• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.12-17
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• 2004

This study is designed to grope for logical methods in the decision-making process of human beings such as creation and analysis. With this in mind, the paper worked with a process where the designers of a design team gather and analyze their opinions in a design process to decide on the HVAC system of buildings. The paper introduced the fuzzy theory, or one of the methods to quantitatively describe language values with ambiguous features, suggesting a method to determine the judgement and suggestion values of the HVAC designers with the characteristics of language variables as the values of design factors greatly influencing the HVAC system. As a result, the paper tested the possibility of the fuzzy system as a logical method to gather the judgement of HVAC designers in a stage of HVAC type selection exerting a great influence on the experience and judgement of the designers and having powerful linguistic features and to determine an appropriate HVAC type which can satisfy the suggested values of related design factors.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.109-116
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• 2005

This paper is to develop the prototype of a decision making for loan granting system at banks and to evaluate the effectiveness of it. The prototype is called at FENET-LG in this paper. The decision to grant a loan is an unstructured and vagueness task because it is required a tremendous amount of data and many complex relationships among them. Evaluating these many data and relationships is a difficult task even for most experienced decision maker of bank. Therefore, where complex judgement is required, the decision maker of bank may benefit from the use of fuzzy expert network to support the evaluation of ability to pay back. Given the characteristics of decision maker of banking facilities judgement task about ability to pay back, the prototype system named FENET-LG is constructed by integration of fuzzy expert system and neural network. The FENET-LG takes advantage of both the deductive approach of fuzzy expert system and the inductive approach of a neural network to provide a decision aid designed to support and facilitate the process of conducting a judgement of ability to pay back.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.897-907
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• 2013

Climate change is expected to worsen the depletion of streamflow in urban watershed. In this study, we therefore considered the treated wastewater (TWW) use as an adaptation strategy and devised a framework to identify prioritized areas for TWW use. An integrated framework that includes hydrological factors as well as social and environmental components were employed to determine the criteria for decision making. Fuzzy theory was employed to consider the uncertainties in the climate change scenarios and the weights of the performance value. All alternatives were evaluated using the fuzzy TOPSIS method. In addition, statistical method and decision making methods under complete uncertainty were used for robust decision making. As a result, ranking the alternatives using the fuzzy TOPSIS method and robust approach such as maximin, maximax, Hurwicz and equal likelihood criterion mitigated the level of uncertainty and ambiguity in each alternative. The finding of this study can be helpful in prioritizing water resource management projects considering various climate change scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7971-7977
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• 2015

This paper attempts to select the attributes of job creation and to rank them for evaluation of companies' job creation. And the results of this paper are expected to provide the information for the polices of job creation. In doing so, this paper applies fuzzy decision making analysis that reflects ambiguity and uncertainty in decision-making process. According to the results, the weight of quality of employment is similar with that of quantity of employment. In addition, annual employment growth rate, annual net employment are ranked as first and the percentage of irregular employment, the average length of employment of all workers, average monthly wages of all workers, and employment growth over sales growth rate are next ranked.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.502-509
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• 2013

In Information age, The academic liberal art computer education course set up goals to promote computer literacy and develop the ability to cope with changes in information society and improve productivity and national competitiveness. In this paper, we analyze on discovering of decisive variable and satisfaction index to have a influence on computer education on university students. As a preprocessing course, the proposed method selects optimum variable using correlation based feature selection(CFS) of machine learning tool based on Java and we calculate weighted value for each variable and then, we generate the optimal variable using weighted value based on fuzzy decision making method. we proposed Fuzzy decision making method in analysis of the academic liberal art computer education satisfaction index data and checked the accuracy of the satisfaction evaluation by using recall and precision.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.249-254
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• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1479-1485
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• 1999

This paper proposes a fuzzy decision making method for power transformer protection to identify an internal fault from other transient states such as inrush, over-excitation and an external fault with current transformer (CT) saturation. In this paper, analyzing over 300 EMTP simulations of disturbances, four input variables are selected and fuzzified. At every sampling interval from half to one cycle after a disturbance, from the EMPT simulations, different fuzzy rule base is composed of twelve if-then fuzzy rules associated with their basic probability assignments for singleton- or compound-support hypotheses. Dempster's rule of combination is used to process the fuzzy rules and get the final decision. A series of test results clearly indicate that the method can identify not only an internal fault but also the other transients. The average of relay operation times is about 12(ms). The proposed method is implemented into a Digital Signal Processor (TMS320C31) and tested.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1994.04a
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• pp.55-67
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• 1994

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics ar low speed. In this paper the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's decision-making by using the FNN(Fuzzy neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS90 MK III) and represent the ship motion characteristics internally According to learning procedure both FNN controllers can tune membership functions and identify fuzzy control rules automatically The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.