• 대한토목학회논문집
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• 제26권2D호
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• pp.251-258
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• 2006

본 연구에서는 개별차량의 차두시간분포 분석을 통해 고속도로 설계용량 산정모형을 개발하였으며 연구결과를 요약하면 다음과 같다. 교통류 기본관계와 차두시간 분포특성을 분석한 결과, 1) 개별차량 자료로부터 작성한 속도-교통량 관계는 선형을 이루지 않고 상당한 편차가 있는 분포를 이루고 있었으며, 2) 속도별 차두시간의 통계적 분포는 Pearson type V 분포의 형태로 추정하였을 경우 통계적 검정값이 가장 우수하였다. 새로운 고속도로 설계용량 산정모형은 기존 미국 도로용량편람의 용량의 정의에 본 연구의 결과인 속도별 최소차두시간의 통계적 정의를 포함시킴으로써 개발하였다. 새로운 고속도로 설계용량 산정모형에 의해 설계속도별로 산정한 용량수준을 기존의 용량편람에서 제시한 용량과 비교한 결과, 본 연구에서 제시한 도로설계 시 기준용량은 설계속도 80km/h 이하에서는 기존 용량편람보다 낮게, 설계속도 106km/h 이상에서는 기존 용량편람보다 높게 평가되었다. 더불어 본 연구 결과와 기존 용량편람의 큰 차이점은 용량을 확률분포로 정의함으로써 도로 설계 시 용량수준을 유연하게 적용할 수 있다는 사실이다. 다시 말해 본 연구는 도로설계 시 차로수 산정에 있어 기존의 단 한대의 추가 수요가 발생하더라도 한 차로를 추가하여야 하는 비효용에 대한 이론적 반론을 제시하고 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.306-309
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• 2003

This paper presents a speed estimation algorithm of Switched Reluctance Motor(SRM) using flux-linkage modeling. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation and experimental data was used for neural network training. Through measurement of the phase flux linkage and phase currents, the neural network is able to estimate the rotor position and speed. The simulation result shows some good results, and possibility of this algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.244-247
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• 2003

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. A minimum order state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A minimum order state observer is implemented to compute the speed and Position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

• Advances in environmental research
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• 제4권4호
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• pp.211-218
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• 2015

Traffic noise estimation models are useful in evaluation of the noise pollution in current circumstances. They are helpful tools for design and planning new roads and highways. Measurement of average traffic noise level is possible when traffic speed and volume are known. The objective of this study was to devise a model for prediction of highway traffic noise levels based on current traffic variables in Iran. The design of this model was to take the impact of traffic congestion into consideration and to be field tested. This study is a library research augmented by field study conducted on Saeedi Highway located south west of Tehran. The period for the field study lasted 5 days from 7-12 February, 2013. This study examined liner and non-liner methods in formulation of its model. Liner method without a fixed coefficient was the best fit for the intended model. The proposed model can serve as a decision making tool to estimate the impact of key influential factors on sound pressure levels in urban areas in Iran.

• ETRI Journal
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• 제25권5호
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• pp.418-421
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• 2003

We propose an unbiased signal-to-interference ratio (SIR) estimator for the high speed downlink packet access (HSDPA) system. The proposed SIR estimator solves the problem of underestimation present in conventional SIR estimators and is suitable for channel quality measurement in the adaptive modulation and coding scheme of HSDPA, which requires accurate SIR estimation for optimum adaptive modulation and coding selection. Our analysis and simulation results demonstrate the improved estimation performance of the proposed SIR estimator.

• 한국전자통신학회논문지
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• 제9권12호
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• pp.1373-1380
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• 2014

교통정보서비스에서 정확한 통행량과 통행속도를 산출하기 위해서는 기본적으로 제공되는 GPS 데이터의 품질이 보장되어야 한다. 그렇지만, 통신비용의 문제로 인하여 GPS 데이터를 제공하는 Probe 차량으로부터 제한된 GPS 데이터가 제공이 된다면 정확한 정보를 제공하기 어렵다. 본 논문에서는 제한된 GPS 데이터로 인하여 손실되는 링크들을 위상정보와 결합시켜 복원시킨 후, 통행 속도를 산출하는 알고리즘을 개발하였다. 이를 적용한 S시의 T 교통정보서비스는 이전보다 더 정확한 통행량 및 통행 속도를 시민들에게 제공할 수 있게 되었다.

• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.267-272
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• 2010

For the last decade, recurrent neural networks (RNNs) have been commonly applied to communications channel equalization. The major problems of gradient-based learning techniques, employed to train recurrent neural networks are slow convergence rates and long training sequences. In high-speed communications system, short training symbols and fast convergence speed are essentially required. In this paper, the derivative-free Kalman filter, so called the unscented Kalman filter (UKF), for training a fully connected RNN is presented in a state-space formulation of the system. The main features of the proposed recurrent neural equalizer are fast convergence speed and good performance using relatively short training symbols without the derivative computation. Through experiments of nonlinear channel equalization, the performance of the RNN with a derivative-free Kalman filter is evaluated.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권3호
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• pp.289-297
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• 2014

This paper proposed a novel high performance sensorless control scheme for IPMSM based on an extended nonlinear state observer. The gain-matrix of the observer has been derived by using state linearization method. Steady state errors in estimated rotor position and speed due to parameter inaccuracy have been analyzed, and an equivalent flux error is defined to represent the overall effect of parameter errors contributing to the wrong convergence of the estimated rotor speed as well as rotor position. Then, an online compensation strategy was proposed to limit the estimation errors in rotor position and speed. The effectiveness of the extended nonlinear state observer is validated through simulation and experimental test.

• 전자공학회논문지B
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• 제30B권8호
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• pp.54-63
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• 1993

This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

• 산업기술연구
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• 제33권A호
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• pp.41-48
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• 2013

A statistical downscaling methodology has been developed to investigate future daily wind speeds over South Korea. This methodology includes calibration of the statistical downscaling model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, validation of the model for the calibration period, and estimation of the future wind speed based on the general circulation model (GCM) outputs of scenario A1B of the CGCM3. Based on the scenario A1B of the CGCM3 model, the potential impacts of climate change on the daily surface wind speed is relatively small (+/- 1m/s) in South Korea.