• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1145-1150
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• 1993

In this paper, two methods of fuzzy modeling are prsented to describe the input-output relationship effectively based on relation characteristics utilizing simplified reasoning and neuro-fuzzy reasoning. The methods of modeling by the simplified reasoning and the neuro-fuzzy reasoning are used when the input-output relation of a system is 'crisp' and 'fuzzy', respectively. The structure and the parameter identification in the modeling method by the simplified reasoning are carried out by means of FCM clustering and the proposed GA hybrid scheme, respectively. The structure and the parameter identification in the modeling method by the neuro-fuzzy reasoning are carried out by means of GA and BP algorithm, respectively. The feasibility of the proposed methods are evaluated through simulation.

• 전기학회논문지
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• 제61권7호
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• pp.1007-1013
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• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• 한국정밀공학회지
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• 제14권2호
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• pp.136-144
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• 1997

Usually triangular patches are used to transfer geometric shape in Rapid Prototyping CAM system. STL, a list of triangles, is de facto standard in RP industry. Because STL does not have topological infoma- tion, it can cause errornous results. So STL should be verified before using. After adding support structures to anchor the part to the platform and to prevent sagging or distortion, slicing and layer by layer manufactur- ing process are done. But triangular patch is surface model and cannot provide sufficient information on geometry in the above processes. So, geometric modeling is necessary in verifying STL, adding support structures and slicing. It is natural that triangle based modeling is the best when tringular patches are used as input. Considering support structures, solid and faces coexist in RP process. Therefore non-manifold modeler is required. In this study, triangle based non-manifold geometric modeling is proposed for RP sys- tem consistent with STL input.

• 한국컴퓨터그래픽스학회논문지
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• 제23권5호
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• pp.29-38
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• 2017

본 논문은 나뭇가지 패턴을 의자의 골격에 임의로 합성하는(Tree-Inspired Chair) 모델링 기법을 제안한다. 여러 개의 입력모델을 합성하는 기존 기법과 다르게, 제안 기법은 하나의 메쉬만 사용하여, 사용자가 원하는 부분의 contour mesh로부터 나무 성장 시뮬레이션으로 생성된 패턴을 갖는 의자 모델링이 가능하다. 우리는 나뭇가지 패턴을 생성시킬 영역 contour mesh를 효율적으로 추출하기 위하여 새로운 기법을 제안한다. 우선, 입력된 모델의 face 면적에 기반한 contour mesh를 생성하고, 그 메쉬의 앞뒷면 정보를 이용하여 연결정보가 복원된 skeleton mesh를 생성한다. 또한, 입력 모델의 형상과 유사하게 나뭇가지 패턴을 생성하기 위해 형상 표면의 tangent vector를 고려하는 3-way 나무성장 시뮬레이션 기법을 제안한다. 제안기법은 기존의 가구 모델을 이용하여 간단한 파라미터의 조작만으로 나뭇가지 형상과 가구 모델의 골격을 결합하는 새로운 형태의 가구 모델링을 보여준다. 우리는 실험을 통하여 제안 기법의 성능과 유효성을 보여주었다.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.189-200
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• 2004

In this paper, we introduce a new soft computing technique that dwells on the ideas of combining fuzzy rules in a fuzzy system with polynomial neural networks (PNN). The PNN is a flexible neural architecture whose structure is developed through the modeling process. Unfortunately, the PNN has a fatal drawback in that it cannot be constructed for nonlinear systems with only a small amount of input variables. To overcome this limitation in the conventional PNN, we employed one of three principal soft computing components such as a fuzzy system. As such, a space of input variables is partitioned into several subspaces by the fuzzy system and these subspaces are utilized as new input variables to the PNN architecture. The proposed soft computing technique is achieved by merging the fuzzy system and the PNN into one unified framework. As a result, we can find a workable synergistic environment and the main characteristics of the two modeling techniques are harmonized. Thus, the proposed method alleviates the problems of PNN while providing superb performance. Identification results of the three-input nonlinear static function and nonlinear system with two inputs will be demonstrated to demonstrate the performance of the proposed approach.

