• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.247-251
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• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme and verified its usefulness. However, the previously proposed scheme has the problem of lower diagnostic resolution as in the case of other qualitative approaches. In order to improve the diagnostic resolution, a concept of fuzzy number is introduced into the basic FCM-based fault diagnostic algorithm. By incorporation the fuzzy number into fault FCM models, quantitative information such as the transfer gain between the state variables can be effectively utilized for better diagnostic resolution. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and modified and modified pattern matching scheme are also proposed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.11-17
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• 2018

IDS/IPS and networked computer systems are playing an increasingly important role in our society. They have been the targets of a malicious attacks that actually turn into intrusions. That is why computer security has become an important concern for network administrators. Recently, various Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems is useful for existing intrusion patterns on standard-only systems. Therefore, probe detection of private clouds using BlockChain has become a major security protection technology to detection potential attacks. In addition, BlockChain and Probe detection need to take into account the relationship between the various factors. We should develop a new probe detection technology that uses BlockChain to fine new pattern detection probes in cloud service security in the end. In this paper, we propose a probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) based on service security using BlockChain technology.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.17-40
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• 1994

The objectives of this paper are to apply fuzzy cognitive map (FCM)- related techniques to (1) extract causal knowledge from a specific problem-domain and (2) perform a series of causal analysis in complicated decision making area. We propose a set operation-based augmentation (SOBA) algorithm to combine multiple FCMs developed by multiple experts. Based on the SOBA knowledge acquisition algorithm, we can obtain a causal knowledge base fairly representing multiple experts' knowledge about a problem domain. The causal knowledge base built by SOBA algorithm can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if-then) knowledge base. We applied out method to stock market analysis problem whichis a typical of highly unstructured problems in OR/MS fields.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.203-212
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• 1998

본 논문에서는 FCM을 이용하여 의사결정의 질을 높일 수 있는 추론방법을 제시한다. 이를 위하여 FCM의 추론의 질을 저하시키는 문제중의 하나인 동기화 문제(synchronizatinon Problem)를 설명하고. 이를 해결하기 위한 방안으로서 FCM 계층화(levelization) 알고리즘을 제시한다. 본 논문에서 제안된 계층화된 FCM을 이용한 추론절차를 제시하고, 그 활용예를 설명한다.

• Journal of the Korea Society for Simulation
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• v.7 no.1
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• pp.53-68
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• 1998

FCM은 비구조적인 (unstructured) 문제영역에서 주어진 문제에 대한 효과적인 추론시 적용될 수 있는 매우 유용한 추론도구이다. 그러나, FCM에 사이클이 존재하면 추론효과가 크게 감소한다. 본 노문에서는 사이클이 있는 FCM을 이용한 의사결정의 질을 높일 수 있는 추론방법을 제시한다. 아울러 사이클이 제거된 FCM의 추론이 질을 저하시키는 문제중의 하나인 동기화 문제 (synchronization problem)를 설명하고, 이를 해결하기 위한 방안으로서 FCM 계층화 (levelization) 알고리즘을 제시한다.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.203-208
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• 2005

We propose an algorithmic approach for handling linguistic values defined in the same linguistic variable. Using the proposed approach, we can explicitly capture the differences of individuals' subjectivity with respect to linguistic values defined in the same linguistic variable. The proposed approach can be employed as a useful tool for discovering hidden relationship among linguistic values defined in the same linguistic variable. Consequently, it provides a basis for improving the precision of knowledge acquisition in the development of fuzzy systems including fuzzy expert systems, fuzzy decision tree, fuzzy cognitive map, ok. In this paper, we apply the proposed approach to a collective linguistic assessment among multiple experts.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.430-432
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• 1993

In this paper, an algorithm for the fault diagnosis using simple FCM(Fuzzy Cognitive Map) is proposed FCMs which store uncertain causal knowledges are fuzzy signed graphs with feedback. The algorithm allows searching the origin of fault and the ways of propagating the abnormality throughout the process simply and has following characteristics. First, it can distinguish the cause of soft failure which can degenerate the process as well as hard failure. Second, it is proper for the processes which have difficulties to establish the exact quantative model. Finally, it has short amputation time in comparison with the fault tree or the other AI methods. The applicability of the proposed algorithm for the fault diagonosis to a tank or pipeline system is demonstrated

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.175-183
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• 1999

국내 무역업무 환경이 EDI 시스템 도입 및 정부의 적극적인 활성화 정책에 힘입어 급속도로 변화하고 있다. 이러한 변화와 함께 EDI 시스템 도입, 활용방법, 성과측정 및 표준화에 대한 연구들이 다각적으로 이루어지고 있다. 이 중에서도 기업에게 있어서 EDI 도입에 따른 성과향상 및 성과측정이라는 이슈는 대단히 중요한 의미를 가질 뿐만 아니라, EDI 시스템 도입의 궁극적인 목표이기도 하다. 이러한 배경하에서 EDI 시스템도입에 따른 기업성과를 향상시키기 위한 EDI 시스템 구현 및 활용방안 등에 대한 기존연구들이 많이 소개되어 있다. 그러나, 실제적으로 EDI 시스템을 활용하면서 시스템에 대한 통제요인의 개발 및 통제요인간의 인과관계 확인과 요인들간의 상관성 조절을 통해서 기업 전체의 성과를 향상시킬 수 있는 EDI 통제모형의 개발에 관한 연구는 부족하다. 따라서, 본 연구에서는 EDI 성과를 향상시킬 수 있는 통제요인 및 이들간의 상관관계를 밝히고, 이를 퍼지인식도 (FCM: Fuzzy Cognitive Map)와 연계하여 효율적으로 EDI 시스템을 통제할 수 있는 통제모형을 제시하고자 한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.16-22
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• 2001

There is no doubt that agents play an increasingly predominant role in e-commerce, whether these are business-to-consumer or business-to-business applications. However most of the current e-commerce agents only support a single bid for a product at a fixed price. Although price is an important factor, it is not the only concern of both business and consumer. There is doubt as to whether such agents satisfv both parties. Negotiation on a variety of issues is needed in order to reach an agreement. In this paper, a computational agent negotiation(CAN) model is proposed to facilitate multiple-issue negotiation via an agent. The main contribution of the CAN model is it enables agent to participate actively in the negotiation with various feedback instead of simply an agreement or rejection.