• 해양환경안전학회지
• /
• 제24권4호
• /
• pp.381-388
• /
• 2018

본 연구에서는 선박의 속력을 고려한 해상교통량 평가 방법을 제안하였으며, 이를 선박의 속력을 고려하지 않은 기존의 방법과 비교하였다. 평가를 위하여 평택 당진항 10일간의 GICOMS 자료를 본 연구에 적용하였다. 그 결과 제안된 방법으로 평가된 환산교통량은 기존의 평가 방법에 비해 4.41(${\pm}0.99$)배 증가하거나, 0.59(${\pm}0.04$)배 감소하는 것으로 나타났다. 제안된 평가 방법을 적용한 각 시간대별 평균 해상교통혼잡도는 기존의 평가 방법 결과에 비해 1.43(${\pm}0.10$)배 높게 나타났으며, 각 시간대별 최대 해상교통혼잡도는 1.62(${\pm}0.34$)배 높게 나타났다. 해상교통혼잡도 최대 평가 결과인 피크타임 해상교통혼잡도는 선박의 속력 분포로 인하여 기존의 평가 방법과 다르게 평가됨을 확인하였다. 결과적으로 선박의 속력은 실용교통용량 평가 시 중요 값으로 적용되기 때문에 해상교통량을 평가할 때 선박의 속력을 고려하여야 할 것으로 사료된다.

• Journal of Communications and Networks
• /
• 제12권6호
• /
• pp.624-631
• /
• 2010

Effective traffic matrix estimation is the basis of efficient traffic engineering, and therefore, quality of service provision support in IP networks. In this study, traffic matrix estimation is investigated in IP networks and an Elman neural network-based traffic matrix inference (ENNTMI) method is proposed. In ENNTMI, the conventional Elman neural network is modified to capture the spatio-temporal correlations and the time-varying property, and certain side information is introduced to help estimate traffic matrix in a network accurately. The regular parameter is further introduced into the optimal equation. Thus, the highly ill-posed nature of traffic matrix estimation is overcome effectively and efficiently.

• 제어로봇시스템학회논문지
• /
• 제22권2호
• /
• pp.110-116
• /
• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제5권11호
• /
• pp.1946-1958
• /
• 2011

Wireless Sensor Network (WSN) is made up of a number of sensor nodes and base stations. Traffic flow in WSN appears self-similar due to its data delivery process, and this impacts queue length greatly and makes queuing delay worse. Active queue management can be designed to improve QoS performance for WSN. In this paper, we propose self-similar traffic rate estimating algorithm named Power-Law Moving Averaging (PLMA) to regulate packet marking probability. This algorithm improves the availability of the rate estimation algorithm under the self-similar traffic condition. Then, we propose an adaptive Proportional Integral algorithm (SSPI) based on the estimation of the Self-Similar traffic rate by PLMA. Simulation results show that SSPI can achieve lower queue length jitter and smaller setting time than PI.

• ETRI Journal
• /
• 제42권3호
• /
• pp.311-323
• /
• 2020

Encrypted traffic classification plays a vital role in cybersecurity as network traffic encryption becomes prevalent. First, we briefly introduce three traffic encryption mechanisms: IPsec, SSL/TLS, and SRTP. After evaluating the performances of support vector machine, random forest, naïve Bayes, and logistic regression for traffic classification, we propose the combined approach of entropy estimation and artificial neural networks. First, network traffic is classified as encrypted or plaintext with entropy estimation. Encrypted traffic is then further classified using neural networks. We propose using traffic packet's sizes, packet's inter-arrival time, and direction as the neural network's input. Our combined approach was evaluated with the dataset obtained from the Canadian Institute for Cybersecurity. Results show an improved precision (from 1 to 7 percentage points), and some application classification metrics improved nearly by 30 percentage points.

• 한국항만경제학회:학술대회논문집
• /
• 한국항만경제학회 2007년도 정책세미나 및 국제학술대회
• /
• pp.255-270
• /
• 2007

