• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.328-338
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• 2006

A new evolutionary computation technique, called particle swarm optimization(PSO), has been proposed and introduced recently. PSO has been inspired by the social behavior of flocking organisms, such as swarms of birds and fish schools and PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. In this paper, characteristics of PSO such as mentioned are reviewed and compared with GA which is based on the evolutionary mechanism in natural selection. Also dimensionalities of PSO and GA are compared throughout numeric experimental studies. The comparative studies demonstrate that PSO is characterized as simple in concept, easy to implement, and computationally efficient and can generate a high-quality solution and stable convergence characteristic than GA.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1273-1276
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• 1998

The HMM-Net is an architecture for a neural network that implements a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria used for learning HMM-Net classifiers are maximum likelihood (ML), maximum mutual information (MMI), and minimization of mean squared error(MMSE). In this paper we propose an efficient learning method of HMM-Net classifiers using hybrid criteria, ML/MMSE and MMI/MMSE, and report the results of an experimental study comparing the performance of HMM-Net classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numeric digits from /0/ to /9/ show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.350-353
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• 2003

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experiment81 results of the simulation.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2098-2106
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• 2014

In the area of clustering, there are numerous approaches to construct clusters in the input space. For regression problem, when forming clusters being a part of the overall model, the relationships between the input space and the output space are essential and have to be taken into consideration. Conditional Fuzzy C-Means (c-FCM) clustering offers an opportunity to analyze the structure in the input space with the mechanism of supervision implied by the distribution of data present in the output space. However, like other clustering methods, c-FCM focuses on the distribution of the data. In this paper, we introduce a new method, which by making use of the ambiguity index focuses on the boundaries of the clusters whose determination is essential to the quality of the ensuing classification procedures. The introduced design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the fuzzy classifiers and quantify several essentials design aspects.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.933-935
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• 1998

The HMM-Net is an architecture for a neural network that implements a hidden markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria used for learning HMM-Net classifiers are maximum likelihood(ML) and minimization of mean squared error(MMSE). In this paper we propose an efficient learning method of HMM_Net classifiers using a ML-MMSE hybrid criterion and report the results of an experimental study comparing the performance of HMM_Net classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numeric digits from /0/ to /9/ show that the performance of the proposed method is better than the others in the repects of learning and recognition rates.

• 대한기계학회논문집A
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• 제33권1호
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• pp.42-48
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• 2009

A design methodology for control strategy and control structure gives a direct impact on wind turbine's performance and life cycle. A baseline control law which is a variable rotor speed and variable pitch control strategy is introduced, and a mathematic performance model of a wind turbine dynamics is derived. By using a numeric optimization algorithm, the steady state operating conditions of wind turbines are identified. Because aerodynamic interaction of winds with rotor blades is basically nonlinear, a linearization procedure is applied to analyze wind turbine dynamic variations for whole operating conditions. It turns out the wind turbine dynamics vary much depending on its operating condition.

• International Journal of Internet, Broadcasting and Communication
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• 제8권3호
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• pp.63-68
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• 2016

This thesis proposed an objective and accurate fundamental numeric data for the economics and business analysis of applicable CCS technology to plant using existing fossil fuel by analyzing the influence of process improvement for commercialization of Carbon Capture and Storage(CCS) technology, which enables storing $CO_2$ generated by fossil fuel by extracting before emitting to air and press until it becomes liquid, and development and performance improvement of new solvent on Total Life Cycle Cost(TLC) of CCS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.154-156
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• 1995

The effect of a periodic and a chaotic' behaviour in the Bonhoeffer-Van der Pol(BVP) oscillation of the nerve membrane driven by a periodic stimulating current $A_1=cos\;{\omega}\;t$ are investigated by numeric analysis and hardware Implementation. To control the chaotic motion, we are suggested by temperature parameter c, $c=c(1+\eta\;cos\;{\Omega}\;t)$ which the values of $\eta,\;Omega$ varied respectively. The feasibilities of chaotic and periodic phenomena were analysed by phase plane and time series.

• 한국대기환경학회지
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• 제20권3호
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• pp.303-315
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• 2004

The change of land use such as the construction of way in mountainous area and tunnel leads to the quantitative change of the greenhouse gas. This study tried to clarify the effect of the change of land use around Miryang Ice Valley on thermal environment of micro-meteorological scale by numerical experiment. We carried out several numerical experiment under different atmospheric conditions with different amount of greenhouse gases. Heating rate increased by the greenhouse gas in the ground level is average of 0.0073 K/day. And the increasing rate if smaller than the daily average heat crossing quantity.

• International Journal of Control, Automation, and Systems
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• 제3권1호
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• pp.15-31
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• 2005

Nowadays, the road safety is an important research field. One of the principal research topics in this field is the vehicle localization in the road network. This article presents an approach of multi sensor fusion able to locate a vehicle with a decimeter precision. The different informations used in this method come from the following sensors: a low cost GPS, a numeric camera, an odometer and a steer angle sensor. Taking into account a complete model of errors on GPS data (bias on position and nonwhite errors) as well as the data provided by an original approach coupling a vision algorithm with a precise numerical map allow us to get this precision.