• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.607-617
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• 1996

This paper shows that fuzzy set theory can be useful in modeling and solving job scheduling problems with uncertain processing times. The processing times are considered as fuzzy numbers(fuzzy intervals or time intervals) and the fuzzy Delphi method is used to estimate a reliable time interval of each processing time. Based on these time estimates, we then propose an efficient methodology for calculating the optimal sequence and the fuzzy makespan.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1647-1651
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• 2009

The uncertainty or imprecision associated with vague parameters and weighting sets, reduces the ability to decide what alternative is better for a particular location. To efficiently reduce the effect of imprecision frequently arising in available information, fuzzy theory has been used to improve consideration of imprecision in a Multi-Criteria Decision Analysis (MCDA) problem. Fuzzy logic offers a way to represent and handle imprecision present in continuous real world applications. A GIS implementing fuzzy set theory, (referred to in this paper as the "Spatial Fuzzy Approach") enables decision makers to express imprecise concepts associated with geographic data and provides decision makers the ability to have even more definition and discrimination in terms of the best alternatives for a particular spatial location. This study is focused on addressing questions pertaining to the methodology of floodplain analysis using GIS and Spatial Fuzzy MCDA to evaluate flood damage reduction alternatives. The issues will be examined in a case study of the Suyoung River Basin in Pusan, Korea.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.196-206
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• 2000

These days, the fuzzy logic or the fuzzy set theory has received attention from a number of researchers in the area of industrial application. Moreover, the fuzzy logic control has been successfully applied to a large numbers of control problems where the conventional control methods had failed. Using this control theory we designed a climate controller for an automotive climate control system whose mathematical model is difficult. This paper describes an automotive climate control where the fuzzy control has been used to stabilize parameter uncertainties and disturbance effects. To show the validity and effectiveness of the proposed control method, the fuzzy logic controller was implemented with a philips 80C552 microcomputer chip and tested in an actual vehicle. From the experimental results, it could be conduced that the proposed controller is superior to conventional controllers in both control performance and thermal comfort. The climate control system in cars is difficult to model mathematically so we tested a fuzzy logic control system which promised better results.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.5
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• pp.23-29
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• 1994

The design procedure for fuzzy logic controller depends on the expert's knowledge or trial and error. Moreover, it is very difficult to guarantee the stability and robustness of the system due to the linguistic expression of fuzzy control. However, fuzzy logic control has succeeded in many control problems that the conventional control theory has difficulties to deal with. As a result, this control theory is applied to the engine control system which a mathematical model is difficult. In this study, the fuzzy logic is applied to obtain the gain of PI control at idle speed control system, and a simple engine model is developed in order to perform simulation. Experimental results show that the response to reach the target engine speed at idle speed control system is improved by adopting the gain obtained with fuzzy logic.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.28.5-28
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• 2001

This paper investigates a classification method of the electrocardiogram (ECG) into different disease categories. The features for the classification of the ECG are the coefficients of the discrete wavelet transform (DWT) of ECG signals. The coefficients are calculated with Haar wavelet, and after DWT we can get 64 coefficients. Each coefficient has morphological information and they may be good features when conventional time-domain features are not available. Since all of them are not meaningful, it is needed to reduce the size of meaningful coefficients set. The distributions of each coefficient can be the rules to classify ECG signal. The optimally reduced feature set is obtained by fuzzy c-means algorithm and rough set theory. First, the each coefficient is clustered by fuzzy c-means algorithm and the clustered ...

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Journal of the Ergonomics Society of Korea
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• v.17 no.1
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• pp.47-54
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• 1998

Product design and development is very important process in enterprise activities. Reducing development time and reflecting consumer's needs is required to product design and development for increasing benefit and decreasing cost. Human sensibility ergonomics is one of the important technology of R&D in product development. However, the subjective method of human sensibility ergonomics has several problems to analyze and to Quantify experimental data and objective method of human sensibility ergonomics is still in process on study. In this research, new analyzing method is proposed for the subjective human sensibility ergonomics applied with fuzzy set theory. What is the useful theory for controlling uncertain type of information like human mind? This approach is more effective method for analyzing consumer's needs for product design and development process. At collecting needs, certainty scale is added for adapting hedge of fuzzy function. Using a kind of union operator, synthesize each item to analyze identification of each item with fuzzy hamming distance. Identification of analysis is classified with the relational weight using Relationship Chart Method, and is drawn the relationship diagram for clustering each item. A case study with sample test is conducted and demonstrated with this suggested method for more effective way.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.215-215
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• 1988

This paper presents a fuzzy set theory based formulation and heuristic which will allow plant layout problems to be solved for more than two input goals with different weights. The heuristic combines a construction and improvement procedure to generate a good layout from the formulation. To test the effectiveness of the heuristic, a set of examples previously used by various authors is solved and the results are compared to those from other known heuristics. The comparison indicates that the proposed method performs well for each of seventeen classical test problems.

• Korean Management Science Review
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• v.13 no.2
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• pp.215-232
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• 1996

This paper presents a fuzzy set theory based formulation and heuristic which will allow plant layout problems to be solved for more than two input goals with different weights. The heuristic combines a construction and improvement procedure to generate a good layout from the formulation. To test the effectiveness of the heuristic, a set of examples previously used by various authors is solved and the results are compared to those from other known heuristics. The comparison indicates that the proposed method performs well for each of seventeen classical test problems.

• Honam Mathematical Journal
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• v.37 no.3
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• pp.269-279
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• 2015

Atanassov introduced another fuzzy object, called intu- itionistic fuzzy set as a generalization of the concept of fuzzy subset. The aim of this paper is the elaboration of a representation theory of involutive interval-valued Łukasiewicz-Moisil algebras by using the notion of intuitionistic fuzzy sets.