• Title/Summary/Keyword: freight data

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A Study on Estimating of Air Freight Demand using Regression Model (회귀모형을 이용한 군 항공화물수요 예측에 관한 연구)

  • Seo, Se-Kyung;Jung, Byung-Ho;Kim, Ik-Ki
    • Journal of the military operations research society of Korea
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    • v.35 no.3
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    • pp.1-15
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    • 2009
  • Central supply depot of Air Force has been receiving and storing the goods from the inside and outside of the country. And it also has been distributing the goods to the air base by air, rail, road, etc. These goods have been called central goods. Among these central goods, 10% of them are transported by air and the amount of freight is increasing day by day. So, air transportation in the Air Force has been more important than ever. But, studies of demand estimation for activating air transportation are very difficient. This study verified the main factors affecting to air transportation and the function of regression model will be useful data for estimating air freight demand.

A Study on International Passenger and Freight Forecasting Using the Seasonal Multivariate Time Series Models (계절형 다변량 시계열 모형을 이용한 국제항공 여객 및 화물 수요예측에 관한 연구)

  • Yoon, Ji-Seong;Huh, Nam-Kyun;Kim, Sahm-Yong;Hur, Hee-Young
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.473-481
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    • 2010
  • Forecasting for air demand such as international passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison of the performances of the multivariate time series models. In this paper, we used real data such as exchange rates, oil prices and export amounts to predict the future demand on international passenger and freight.

A Study on the Analysis of Dangerous Driving Behavior and Traffic Accident Risk according to the Operation Characteristics of Commercial Freight Vehicles (사업용 화물자동차 운행특성에 따른 위험운전행동 및 교통사고 위험도 분석 연구)

  • Park, Jin soo;Lee, Soo beom;Park, Jun tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.152-166
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    • 2022
  • This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

Value of Freight Travel-Time Savings for Road Investment Evaluation (도로사업의 투자분석을 위한 화물운송시간가치 산정)

  • 최창호
    • Journal of Korean Society of Transportation
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    • v.20 no.3
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    • pp.41-52
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    • 2002
  • Most investment evaluations and economic assessments of road transport proposals in Korea omit a valuation of the time spent in transit for loads of freight. These days there were few attempts to estimate value of freight travel-time savings in Korea, but most of them included rail or marine with statewide area so that couldn't obtain unique travel-time savings for road freight transport. This study applied revealed Preference method and associated binominal logit models to estimate the value of travel-time savings in transit from an statewide survey of road freight transport in 1997. Data sets were segmented according to transport areas and business types. The results of this study showed that the value of freight travel-time savings varied wide ranges from 53,449 won per hour in urban transport to 29,397 won per hour in regional transport, that the use of statewide value of freight travel-time savings can drives wrong results into economic assessment, and that the use of adequate value of freight travel-time savings according to assessment area is very important.

Estimation Model for Freight of Container Ships using Deep Learning Method (딥러닝 기법을 활용한 컨테이너선 운임 예측 모델)

  • Kim, Donggyun;Choi, Jung-Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.5
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    • pp.574-583
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    • 2021
  • Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

A Study on the Analysis of Management Characteristics of Coastal Port Freight Transportation Business Using Panel Regression Analysis (패널회귀분석을 이용한 내항 화물운송사업체의 경영특성 분석에 관한 연구)

  • Kim, Suk;Park, Sung-Hoon;Yang, Tae-Hyeon;Yeo, Gi-Tae
    • Journal of Digital Convergence
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    • v.17 no.3
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    • pp.79-92
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    • 2019
  • This study analyzes the effects of freight transportation income, capital, asset, non-operating expenses, and debt ratio on the debts of inner port freight transportation businesses through the GLS of panel regression analysis and the estimation of fixed effects model. The factors and hypotheses were established through a theoretical background review, and the financial statement and profit and loss data of inner port freight transportation businesses for 10 years from 2006 to 2015 were analyzed. The results showed that assets had positive effects on debts, and negative effects on capital, non-operating expenses, and debt ratio, but no effect on freight transportation income. This result empirically demonstrates the tendency of inner port freight transportation businesses to secure assets by increasing debts, creation of debt reduction leverage effect using non-operating expenses such as interest expenses through bank borrowing, and the adoption of management characteristics and financial operation method to lower the debt ratio by reducing capital more than debts. In future studies, it is necessary to analyze coastal port freight transportation business by industry (oil tankers, cargo ships, and barge ships), and regions such as East, West and South sea.

