• 한국인터넷방송통신학회논문지
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• 제11권1호
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• pp.125-132
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• 2011

기존의 화재 감시 시스템은 보통 연기, CO 혹은 온도나 온도의 변화량을 가지고 화재여부를 판단하였다. 대부분 각각의 센서에서 측정된 값을 미리 설정한 값과 비교하여 기준을 넘었을 경우에 화재라고 결정한다. 그러나 화재 가능성이 있는 상황도 정확히 예측하는 것이 화재를 예방하기 위해 요구된다. 본 연구에서는 여러 인자들 간의 조합에 의한 규칙을 생성하고, 불명확한 데이터 처리가 가능한 퍼지추론을 사용하여 화재상황을 인식하는 방식을 제안한다. 또한 퍼지추론 방식에서 지식의 일반화, 형식화의 문제점을 해결하기 위해, 화재의 특정 패턴들의 특징을 찾아서 분석하고 규칙베이스를 구축함으로써 시스템의 성능을 더욱 향상 시킨다. 화재의 레벨을 3단계(정상, 주의, 위험)로 나누고, 각 단계별로 훈련데이터를 FCM(fuzzy C-means clustering)에 의해 규칙화 하여 추론하는 시스템을 제안한다. 제안된 방식을 UCI의 삼림화재 데이터를 이용하여 성능을 평가한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.681-683
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• 1998

Fuzzy Inference System is to trans late and be concrete with human expert in to mathematical equation. It is easy to be applied for Nonlinear System and the know ledge can be applied at that. With using the rule according to the Knowledge, when it is realized simulations must be required repeatedly and small vibration is generated in steady state, too. In this paper, we applied the system to the methodology of optimization with self-learn ing by us ing ANFIS(Adaptive Network-based Fuzzy Inference System) which makes use of back-propagation and least square method at a first order Sugeno Fuzzy System. In order to show the effect of Algorithm, we demonstrated it by us ing Rotary Inverted Pendulum.

• 산업공학
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• 제4권2호
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• pp.81-92
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• 1991

A study showed that the two most important obstacles to assembly automation were that product designs are generally not assembly oriented and that most components cannot be handled automatically without problems. In the view of the importance of well designed product with high assemblability, a tool must be developed to pre-evaluate a product during design phase whether it can be assembled with minimum efforts. In this research, a prototype expert system for DFA has been developed that can be used to advise the designer of difficulties that his/her design presents for automatic handling during manufacture. This rule-based system has been implemented on an IBM personal computer, using the Texas Instruments' Personal Consultant Plus.

• 지능정보연구
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• 제1권2호
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• pp.73-83
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• 1995

본 논문 에서는 진화 알고리즘을 이용하여 퍼지 규칙 베이스의 최적 규칙들을 자동으로 생성하는 방법을 제안한다. 진화 알고리즘에 의한 퍼지 논리 시스템의 최적 규칙은 전문가의 사전 경험이나 지식이 없이도 자동 설계가 가능하고 이들 규칙을 이용하여 지능 제어를 할 수 있다. 본 논문에서 사용한 접근 방법은 퍼지 규칙 소속함수의 자동 조정으로 규칙을 생성하고, 최적의 제어 규칙 탐색은 퍼지 논리 시스템의 성능 기준으로 정의한 적합도 값을 기반으로 탐색한다. 제안한 방법의 유용성을 보이기 위해 비선형 시스템에서 컴퓨터 모의실험을 행하였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권10호
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• pp.4204-4222
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• 2015

Cloud is the latest buzz word in the internet community among developers, consumers and security researchers. There have been many attacks on the cloud in the recent past where the services got interrupted and consumer privacy has been compromised. Denial of Service (DoS) attacks effect the service availability to the genuine user. Customers are paying to use the cloud, so enhancing the availability of services is a paramount task for the service provider. In the presence of DoS attacks, the availability is reduced drastically. Such attacks must be detected and prevented as early as possible and the power of computational approaches can be used to do so. In the literature, machine learning techniques have been used to detect the presence of attacks. In this paper, a novel approach is proposed, where intelligent rule based feature selection and classification are performed for DoS attack detection in the cloud. The performance of the proposed system has been evaluated on an experimental cloud set up with real time DoS tools. It was observed that the proposed system achieved an accuracy of 98.46% on the experimental data for 10,000 instances with 10 fold cross-validation. By using this methodology, the service providers will be able to provide a more secure cloud environment to the customers.

• 지능정보연구
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• 제5권1호
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• pp.1-12
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• 1999

강건설계(robust design)는 낮은 비용으로 잡음에 강건한 고품질의 제품이나 공정을 설계하는 체계적이고 효율적인 방법이다. 그러나 강건설계의 과정 중 비표준 직교배열의 사용과 교호인자을 포함한 실험계획은 다소 복잡하고, 전문지식이 필요한 부분으로 비전문가에는 난해한 작업이다. 이를 해결하기 위하여 본 연구에서는 표준직교배열의 변형과 선점도를 이용하여 교호인자를 직교배열의 열에 자동으로 할당하는 전문가시스템 prototype을 개발하였다. 사용자가 수준별 인자수와 교호작용의 유무를 입력하면, 시스템은 적절한 직교배열을 선정하여 필요에 따라 변형하며, 제어인자와 교호작용을 직교배열표에 자동으로 할당하여 출력한다. 개발된 시스템을 사용함으로써 초보자도 직교배열을 쉽게 변형할 수 있으며 다수의 교호인자를 포함한 실험계획을 빠르게 할 수 있다. 본 연구에서 이용된 지식은 문헌에서 추출하였으며, 추론 전략으로는 규칙기반추론(rule-based reasoning)을 이용하였다.

• 전자공학회논문지B
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• 제29B권7호
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• pp.30-41
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• 1992

As a general model of rule-based systems, we propose a model for a fuzzy production system having chaining rules and an inference engine associated with the model. The concept of so-called 'fuzzy petri nets' is used to model the fuzzy production system and the inference engine is designed to be capable of handling inexact knowledge. The fuzzy logic is adopted to represent vagueness in the rules and the certainty factor is used to express uncertainty of each rules given by a human expert. Parallel, inference schemes are devised by transforming Fuzzy Petri nets to matrix formula. Futher, the inference engine mechanism under the Mamdani's implication method can be desceribed by a simple algebraic formula, which makes real time inference possible.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• 한국수학교육학회지시리즈A:수학교육
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• 제32권1호
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• pp.75-90
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• 1993

의상결정 문제가 의사결정자의 취향에 좌우되는 볼확실한 상황에서 의사결정은 하나가 아닌 일련의 관련된 결정들로 구성된다. 규칙기준 전문가 시스템은 그와같은 의사결정 문제를 표현할 수 없다. 이 논문은 그와같은 문제들은 해결하기 위하여 모델기준 지식표현과 확률추론을 결합하여 자문시스템 IDPI를 제시하고 그와같은 방법을 사용하여 대학생들을 위한 진로자문 시스템을 구현한다.