• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1763-1772
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• 1996

The conventional training set selection methods for the satellite image classification usually depend on the manual selection using data from the direct measurements of the ground or the ground map. However this task takes much time and cost, and some feature values vary in wide ranges even if they are in the same class. Such feature values can increase the robustness of the neural net but learning time becomes longer. In this paper,we propose anew training set selection algorithm using a rule-based method. By the technique proposed, the SPOT multispectral Imagery is classified in 3 bands, and the pixels which satisfy the rule are employed as the training sets for the neutralist classifier. The experimental results show faster initial convergence and almost the same or better classification accuracy. We also showed an improvement of the classification accuracy by using texture features and NDV1.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1171-1179
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• 2004

We describe word boundary detection that extracts the boundary between speech and non-speech. The proposed method uses two features. One is the normalized root mean square of speech signal, which is insensitive to white noises and represents temporal information. The other is the normalized met-frequency band energy of voice signal, which is frequency information of the signal. Our method detects word boundaries using a recurrent fuzzy associative memory(RFAM) that extends FAM by adding recurrent nodes. Hebbian learning method is employed to establish the degree of association between an input and output. An error back-propagation algorithm is used for teaming the weights between the consequent layer and the recurrent layer. To confirm the effectiveness, we applied the suggested system to voice data obtained from KAIST.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1934-1938
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• 2008

In this study, the landuse pattern at the Gab river is analyzed using time-series aerial images. This study area is divided by two zones like as inland and floodplain. To begin with, in inland, the landuse area of items such as residential, road, industrial, public facilities is increased by following the urbanization. On the other hand, the area of the other items such as agricultural, forest and river is decreased. Also, the inclination of those two groups is reversed around 1988. Form the results, it is clarified that the Gab river is urbanized around 1988. In floodplain, the area of river is decreased as time goes by. This result means that the area of landuse factors such as level-upped riverside land, bridge, head work is increased conversely. Also, the proportion of the water to the river considering the hydrologic factor like rainfall is increased as time goes by. Overall, it is concluded that aerial image can be applied to get a landuse information that is needed in river management and planning.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.51-65
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• 2002

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1159-1163
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• 2010

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이다. 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 수위자료로부터 단시간 수위예측에 관해 연구하였다. 신경망은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 연결강도를 최적화함으로서 모형의 구조를 스스로 조직화하기 때문에 모형의 구조에 적합한 최적 매개변수를 추정할 수 있다. 따라서 정확한 예측이 어려운 하천수위를 과거의 자료로 부터 학습된 신경망의 수학적 알고리즘을 통해 유출량의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 따라서 본 연구에서는 인공신경망의 가중치를 유전자 알고리즘에 의해 최적화시킨후 오류역전파알고리즘에 의해 신경망의 학습을 진행하는 모형으로 감천유역의 선산수위표지점의 수위를 1시간~6시간까지 예측하였다.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.853-860
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• 2012

It is well-known that loop effect of the stage-discharge relationship is formulated based on many field observations especially for the sand rivers. Theoretical understandings of the loop effect for the sand rivers have been widely provided, based on the facts that it is driven by the flood wave propagation and bed form changes over the given flood period. However, very few theoretical studies or field observations associated with loop-rating curves in the gravel or rock-bed mountain streams have been attempted so far, due particularly to the difficulties in the accurate discharge measurement during the flood in such field conditions. The present paper aims to report a unique loop-rating curve measured at a gravel and rock-bed mountain stream based on the flood discharge observation acquired during the typhoon, Muifa that passed nearby Jeju Island in summer of 2011. As velocity instrumentation, a non-intrusive Surface Velocity Doppler Radar to be suitable for the flood discharge measurement was utilized, and discharges were consecutively measured for every hour. Interestingly, the authors found that the hysteresis of the loop-rating curve was adverse compared to the typical trend of the sand bed streams, which means that the discharge of the rising limb is smaller than the falling limb at the same stage. We carefully speculate that the adverse trend of the loop-rating curve in the gravel bed was caused by the bed resistance change that works differently from the sand bed case.

• Korean Journal of Materials Research
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• v.4 no.1
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• pp.81-89
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• 1994

Ti film of lOnm thickness and Co film of 18nm thickness were sequentially e-heam evaporated onto Si (100) substrates. Metal deposited samples were rapidly thermal-annt.aled(KTA) in thr N1 en vironment a t $900^{\circ}C$ for 20 sec. to induce the reversal of metal bilayer, so that $CoSi_{2}$ thin films could be formed. The sheet resistance measured by the 4-point probe was 3.9 $\Omega /\square$This valur was maintained with increase in annealing time upto 150 seconds, showing high thermal stab~lity. Thc XRII spectra idrn tified the silicide film formed on the Si substrate as a $CoSi_{2}$ epitaxial layer. The SKM microgr;iphs showed smooth surface, and the cross-sectional TKM pictures revealed that the layer formed on the Si substrate were composed of two Co-Ti-Si alloy layers and 70nm thick $CoSi_{2}$ epl-layer. The AES analysis indicated that the native oxide on Si subs~rate was removed by TI ar the beginning of the RTA, and Ihcn that Co diffused to clean surface of Si substrate so that epitaxial $CoSi_{2}$ film could bt, formed. In thc rasp of KTA at $700^{\circ}C$. 20sec. followed by $900^{\circ}C$, 20sec., the thin film showed lower sheet resistance, but rough surface and interface owing to $CoSi_{2}$ crystal growth. The application scheme of this $CoSi_{2}$ epilayer to VLSI devices and the thermodynarnic/kinetic mechan~sms of the $CoSi_{2}$ epi-layer formation through the reversal of Co/Ti bdayer were discussed.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.189-198
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• 2009

The traditional interrupt-based protocol processing at end hosts has two priority-inversion problems. First, low-priority packets may interrupt and delay high-priority process executionssince interrupts have the highest priority in most operating systems. Second, low-priority packet may delay high priority packets when they arrive almost simultaneously since interrupt processing is performed in a FCFS (first come, first served) order. These problems can be solved by a priority-based protocol processing policy and implementation. However, general priority-based schemes commonly have the problem of starvation and cannot support the each network flow requiring the mutually exclusive QoS since the packets are processed in the FCFS order. Therefore, the priority-based schemes are not appropriate for different QoS-demanding applications. In this paper, we present a bottom-half-based approach that relies on priority- and budget-based processing. The proposed approach allows us to solve both the starvation and priority-inversion problems, and further enables effective QoS isolation between different network connections. This feature also enables bounding the protocol processing time at an end host. We finally show through experiments that the proposed approach achieves QoS isolation and control.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.