetic algorithm into the FCM-driven inference process. To prove the empirical validity of the proposed approach, valid questionnaires were gathered from a number of experts on software sales, and analyzed statistically. Results showed that the proposed approach is robust and significant.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.91-109
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• 2004

This study investigates the effectiveness of a hybrid approach using fuzzy sets that describe approximate phenomena of the real world. Compared to the other existing techniques, the approach handles inexact knowledge in common linguistic terms as human reasoning does it. Integration of fuzzy sets with case-based reasoning (CBR) is important in that it helps to develop a successful system far dealing with vague and incomplete knowledge which statistically uses membership value of fuzzy sets in CBR. The preliminary results show that the accuracy of the integrated fuzzy-CBR approach proposed for this study is higher that of conventional techniques. Our proposed approach is applied to corporate bond rating of Korean companies.