• 한국도로학회논문집
• /
• 제15권3호
• /
• pp.93-101
• /
• 2013

PURPOSES : This study is to investigate the relationship of socioeconomic characteristics and road network structure with traffic growth patterns. The findings is to be used to tweak traffic forecast provided by traditional four step process using relevant socioeconomic and road network data. METHODS: Comprehensive statistical analysis is used to identify key explanatory variables using historical observations on traffic forecast, actual traffic counts and surrounding environments. Based on statistical results, a multiple regression model is developed to predict the effects of socioeconomic and road network attributes on traffic growth patterns. The validation of the proposed model is also performed using a different set of historical data. RESULTS : The statistical analysis results indicate that several socioeconomic characteristics and road network structure cleary affect the tendency of over- and under-estimation of road traffics. Among them, land use is a key factor which is revealed by a factor that traffic forecast for urban road tends to be under-estimated while rural road traffic prediction is generally over-estimated. The model application suggests that tweaking the traffic forecast using the proposed model can reduce the discrepancies between the predicted and actual traffic counts from 30.4% to 21.9%. CONCLUSIONS : Prediction of road traffic growth patterns based on surrounding socioeconomic and road network attributes can help develop the optimal strategy of road construction plan by enhancing reliability of traffic forecast as well as tendency of traffic growth.

• 한국경영과학회지
• /
• 제38권3호
• /
• pp.71-86
• /
• 2013

This research explores the question how interactions between customer and firm affect firm growth. To test suggested hypotheses, this study collects data on social commerce industry in Korea during the period from the beginning of social commerce industry in Korea, May 2010, to March 2012, and investigates the effect of social media on the growth of social commerce firms. We suggest two hypotheses in this study. First, as web traffic inflow through social media into a focal social commerce increases, the growth rate of the focal social commerce increases. Second, the more diverse social media channel through which web traffic inflows into a focal social commerce, the weaker the positive effect of web traffic inflow on the growth rate of the focal social commerce. Analysis of data shows that inflow through social media is positively related to the growth of social commerce. In addition, our analysis shows that inflow channel diversity weakens the positive relationship between web traffic inflow through social media and growth rate of social commerce firms. These results suggest that firms need to concentrate on few social media in order to attract customers. The study contributes to understanding how interaction between firms and customers influences the growth of the firm.

• 스마트미디어저널
• /
• 제5권4호
• /
• pp.75-82
• /
• 2016

우리나라의 경제 성장과 도로 환경의 변화를 통해 국내 자동차 시장이 성장하였으나, 이로 인해 교통사고율 또한 증가하였고, 인명 피해가 심각한 수준이다. 이에 따라, 정부에서는 교통사고 데이터를 개방하고 문제를 해결하기 위한 정책을 수립 및 추진 중이다. 본 논문에서는 교통사고 데이터를 이용하여 클래스의 불균형을 해소하고, Hybrid Model 구축을 통한 교통사고 예측을 위해 원본 교통사고 데이터와 Sampling을 수행한 데이터를 학습 데이터로 사용한다. 두 학습데이터에 연관규칙 학습기법인 FP-Growth 알고리즘을 이용하여 교통사고 상해 심각도와 연관된 패턴을 학습한다. 두 학습 데이터의 연관 패턴을 분석을 통해 같은 연관된 패턴을 추출하고 의사결정트리와 다항 로지스틱 회귀분석기법에 연관된 속성에 가중치를 부여하여 융합형 Hybrid Model을 구축하고 교통사고 피해자 상해 심각도를 예측하는 방법에 대해 제안한다.

• 원예과학기술지
• /
• 제33권3호
• /
• pp.340-348
• /
• 2015

Mowing turfgrasses, especially fast growing species like perennial ryegrass, is one of the most time and money consuming tasks of their management. Trinexapac-ethyl (TE) is a popular plant growth regulator used to reduce mowing requirements, improve stress tolerance, and enhance turf quality. This study was conducted to investigate the effect of TE rate and frequency of applications on growth response and traffic tolerance of perennial ryegrass. The experiment was a split-plot laid out in a randomized complete block (RCB) design with three replications. TE was applied to main plots at 0.00, 0.25, and $0.50kg\;a.i.\;ha^{-1}$. Application pattern included an initial application, followed by two sequential applications at 6-wk intervals. Traffic treatment was applied to subplots with a cleated roller. Results demonstrated that TE consistently reduced vertical shoot growth, clippings dry weight, with maximum growth reduction of 59% and 65%, for 0.25 and $0.50kg\;a.i.\;ha^{-1}$, respectively, occurring at 2 weeks after initial TE treatment (WAT). Traffic also dramatically reduced vertical shoot growth and clippings dry weight. Overall, quality of perennial ryegrass was enhanced by sequential TE applications, however, turf quality and surface coverage reduced greatly under traffic, regardless of TE treatment. Total chlorophyll, chlorophyll a and chlorophyll b and total carbohydrates (TC) contents were also positively influenced following sequential TE application. Our results indicated that TE reduces mowing frequency and enhances turf quality rather than influencing traffic resistance.

