• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.287-295
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• 2010

Based on the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued in tuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy numbers, and the information about attribute weights is partially known. Anumerical example is used to illustrate the applicability of the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.171-186
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• 1998

While one main stream of research in GDSS (Group Decision Support System) is to investigate how GDSS affects decision-making performances of groups according to task types, support features, meeting facilitation modes and meeting environments. little study h3s been done about how group characteristics affect group decision processes and outcomes depending upon GDSS is provided or not. So far, most GDSS research has considered group characteristics (e.g. personality homogeneity) as given and did not include it as control variables in experiments. Therefore, the objective of this study is to investigate how members of two different groups perceive the use of GDSS in group meetings through lab experiments. The two groups are homogeneous and heterogeneous groups in terms of members' personality mix. This research found that the effect of GDSS is a function of groups' personality homogeneity in regards of the satisfaction on decision process and the communication thoroughness. The support of GDSS and the group homogeneity are proved to influence participant's perception about some dependent variables such as satisfaction on decision process.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.81-87
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• 2008

Sasanag Contitution Medicine(SCM) is the traditional medicine theory based on constitutional medicine in Korea. It is most import ant that a personal SCM type is determined accurately ahead of applying any Sasang treatments. For this, many researches have been studied to diagnose the SCM type using constitutional clinical data. The decision tree is a tree-structured data-mining methodology. Recently, in the Korean traditional medicine society, there have been several efforts to find diagnosing tools using the decision tree method. So, we developed a decision tree program based on web for analyzing constitutional clinical information. It can use various clinical data as input data, offer filtering function to select clinical data to be used. We can find useful factor to be influential on SCM types using this program.

• Journal of the military operations research society of Korea
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• v.3 no.1
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• pp.51-82
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• 1977

Decision making is a function of many variables, but among these, human burden (soft-ware) and machine burden (hard-ware) are critical. Decision Maker is rather concerned with the soft-ware and just wants to have machine calculate the quantitative arithmetic involved in the decision-making study, because he is responsible for that decision whether or not he knows details about the techniques used by his staffs. From the point of these considerations, computer-assisted war game model has its significance in military decision making. The major outcome of this model is time-phased FEBA movement. FEBA is moved mainly by the ratio of the Index of Combat Effectiveness (ICE). To calculate ICE, Ground Forces are concerning the Index of Firepower (IFP) of individual weapons and in the case of Air Force, sorties are allocated into each sector, and added to the Ground Force IFP. With the ratio of total ICE, FEBA is moved according to the War Game Tables and process is repeated after consideration of casualties. This model is used by IBM-370/135 in MND computer room and also tested by IBM-3741/3717 established at ROKA HQ.

• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.5
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• pp.103-113
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• 2000

A decision support system DSS-WQMRA (Decision Support System-Water Quality Management in Rural Area) was developed to help regional planners for the water quality management in a rural basin. The integrated model DSS-WQMRA, written in JAVA, includes four subsystems such as a GIS, a database, water quality simulation models and a decision model. In the system, the GIS deals with landuse and the location of pollutant sources. The database manages each data and supplies input data for various water quality simulation models. the water quality simulation model is composed of the GWLF( Generalized Watershed Loading Function), PCLM(Pollutant Loading Calculation Module) and the WASP5 model. The decision model based on mixed integer programming is designed to determine optimal costs and thus allow the selection of managemental practices to meet the water quality criteria. The methodology was tested with an example application in the Bokha River Basin, Kyunggi Province in Korea. It was proved that the integrated model DSS-WQMRA could be very useful for water quality management including the non-point source pollution in rural areas.

• Korean Journal of Mathematics
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• v.29 no.1
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• pp.137-167
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• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.6
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• pp.1938-1944
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• 2004

In this study, when we make a diagnosis of constitution using QSCC Ⅱ(Questionnaire of Sasang Constitution Classification). data mining techniques are applied to seek the classification function for improving the accuracy. Data used in the analysis are the questionnaires of 1051 patients who had been treated in Dong Eui Oriental Medical Hospital and Kyung Hee Oriental Medical Hospital. The criteria for data cleansing are the response pattern in the opposite questionnaires and the positive proportion of specific questionnaires in each constitution. And the criteria for variable selection are the test of homogeneity in frequency analysis and the coefficients in the linear discriminant function. Discriminant analysis model and decision tree model are applied to seek the classification function into Sasang constitution. The accuracy in learning sample is similar in two models, the higher accuracy in test sample is obtained in discriminant analysis model.

• Journal of the Ergonomics Society of Korea
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• v.23 no.2
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• pp.37-54
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• 2004

Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.