• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.710-715
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• 2004

The design problem of manufacturing system is addressed, adopting the closed queueing network model with multiple loops and re-entrant flows. The entire design problem is divided into two hierarchical sub-problems of (1) determining the station configuration and (2) optimizing the lot constitution; then they are tackled by neighbor search algorithm (NSA) and greedy mean value analysis (GMVA), respectively. Unlike the conventional MVA concerning multi-class closed queueing networks, the GMVA doesn't stick to a fixed lot proportion; rather it tries to find the optimal balance. The NSA, on the other hand, improves the object function value by altering the station configuration successively with its superior neighbor. The moderate time complexity, presented in big-${o}$ notation, enables us to apply the method even to the large-size practical cases, and the CPU time of an enlarged problem can be approximated by the same equation. The validity of our analytic approach is backed up by simulation studies with a widespread simulation package.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.165-168
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• 2005

The objects, which can be personal digital assistants, electronic rings, doors or even clothes, offer embedded chips with computation facilities and are generally called artifacts. I later realized that this was not so the real problem is actually authentication. Recent results indicate scalability problems for flat ad hoc networks. Sensor network achieves function that handle surrounding information perception through sensor and sensed information to network that is consisted of sensor nodes of large number. Research about new access control techniques and height administration techniques need authentication information persons' certification assurance level classification in sensor network environment which become necessary different view base with authentication information at node for application of AAA technology in USN environment that must do authentication process using information that is collected from various sensor mountings. So, get base authentication information in sensor type and present weight grant model by security strength about authentication information through information who draw. In this paper collected information of sensor nodes model who give weight drawing security reinforcement as authentication information by purpose present be going to. and Must be able to can grasp special quality of each sensor appliances in various side and use this and decide authentication assurance level for value estimation as authentication information elements. Therefore, do to define item that can evaluate Authentication information elements thus and give simple authentication assurance level value accordingly because applying weight. Present model who give authentication assurance level value and weight for quotation according to security strength.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1103-1111
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• 1999

STACOM will be utilized to control substation voltage in the near future. Although STACOM shows good voltage regulation performance owing to its rapid and continuous response, it needs additional reactive power compensation device to keep control margin for emergency such as fault. ULTC transformer is one of good candidates. This paper presents a Kohonen Neural Network (KNN) based coordination control scheme of ULTC transformer and STACOM. In this paper, the objective function of the coordination control is minimization of both STACOM output and the number of switchings of ULTC transformer while maintaining substation voltage magnitude to the predefined constant value. This coordination, control is performed based on reactive load trend of the substation and KNN which offers optimal tap position in view of STACOM output minimization. The input variables of KNN are active and reactive power of the substation, current tap position, and current STACOM output. The KNN is trained by effective Iterative Condensed Nearest Neighbor (ICNN) rule. This coordination control applied to IEEE 14 bus system and shows satisfactory results.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1999년도 학술대회논문집-국제 전기방전 및 플라즈마 심포지엄 Proceedings of 1999 KIIEE Annual Conference-International Symposium of Electrical Discharge and Plasma
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• pp.262-266
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• 1999

In this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PID control system, but the position control system have difficulty in controling variable load and changing parameter. We propose neural network 2-DOF PID control system having feature for removal disturbrances and tracking function in the target value point. The back propagation algorithm of neural network used for tuning the 2-DOF parameter ($\alpha$, $\beta$, ${\gamma}$, η). We investigate the 2-DOF PID control system in the position control system and verify the effectiveness of proposal method through the result of computer simulation.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 춘계종합학술대회
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• pp.395-398
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• 2001

본 논문에서는 직류 서보 전동기를 구동원으로 하는 위치 제어계에서 부하변동에 따른 파라메타 변화, 외란 둥에 강인한 2자유도 PID 제어기의 설계법을 제시하여 신경망으로 2자유도 PID 제어기를 구성하였다. 이 제어기의 계수들이 기동시나 계 응답의 변동시 신경망 역전파 알고리즘(Back-Propagation Algorithm)에 의해서도 수성 되도록 하였다. 그리고 이것을 실제의 위치 제어계에 적용하여 실험을 통해 그 성능을 검증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.491-493
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• 1995

In this paper, the method of long-term load forecasting using a fuzzy neural network of which input is a fuzzy membership function value of a input variable like as GNP which is considered to affect demand of load. The proposed method was applicated in Korea Electric Power Corporation (KEPCO). The comparison with Error Back-Propagation Neural Network has been shown.

• 한국통신학회논문지
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• 제15권4호
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• pp.295-300
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• 1990

역 운동학 문제는 로보트 매니퓰레이터 제어에서 중요한 관점이 되어 왔다. 본 논문에서는 Jacobi 제어 기법을 실현하기 위하여 Hopfield, Tank의 신경회로망 모델을 사용하였다. 뉴런의 상태는 매니퓰레이터의 관절 속도를 나타내고, 연결강도는 Jacobi 행렬의 값으로 결정되어 진다. 회로망의 에너지 함수는 실제 관절 속도와 원하는 관절 속도간의 최소 자승 오차와 대응하도록 구성한다. 매 샘플링에서 연결 강도와 뉴런의 상태는 현재의 관절위치값에 따라서 변한다. 여유 자유도를 가지는 평면 매니퓰레이터에 대한 역 운동학 해를 컴퓨터 시뮬레이션을 통하여 구하였다.

• 대한안전경영과학회지
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• 제22권4호
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3333-3354
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• 2022

The 5G Core Network (5GC) is an essential part of the mobile communication network, but its security protection strategy based on the boundary construction is difficult to ensure the security inside the network. For example, the Network Function (NF) mutual authentication mechanism that relies on the transport layer security mechanism and OAuth2.0's Client Credentials cannot identify the hijacked NF. To address this problem, this paper proposes a trust model for 5GC based on NF interaction behavior to identify malicious NFs and improve the inherent security of 5GC. First, based on the interaction behavior and context awareness of NF, the trust between NFs is quantified through the frequency ratio of interaction behavior and the success rate of interaction behavior. Second, introduce trust transmit to make NF comprehensively refer to the trust evaluation results of other NFs. Last, classify the possible malicious behavior of NF and define the corresponding punishment mechanism. The experimental results show that the trust value of NFs converges to stable values, and the proposed trust model can effectively evaluate the trustworthiness of NFs and quickly and accurately identify different types of malicious NFs.