• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.359-365
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion(FBFE) based on virus evolutionary genetic algorithm (VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter(EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FDFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by idenLifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.81-90
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• 2006

It is important to clarify the relationship between traffic accidents and various influencing factors in order to reduce the number of traffic accidents. This study developed a traffic accident frequency prediction model using by multi-linear regression and qualification theories which are commonly applied in the field of traffic safety to verify the influences of various factors into the traffic accident frequency The data were collected on the Korean National Highway 17 which shows the highest accident frequencies and fatality rates in Chonbuk province. In order to minimize the uncertainty of the data, the fuzzy theory and neural network theory were applied. The neural network theory can provide fair learning performance by modeling the human neural system mathematically. Tn conclusion, this study focused on the practicability of the fuzzy reasoning theory and the neural network theory for traffic safety analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.907-913
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• 2004

The major interest of general mobile robot is making a route and following a maked route. But, In the case of robot that is in need of movement of partial high speed, the condition of dynamic limitation is exist, and in these conditions, it demands controlling against movements we want. In this paper, in respect of the following a route at the situation that don't have the environmental map, that is, unknown environments, to prevent the slide of moving robot or the overturn that can happen for it moves fast, we organize the dynamic condition of limitation using the fuzzy logic, and we obtain more safe and fast route tracing ability by changing the standard velocity. Especially, by modeling the line tracing mobile robot, we design the tracing controller against a realtime changing target, and using the fuzzy optimized velocity limitation controller, we confirm that our robot shows its stable tracing ability by limiting its velocity intelligently against the continuously changing line.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.500-506
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• 2012

A method to model left ventricular assist device (LVAD) and detect suction occurrence for safe LVAD operation is presented. An axial flow blood pump as a LVAD has been used to assist patient with heart problems. While an axial flow blood pump, a kind of a non-pulsatile pump, has relative advantages of small size and efficiency compared to pulsatile devices, it has a difficulty in determining a safe pump operating condition. It can show different pump operating statuses such as a normal status and a suction status whether suction occurs in left ventricle or not. A fuzzy subtractive clustering method is used to determine a model of the axial flow blood pump with this pump operating characteristic and the developed pump model can provide blood flow estimates before and after suction occurrence in left ventricle. Also, a fuzzy subtractive clustering method is utilized to develop a suction detection model which can identify whether suction occurs in left ventricle or not.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• Journal of The Geomorphological Association of Korea
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• v.24 no.1
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• pp.77-91
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• 2017

Many debris landforms in the mountains of Korea have formed in the periglacial environment during the last glacial stage when the generation of sediments was active. Because these landforms are generally located on steep slopes and mostly covered by vegetation, however, it is difficult to observe and access them through field investigation. A scientific method is required to reduce the survey range before performing field investigation and to save time and cost. For this purpose, the use of remote sensing and GIS technologies is essential. This study has extracted the potential area of debris landform formation using a fuzzy set model as a mathematical data integration method. The first step was to obtain information about the location of debris landforms and their related factors. This information was verified through field observation and then used to build a database. In the second step, we conducted the fuzzy set modeling to generate a map, which classified the study area based on the possibility of debris formation. We then applied a cross-validation technique in order to evaluate the map. For a quantitative analysis, the calculated potential rate of debris formation was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). The prediction accuracy of the model was found to be 83.1%. We posit that the model is accurate and reliable enough to contribute to efficient field investigation and debris landform management.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.401-404
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• 2007

본 논문은 거울 투영을 이용하여 2D의 감정인식 데이터베이스를 3D에 적용 가능하다는 것을 증명한다. 또한, 감정 확률을 이용하여 퍼지 모델링을 기반으로한 얼굴표정을 생성하고, 표정을 움직이는 3가지 기본 움직임에 대한 퍼지이론을 적용하여 얼굴표현함수를 제안한다. 제안된 방법은 거울 투영을 통한 다중 이미지를 이용하여 2D에서 사용되는 감정인식에 대한 특징벡터를 3D에 적용한다. 이로 인해, 2D의 모델링 대상이 되는 실제 모델의 기본감정에 대한 비선형적인 얼굴표정을 퍼지를 기반으로 모델링한다. 그리고 얼굴표정을 표현하는데 기본 감정 6가지인 행복, 슬픔, 혐오, 화남, 놀람, 무서움으로 표현되며 기본 감정의 확률에 대해서 각 감정의 평균값을 사용하고, 6가지 감정 확률을 이용하여 동적 얼굴표정을 생성한다. 제안된 방법을 3D 인간형 아바타에 적용하여 실제 모델의 표정 벡터와 비교 분석한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.585-590
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• 1998

The purpose of this paper is to develop a neurofuzzy modeling & inference system which can determine principle dimensions and hull factors in an initial ship design. Neurofuzzy modeling & inference for a hull form design (NeFHull) applies the given input-output data to the fuzzy theory. NeFHull also deals the fuzzificated values with neural networks. NeFHull redefines normalized input-output data as membership functions and executes the fuzzficated information with backporpagation-neural -networks. A hybrid learning algorithms utilized in the training of neural networks and examining the usefulness of suggested method through mathematical and mechanical examples.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.41-51
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• 2001

In this paper, the mathematical modeling and the design of controllers were performed for the dynamic performance simulation of the diesel engine for underwater vehicle. Nonlinear equations are acquired through the mathematical modeling using mean torque production model technique. Three kinds of controllers were designed for the perform simulation of the engine model. As the result of simulation, it was confirmed that each controller can be applied with regard to system characteristics and desired conditions etc.