• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.176-178
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• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1006-1025
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• 2012

Improving the quality of service in IP networks is a major challenge for real-time voice communications. In particular, packet arrival-delay variation, so-called "jitter," is one of the main factors that degrade the quality of voice in mobile devices with the voice-over Internet protocol (VoIP). To resolve this issue, a receiver-based enhanced timing recovery algorithm combined with active jitter estimation is proposed. The proposed algorithm copes with the effect of transmission jitter by expanding or compressing each packet according to the predicted network delay and variations. Additionally, the active network jitter estimation incorporates rapid detection of delay spikes and reacts to changes in network conditions. Extensive simulations have shown that the proposed algorithm delivers high voice quality by pursuing an optimal trade-off between average buffering delay and packet loss rate.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1768-1769
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• 2011

The nonlinear estimation and the pseudo-linear estimation are used to treat the target localization in sensor network which provides range difference of arrival (RDOA) measurements. It is known that the nonlinear estimation has sensitive problem for the initial estimate and the pseudo-linear estimation has a large estimation error. The QCLS method is the typical estimator of the methods for pseudo-linear estimation. However the estimate by using the QCLS method includes the estimation error because the first stage of two estimation processes of the QCLS method causes the biased estimation error. Therefore we propose a instrumental variables(IV) method for minimizing the estimation error of the first stage. The simulation shows that the performance of the proposed method is superior to the QCLS method.

• 대한전기학회논문지
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• 제45권2호
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• pp.325-328
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• 1996

In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2003년도 추계학술대회
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• pp.616-623
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• 2003

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However if we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.344-346
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• 2019

본 논문에서는 Ultra-Wideband(UWB) 시스템에서 합성곱 신경망을 이용한 거리 추정 기법을 제안한다. 합성곱 신경망을 이용한 딥러닝 모델을 학습하는데 사용하는 학습 데이터는 MATLAB 프로그램을 통해 생성하였으며, IEEE 802.15.4a 표준을 활용한다. 기존 거리 추정에 사용하는 문턱값 기반의 거리추정 기법과 성능 비교를 통해 제안하는 거리 추정 기법의 성능을 검증한다.

• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.17-22
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• 2024

Software cost and schedule estimation is usually based on the estimated size of the software. Advanced estimation techniques also make use of the diverse factors viz, nature of the project, staff skills available, time constraints, performance constraints, technology required and so on. Usually, estimation is based on an estimation model prepared with the help of experienced project managers. Estimation of software cost is predominantly a crucial activity as it incurs huge economic and strategic investment. However accurate estimation still remains a challenge as the algorithmic models used for Software Project planning and Estimation doesn't address the true dynamic nature of Software Development. This paper presents an efficient approach using the contemporary Constructive Cost Model (COCOMO) augmented with the desirable feature of fuzzy logic to address the uncertainty and flexibility associated with the cost drivers (Effort Multiplier Factor). The approach has been validated and interpreted by project experts and shows convincing results as compared to simple algorithmic models.

• 한국측량학회지
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• 제36권5호
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• pp.335-341
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• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• 한국습지학회지
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• 제16권1호
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• pp.103-112
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• 2014

면적평균강우량의 산정은 가용 수자원의 정확한 양을 파악하고 강우-유출해석에 필수적인 입력자료이기 때문에 매우 중요하다. 이와 같은 면적평균강우량의 정확한 산정을 위한 필수적인 조건은 강우관측망의 균일한 공간적 분포이다. 본 연구에서는 보다 향상된 유역 면적평균강우량 산정을 위한 강우관측망의 공간분포 평가방법론을 제시하고, 이를 한강 및 금강 유역에 적용하였다. 강우관측소의 공간적 분포 특성은 최근린 지수(nearest neighbor index)를 이용하여 정량화하였다. 유역별 강우관측소의 공간적 분포가 면적평균강우량 산정에 미치는 영향을 평가하기 위하여 2013년의 강우사상에 대해 산술평균법, 티센가중법, 추정이론을 이용하여 면적평균강우량을 산정하고 각 경우에 대해 추정오차를 평가하였다. 그 결과 공간분포가 우수한 유역은 면적평균강우량의 추정오차가 상대적으로 작으며, 반대로 공간분포가 왜곡된 유역의 경우는 상대적으로 추정오차가 큼을 확인하였다.

• 조명전기설비학회논문지
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• 제28권10호
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• pp.27-36
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• 2014

Network analysis applications in energy management systems play a key role in the economic and reliable operation of power systems. In order to provide operators with useful network information, the accurate results of topology processing, state estimation, power flow, and contingency analysis must be simulated. This paper proposes a validation methodology of network analysis applications in energy management systems. The energy management systems was checked to ensure that it meets the originally specified functions based on the proposed methodology. In addition, the performance of state estimation is evaluated with the reference of the proposed methodology. The proposed methodology is being conducted by energy management systems and the Korean power systems have been utilized for the test systems.