In North-East Asia, Port traffic in Asia-North America sea route has been rapidly increasing due to economic growth in China and ASEAN. Furthermore, the major shipping companies directly call at northern chinese ports like Qingdao, Dalian and Tianjin without passing through Korean ports on Asia-North America sea route. To acquire a port traffic and develop a hub port, governments in North-East Asia have intensively invested in the development of port. Therefore, Busan new port and Gwangyang port have been developed in Korea. According to the medium-long term development planning, the port should give a enormous budget investment for the port facilities construction. So the inaccurate estimation may lead to the unreasonable port development policy. Firstly, based on the estimation of Chiang Bong-Gyu & Yang Hang Jin(2005), this study gave a comparison with the estimation of Ministry of Maritime Affairs and Fisheries(2001) and OSC/Glori(2005). Secondly, taking into account the influence factors for port traffic, this study made an estimation of port traffic for Busan new port. On the basis of this estimation, this study is compared with the estimation of Ministry of Maritime Affairs and Fisheries(2001) and OSC/Glori(2005). In conclusion, in case of the development of Busan new port, based on the estimation of Ministry of Maritime Affairs and Fisheries(2001), this study should the high possibility that the Busan new port will be serious lack of the port facilities in the year of 2011. And according to the OSC/Glori(2005)'s estimation result, there is a lack of the port facilities, though we have modified the port investment plan.

• 대한교통학회지
• /
• 제19권1호
• /
• pp.77-88
• /
• 2001

현재까지의 관측교통량기반 수요추정법은 단일차종(singleclass)기반 연구가 대부분을 차지하고 있다. 그러나 현실 교통망에서는 여러 차종이 혼재되어 교통수요나 흐름을 만든다. 즉, 기존의 관측교통량기반 수요추정법은 PCE(Passenger Car Equivalent) 환산을 통한 여러 개의 차종O/D 및 관측교통량을 승용차 단위로 전환하여 하나의 O/D 및 관측교통량으로 만들어 O/D를 추정하고, 최초의 PCE환산이전 차종별 O/D의 고정비율과 관측교통량 고정비율로 곱해 차종별 O/D 및 관측교통량으로 나누어 분석하는 것이 일반적인 방법이었다. 즉, 다차종기반분석법은 각각의 차종별 O/D에 대한 노선선택비율을 각각 계산하고, 그에 따른 목적함수 감소방향인 gradient를 또한 각각 계산하여 차종별 추정력을 극대화하는 것이 그 장점이라고 할 수 있다. 따라서, 본 연구에서는 단일차종기반추정법을 다차종기반추정법으로 확장하여 차종간 혼잡을 고려한 보다 현실적인 수요추정기법을 마련하는 것이 본 연구의 목적이라고 하겠다.

• Journal of Power Electronics
• /
• 제14권5호
• /
• pp.1038-1046
• /
• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• 한국통신학회논문지
• /
• 제23권9A호
• /
• pp.2184-2196
• /
• 1998

Admission control is one of the most important congestion control mechanism to be executed at the call set up phase by regulating traffic into a network in a preventive way. An efficient QOS evaluation or bandwidth estimation method is required for call admission to be decided in real time. In this paper, we spropose a computtionally simple approximation method of estimating cell loss probability and mean cell delay for admission control of both delay sensitive and loss sensitive calls. Mixed input queueing system, where a new call combines with the existing traffic, is used as a queueing model for QOS estimation. Also traffic parameters are suggested to characterize both a new call and existing traffic. Aggregate traffic is approximated by a renewal process with these traffic parameters and then mean delay and cell loss probability are detemined using appropriate approximation formulas. The accuracy of this approximation approach is examined by comparing their results with exact analysis or simulation results of vrious mixed unput queueing systems. Based on this QOS estimation method, call admission control scheme which is traffic independent and computable in yeal time are proposed.

• 한국철도학회논문집
• /
• 제14권1호
• /
• pp.57-65
• /
• 2011

교량을 주행하는 열차의 주행안전성과 승차감의 확보를 위해 Eurocode, 신간선 기준, 호남고속철도 설계지침 등에서는 교량의 연직변위, 연직가속도, 면틀림 등의 항목으로 제한하고 있다. 그러나 이와 같은 제한 기준은 교량 설계자의 편의를 위한 간접적인 방법이다. 또한 이와 같은 기준은 일반적인 경간(Eurocode의 경우 120m 이하)에 대한 제한 기준으로서, 이 이상의 장경간 교량의 경우에는 교량/열차 상호작용 해석 등에 의한 면밀한 검토를 제안하고 있다. 본 연구에서는 교량/열차 상호작용 해석을 수행하여 열차에서의 응답을 통해 교량 상을 주행하는 열차의 주행안전성 및 승차감을 직접적으로 평가하고자 하였다. 즉, 중앙경간 300m의 현수교를 주행하는 KTX 열차에 대하여 열차 내부의 가속도와 윤중감소율을 구해 평가하는 방법을 취하였다. 또한, 이동 열차하중과 지진하중이 동시에 작용할 경우를 고려한 교량/열차/지진 상호작용해석을 수행하여 지진 시의 응답을 평가하였다.