• 한국지능시스템학회논문지
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• 제15권2호
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• pp.270-275
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• 2005

본 논문은 퍼지 모델을 이용한 불확실한 카오스 시스템의 적응 동기화 기법을 제안한다. 카오스 동기화 시스템은 마스터 시스템과 슬레이브 시스템으로 구성되며 각각의 시스템은 Takagi-Sugeno (T-S) 퍼지 모델을 통해 표현된다. 마스터 시스템은 파라미터가 미리 알려지지 않은 불확실한 모델로 가정되므로 불확실한 파라미터를 추정하기 위해 적응 기법을 적용하여 슬레이브 시스템을 설계한다. 동기화 오차 시스템을 안정화하고 불확실한 파라미터를 추정하는 적응 규칙을 이용한 제어기를 설계하며 Lyapunov 이론을 통해 안정도를 해석한다. 제안된 퍼지 적응 동기화 기법의 효과를 확인하기 위해서 Duffing 시스템과 Lorenz 시스템에 대해 모의 실험을 수행한다.

• 한국CDE학회논문집
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• 제5권2호
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

• 조명전기설비학회논문지
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• 제25권11호
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• pp.39-49
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• 2011

Smart Grid has two main objectives on both supply and demand aspects which are to distribute the renewable energy sources on supply side and to develop realtime price responses on demand side. Renewable energy does not consume fossil fuels, therefore it improves the eco-friendliness and saves the cost of power system operation at the same time. Demand response increases the flexibility of the power system by mitigating the fluctuation from renewable energies, and reduces the capacity investment cost by shedding the peak load to off-peak periods. Currently Smart Grid technologies mainly focus on energy monitoring and display services but it has been proved that enabling technologies can induce the higher demand responses through many pilot projects in USA. On this context, this paper provides a price responsive algorithm for HEMS (home energy management system) on the real time pricing environment. This paper identifies the demand response as a core function of HEMS and classifies the demand into 3 categories of fixed, transferable, and realtime responsive loads which are coordinated and operated for the utility maximization or cost minimization with the optimal usage combination of three kinds of demand.

• 대한안전경영과학회지
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• 제17권2호
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• pp.1-11
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• 2015

Enterprise Risk Management(ERM) is aiming at the establishment of the risk management process to prevent and cope with risks in advance and is composed of Risk Identification, Risk Assessment, Risk Response and Monitoring. It is feedback through the Risk Re-identification. This study has analysed a sample of the risk management system of an airport operating corporation, for this purpose, relevant documents and examples of overseas airports have been reviewed. It has found that corporations establishing ERM have been performing identical procedures such as the process of Identification, Assessment, Effective Reporting, Communication and monitoring and so on. The A corporation has established the process for risk management and crisis management and organized for its organization and system. The risk management has the same process such as above. In this process, when the symptoms of critical crisis have been recognized, it has been transformed into crisis management system, through which, corporate-wide response has been conducted in the process of crisis status analysis, response and follow-up management. This study expects to contribute to systematic foundation for future business continuity on the basis of risks and response procedures acknowledged by this study.

• 한국지진공학회논문집
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• 제25권6호
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• pp.283-292
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• 2021

In this study, a structural health monitoring system for cable-stayed bridges is developed. In the system, condition assessment of the structure is performed based on measured records from seismic accelerometers. Response indices are defined to monitor structural safety and serviceability and derived from the measured acceleration data. The derivation process of the indices is structured to follow the transformation from the raw data to the outcome. The process includes noise filtering, baseline correction, numerical integration, and calculation of relative differences. The system is packed as a condition assessment program, which consists of four major processes of the structural health evaluation: (i) format conversion of the raw data, (ii) noise filtering, (iii) generation of response indices, and (iv) condition evaluation. An example set of limit states is presented to evaluate the structural condition of the test-bed and cable-stayed bridge.

• Structural Engineering and Mechanics
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• 제90권2호
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• Fibers and Polymers
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• 제7권4호
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• pp.436-441
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• 2006

An integrated platform for garment drape simulation system has been developed. In this system, garment patterns from conventional two-dimensional CAD systems can be assembled into a three-dimensional garment on a parametrically resizable realistic human body model. A fast and robust particle-based physical calculation engine has been developed for garment shape generation. Then a series of geometric and graphical techniques were applied to create realistic impressions on simulated garments. This system can be used as the rapid prototyping tool for garments in the future quick-response system.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 추계학술대회 논문집
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• pp.199-201
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• 2007

This paper presents the installation of measuring system for the transient behaviors of grounding system impedances using portable impulse current generator. The measuring system is controller, with controller, power supply, impulse current generator and data aquisition system. In the evaluation of the impulse response in a ground electrode, the step response is calculated based on the ratio of the voltage and current observed.

• 한국공작기계학회논문집
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• 제18권2호
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• pp.187-193
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• 2009

Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.

• 소음진동
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• 제7권6호
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• pp.1049-1058
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• 1997

To verify the Finite Element Method(FEM) model of an Exhaust System, Frequency Response Function(FRF) is utilized. Up to now, generally, comparisons of natural frequencies and mode shapes of the Exhaust System between numerical analysis and experimental results are adopted to prove completion of the FEM model. However, the comparisons of natural frequencies and mode shapes are not sufficient to have the perfect FEM model of the Exhaust system. Instead of these comparisons. FRF method is introduced for the more accurate FEM model.