• 대한안전경영과학회지
• /
• 제13권1호
• /
• pp.127-131
• /
• 2011

Even if there are no causing factors such as car crash and road works, traffic congestion come from traffic growth on the road. In this case, estimation of traffic flow helps find the solution of traffic congestion problem. In this paper, we present a optimization model which used on traffic equilibrium problem and studied the problem of inverting shortest path sets for complex traffic system. And we also develop pivotal decomposition algorithm for reliability function of complex traffic system. Several examples are illustrated.

• Structural Engineering and Mechanics
• /
• 제85권4호
• /
• pp.531-543
• /
• 2023

The existing concrete bridges are time-varying working systems, where the maintenance strategy should be planned according to the time-varying performance of the bridge. This work proposes a time-dependent residual capacity assessment procedure, which considers the non-stationary bridge load effects under growing traffic and non-stationary structural deterioration owing to material degradations. Lifetime bridge load effects under traffic growth are predicated by the non-stationary peaks-over-threshold (POT) method using time-dependent generalized Pareto distribution (GPD) models. The non-stationary structural resistance owing to material degradation is modeled by incorporating the Gamma deterioration process and field inspection data. A three-span continuous box-girder bridge is illustrated as an example to demonstrate the application of the proposed procedure, and the time-varying reliability indexes of the bridge girder are calculated. The accuracy of the proposed non-stationary POT method is verified through numerical examples, where the shape parameter of the time-varying GPD model is constant but the threshold and scale parameters are polynomial functions increasing with time. The case study illustrates that the residual flexural capacities show a degradation trend from a slow decrease to an accelerated decrease under traffic growth and material degradation. The reliability index for the mid-span cross-section reduces from 4.91 to 4.55 after being in service for 100 years, and the value is from 4.96 to 4.75 for the mid-support cross-section. The studied bridge shows no safety risk under traffic growth and structural deterioration owing to its high design safety reserve. However, applying the proposed numerical approach to analyze the degradation of residual bearing capacity for bridge structures with low safety reserves is of great significance for management and maintenance.

• 산업공학
• /
• 제12권4호
• /
• pp.625-634
• /
• 1999

On this study we selected some variable which affect on the estimated of the voice traffic, and estimated daily average traffic by years according to the variables. We applied nonlinear growth curve model to future traffic forecast with estimated historical traffic data. As a result of the forecasting, this study investigates the year in which the internet traffic goes far than the voice traffic.

• 한국산학기술학회논문지
• /
• 제20권12호
• /
• pp.254-264
• /
• 2019

본 연구는 교통사고 환자의 외상후 스트레스 장애 위험정도, 회복탄력성 및 사회적 관계망이 외상후 성장에 미치는 영향을 알아보기 위해 시도된 서술적 상관관계 연구이다. 연구대상자는 K도 C시 소재 100병상 이상 5개 병원의 교통사고 환자 158명이었으며, 2018년 7월 1일부터 8월 31일까지 구조화된 설문지를 이용하여 자료를 수집하였다. 수집된 자료는 t-test, ANOVA, Pearson's correlation coefficients, Multiple Regression으로 분석하였다. 외상후 성장에 미치는 영향요인을 파악한 결과, 연구의 설명력은 36.9%로 나타났으며, 대상자의 외상후 성장에 미치는 영향요인은 사회적 관계망, 외상후 스트레스 장애 위험정도 순으로 나타났다. 또한 사회적 관계망은 회복탄력성과 외상후 성장의 관계를 완전매개하였다. 이를 토대로, 교통사고 환자의 사회적 관계망이 크고 외상후 스트레스 장애 위험정도가 클수록 외상 후 성장이 높아짐을 확인하였고, 사회적 관계망은 회복탄력성과 외상후 성장의 관계를 완전매개한다는 것을 확인하였다. 따라서 교통사고 환자의 외상후 성장을 돕기 위해 사회적 관계망과 회복탄력성 향상 방안에 대해 모색할 필요가 있고, 교통사고 환자에 대한 반복적이고 장기적인 관찰을 통해 외상후 성장에 대한 추가연구가 필요할 것으로 사료된다.

• ETRI Journal
• /
• 제32권1호
• /
• pp.22-32
• /
• 2010

The pervasive game environments have activated explosive growth of the Internet over recent decades. Thus, understanding Internet traffic characteristics and precise classification have become important issues in network management, resource provisioning, and game application development. Naturally, much attention has been given to analyzing and modeling game traffic. Little research, however, has been undertaken on the classification of game traffic. In this paper, we perform an interpretive traffic analysis of popular game applications at the transport layer and propose a new classification method based on a simple decision tree, called an alternative decision tree (ADT), which utilizes the statistical traffic characteristics of game applications. Experimental results show that ADT precisely classifies game traffic from other application traffic types with limited traffic features and a small number of packets, while maintaining low complexity by utilizing a simple decision tree.

• Journal of Communications and Networks
• /
• 제13권6호
• /
• pp.621-624
• /
• 2011

With the rapid growth of internet traffic, accurate and reliable prediction of internet traffic has been a key issue in network management and planning. This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) error model for forecasting internet traffic and evaluates its performance by comparing it with seasonal autoregressive integrated moving average (ARIMA) models in terms of root mean square error (RMSE) criterion. The results indicated that the seasonal AR-GARCH models outperformed the seasonal ARIMA models in terms of forecasting accuracy with respect to the RMSE criterion.