• 한국입자에어로졸학회지
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• 제7권3호
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• pp.99-108
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• 2011

To establish area specific control strategies for the reduction of the ozone concentration, the Ozone Isopleth Plotting Package for Research(OZIPR) model has been widely used. However, the model results tend to changed by various input parameters such as the background concentration, emission amount of NOx and volatile organic compounds (VOCs), and meteorological condition. Thus, sensitivity analysis should be required to ensure the reliability of the result. The OZIPR modeling results for five local government districts in the Seoul Metropolitan Area (SMA) in June 2000 were used for the sensitivity analysis. The sensitivity analysis result showed that the modeling result of the SMA being VOC-limited region be still valid for a wide range of input parameters' variation. The estimated ozone concentrations were positively related with the initial VOCs concentrations while were negatively related with the initial NOx concentrations. But, the degree of the variations at each local district was different suggesting area specific characteristics being also important. Among the five local governments, Suwon was chosen to identify other variance through the period from April to September in 2000. The monthly modeling results show different ozone values, but still showing the characteristics of VOCs-limited region. Limitations due to not considering long range transport and transfer from neighbor area, limitation of input data, error between observed data and estimated data are all discussed.

• 대한전기학회논문지
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• 제45권1호
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• pp.113-122
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• 1996

As integrity of semiconductor device is increased, accurate and efficient modeling and recipe generation of semiconductor fabrication procsses are necessary. Among the major semiconductor manufacturing processes, dry etc- hing process using gas plasma and accelerated ion is widely used. The process involves a variety of the chemical and physical effects of gas and accelerated ions. Despite the increased popularity, the complex internal characteristics made efficient modeling difficult. Because of difficulty to determine the control input for the desired output, the recipe generation depends largely on experiences of the experts with several trial and error presently. In this paper, the optimal control of the etching is carried out in the following two phases. First, the optimal neural network models for etching process are developed with genetic algorithm utilizing the input and output data obtained by experiments. In the second phase, search for optimal control inputs in performed by means of using the optimal neural network developed together with genetic algorithm. The results of study indicate that the predictive capabilities of the neural network models are superior to that of the statistical models which have been widely utilized in the semiconductor factory lines. Search for optimal control inputs using genetic algorithm is proved to be efficient by experiments. (author). refs., figs., tabs.

• 환경영향평가
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• 제22권5호
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• pp.537-546
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• 2013

In the Seoul Metropolitan Area(SMA) photochemical air pollutants, nitrogenic compound and particulate matters have increased substantially due to mobile sources, power plants and so on. Therefore 'Special Act on Seoul Metropolitan Air Quality Improvement' was enacted on 2003 in order to improve air quality in the SMA. According to the Special Act, Central and local government have developed the state implementation plan(SIP) to reduce air pollutant emissions from various local sources. One of the key elements of the SIP development is the air quality modeling since modeling results can be used to establish emissions control strategies as well as to demonstrate attainment of air quality goals for ozone, particulate matter, and so on. Air quality modeling, therefore, can be usefully utilized to investigate the effects of government's efforts according to control strategies or measures. Using the air quality model, we can determine whether the implementation plan should be revised or not. A number of questions, however, has been raised concerning accuracy, consistency and transparency of modeling results because if we do not trust modeling results, all the measures dependent on modeling becomes in vain. So, without dealing with these questions, we can not guarantee the reliability and utilizability of air quality modeling results. In this study, we tried to establish standard methodology for air quality modeling in order to ensure consistency and transparency of modeling results used in the development and evaluation of national air policy. For this purpose, we established air quality modeling guideline to provide or recommend modeling procedures, vertical and horizontal domains, input data of meteorological and air quality modeling and so on.

• 한국음향학회지
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• 제26권8호
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• pp.426-431
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• 2007

본 논문에서는 수중 채널 환경에서 초음파 통신의 성능 및 효율을 향상시키기 위하여 MIMO(Multiple Input Multiple Output) 용 수중 벡터 채널 모델링을 연구하였으며, 이를 이용한 MIMO 기법의 성능을 분석하였다. 수중 MIMO 채널 모델링을 위하여 실해역 환경에서 측정을 수행하였으며, 측정된 데이터를 분석하여 수중 채널 환경에서의 페이딩, 도플러, 시간지연, 도달각, 수신전력 등의 파라미터 값을 추정하였고, 이를 이용한 MIMO용 수중 벡터 채널 모델링을 수행하였다. 또한 제안된 채널 모델링을 이용하여 수중 MIMO 시스템의 성능을 분석하였으며, 성능 분석 결과 수중에서 MIMO 기법을 사용하는 경우 같은 SNR에 대해 비트 에러 율이 크게 감소함을 알 수 있었다.

• 한국해양공학회지
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• 제13권3B호
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• pp.91-98
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• 1999

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, if the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom(2DOF) servosystem has been proposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. The present paper considers a synthesis problems of this 32DOF servosystem with direct transfer term in the system representation. And, a method how we may obtain a gain such that desirable transient response is achieved, is proposed in the presence of the modelling error and disturbance input.