• 한국IT서비스학회지
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• 제11권3호
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• pp.1-16
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• 2012

This paper is aimed to present a fuzzy decision-making approach to deal with disaster recovery priority decision problem in information system. We derive an evaluation approach based on TOPSIS(Technique for Order Performance by Similarity to Ideal Solution), to help disaster recovery priority decision of total information system for port logistics in a fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by trapezoidal fuzzy numbers. This study applies the fuzzy multi-criteria decision-making method to determine the importance weight of evaluation criteria and to synthesize the ratings of candidate disaster recovery system. Aggregated the evaluators' attitude toward preference, then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. This approach is demonstrated with a real case study involving 4 evaluation criteria(system dependence, RTO, loss, alternative business support), 7 information systems for port logistics assessed by 5 evaluators from Maritime Affairs and Port Office.

• 한국지능시스템학회논문지
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• 제7권2호
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• pp.70-78
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• 1997

여러 가지 고급 제어 이론들에 관한 연구가 심도있게 진행되고 있음에도 불구하고 아직까지 산업현장에는 여러가지 변형된 형태의 PID 제어기가 널리 사용되고있다. 이는 PID 제어기 자체가 가진 제어 구조의 단순성, 효율성, 강건성, 그리고 제어 기술자들에 대한 친밀감 등에 기인한다. 또한 요즘 제어 분야에서는 퍼지 이론을 도입하는 연구가 활발히 진행되고 있다. 특히, 퍼지 이론을 사용해서 거의 모든 함수들을 근사화시킬 수 있다는 연구 결과들이 발표되면서 수학적으로 안정성 및 강건성을 명확히 증명하기에 다소 미흡하였던 퍼지 논리 제어에 관한 연구가 활기를 띠고 있다. 본 논문에서는 먼저 간단한 퍼지 제어기로부터 선형 PID 제어기를 유도한다. 그리고 나서 다소 일반적인 경우의 퍼지 제어기를 사용하여 산업 현장에서 가장 널리 사용되고있는 선형PID 제어기를 유도하여 결굴 PID 제어기는 퍼지 제어기의 일종에 불과함을 입증할 것이다.

• 한국시뮬레이션학회논문지
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• 제6권2호
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• pp.105-115
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• 1997

Fuzzy simulation predicts the behaviors of real system based on a model by qualitative reasoning methods and simulates the representation of ambiguous values on the real system variables using the theory of fuzzy sets. During the simulation, however, unnecessary behaviors due to the fuzzy representation are created, and the number of states of system variables changing temporally in the time axis is drastically increased. In this paper, we present a new algorithm which eliminates the spurious behaviors from the great number of result values due to the results of the fuzzy operation, and reduces the number of the states by transforming the complex state transition rules. This paper also shows the easy implementation of the simulation by using the existing package while it is difficult on the PC due to the complexities of the calculation.

• 한국통신학회논문지
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• 제27권7C호
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• pp.664-669
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• 2002

본 논문에서는 ATM 망에서의 접속된 트래픽에 대해 효율적인 버퍼제어를 위한 퍼지제어 알고리즘을 제안한다. 제안된 퍼지제어 알고리즘은 동적 임계값을 구하기 위해 두 개의 우선순위와 퍼지집합을 사용한다. 즉, 발생된 저, 고순위 트래픽 비율에 따라 퍼지집합 이론을 통하여 추론한 후 그 비퍼지화값으로 접속된 트래픽에 대해 버퍼에서의 임계값을 제어하도록 하였다. 성능분석 결과 기존의 부분버퍼공유기법에서보다 셀손실율 면에서 그 성능이 향상됨을 확인하였다.

• Journal of Electrical Engineering and information Science
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• 제2권5호
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• pp.72-78
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• 1997

This paper presents a fuzzy relaxation algorithm, which is based on the possibility and FAM instead of he probability and compatibility coefficients used in most of existing probabilistic relaxation algorithms, Because of eliminating stages for estimating of compatibility coefficients and normalization of the probability estimates, the proposed fuzzy relaxation algorithms increases the parallelism and has a simple iteration scheme. The construction of fuzzy relaxation scheme consists of the following three tasks: (1) definition of in/output linguistic variables, their term sets, and possibility. (2) Definition of FAM rule bases for relaxation using fuzzy compound relations. (3) Construction of the iteration scheme for calculating the new possibility estimate. Applications to region segmentation an ege detectiojn algorithms show that he proposed method can be used for not only reducing the image ambiguity and segmentation errors, but also enhancing the raw edge iteratively.

• Spatial Information Research
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• 제7권2호
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• pp.223-236
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• 1999

본 연구는 최근 시설의 확충이 절실히 요구됨에서 불구하고 사회적 기피시설로 인식되어 그 입지를 둘러싸고 많은 사회적 문제를 일으키고 있는 쓰레기 소각장의 후보입지를 선정하는데 있어서 보다 유연성있고 객관적인 방법론을 도입하여 의사결정을 위한 지원시스템으로의 GIS 기능을 높이려는데 목적을 두었다. 본 연구에서는 종전의 입지분석시에 주로 많이 활동된 부울 논리에 의한 단순 도면중첩기능의 문제점을 제시하고 쓰레기 소각장의 입지를 선정하는데 있어서 퍼지집합(Fuzzy Set) 과 계층분석과정(AHP : Anlaystic Hierarchy Process) 이론을 활용하여 후보 입지들에 대한 적합도 수준을 평가하는데 보다 유연성을 l할수 있는 방법론을 모색하였다. 특히 본 연구는 쓰레기 소각장의 후보입지들을 선정하는데 있어서 어떠한 요인을 기회요인으로 하였는가, 또한 각 요인들에 대한 상대적 중요성, 즉 가중치를 어떻게 설정하였는가에 따라서 다양한 결과들이 추출될 수 있음을 제시하려는데 초점을 두었다.

• 대한인간공학회지
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• 제29권4호
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• pp.631-637
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• 2010

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.61-68
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• 1998

It has become important to evaluate the qualitive reliability and condition assessment of existing structural systems in order to establish a rational program for repair and maintenance. Since most of if existing structural system may suffer from defect corrosion and damage, it is necessary to account for their effects in fuzzy reliability analysis, In this paper, an attempt is made to develope a reliability analysis for damaged structural systems using failure possibility theory. Damage state is specified in terms of linguistic valiables using natural language information and numerical information, which are defined by fuzzy sets. Using a subjective condition index of failure possibility and information of the damage state is introduced into the calculation of failure probability. The subjective condition index of quantitative and qualitative analysis method is newly proposed based on the fuzzy set operations, namely logical product, drastic product, logical sum and drastic sum

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.3-6
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• 2006

Methods for risk engineering is a bundle of engineering tools including fundamental concepts and approaches of soft computing with application to real issues of risk management. In this talk fundamental concepts and soft computing approaches of risk engineering will be introduced. As the term of risk implies both advantageous and hazardous uncertainty in its origins, a fundamental theory to describe uncertainties is introduced that includes traditional probability and statistical models, fuzzy systems, as well as less popular modal logic. In particular, modal logic capabilities to express various kinds of uncertainties are emphasized and relations with rough sets and evidence theory are described. Another topic is data mining related to problems in risk management. Some risk mining techniques including fuzzy clustering are introduced and a recently developed algorithm is overviewed. A numerical example is shown.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.