Analysis of the Factors Influencing the Ocean Freight Rate (해상운임에 영향을 미치는 주요 요인에 관한 연구)

  • Kim, Myoung-Hee
    • Journal of Navigation and Port Research
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    • v.46 no.4
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    • pp.385-391
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    • 2022
  • In this study, a multivariate time series analysis was conducted to identify various variables that impact ocean freight rates in addition to supply and demand factors. First, we used the ClarkSea Index, Clarksons Average Bulker Earnings, and Clarksons Average Tanker Earnings provided by the Shipping Intelligence as substitute variables for the dependent variable, ocean freight. The following ndependent variables were selected: World Seaborne Trade, World Fleet, Brent Crude Oil Price, World GDP Growth Rate, Industrial Production (IP OECD) Growth Rate, Interest Rate (US$ LIBOR 6 Months), and Inflation (CP I OECD) through previous studies. The time series data comprise annual data (1992-2020), and a regression analysis was conducted. Results of the regression analysis show that the World Seaborne Trade and Brent Crude Oil P rice impacted the ClarkSea Index. Only the World Seaborne Dry Bulk Trade impacted the Clarksons Average Bulker Earnings, World Seaborne Oil Trade, Brent Crude Oil Price, IP, and CP I on the Clarksons Average Tanker Earnings.

Inherent Random Heterogeneity Logit Model for Stated Preference Freight Mode Choice (SP 화물수단선택을 위한 Inherent Random Heterogeneity 로짓 모형 연구)

  • KIM, Kang-Soo
    • Journal of Korean Society of Transportation
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    • v.20 no.3
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    • pp.83-92
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    • 2002
  • Freight mode choice models are essential to the analysis of many areas of transport research. However, observations of actual market choices have only been made in a limited number of situations. Therefore, stated preference(SP) techniques have emerged as an alternative source of actual market choices to be used for estimating freight mode choice models. Considerable confidence exists about SP data, but little consideration has been given to the potential for estimation bias. This paper has been motivated by the theoretical side of estimating SP discrete choice models, focusing on a case study of freight mode choice. Recently developed simulation methods are used to construct inherent random heterogeneity legit models, which consider individual heterogeneity, its inheritance to the next choices and overcome the independence from irrelevant alternatives (IIA) property. This Paper contributes to the development of models dealing with heterogeneity and its inheritance, and sheds light on the heterogeneity of freight transport.

A Study on the Forecasting of Container Freight Volume for Donghae Port and Sokcho Port (동해항 및 속초항의 컨테이너물동량 예측에 관한 연구)

  • Jo, Jin-Haeng;Kim, Jae-Jin
    • Journal of Korea Port Economic Association
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    • v.26 no.1
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    • pp.83-104
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    • 2010
  • The purpose of this paper is to prepare container port policy and to contribute to the regional economy by forecasting of the container freight volume for the Donghae Port and Sokcho Port. As a methodology a survey and O/D technique were adopted. O/D technique was applied to the container freight data of Korea Maritime Institute. The main results of this paper are as follows: First, it is adviserable that Gangwondo Province should adopt incentive program of 100,000 won Per TEU rather than 50,000 won per TEU. Secondly, container freight volume for Donghae Port and Sokcho Port is forecast to be 22,388 TEU in 2010, 152,367 TEU in 2015 and 354,217 TEU from 6,653 TEU in 2008. Thirdly, joint port marketing is required for the Donghae Port and Sokcho Port in terms of same region in one hour drive.

A Study on the Small-medium Sized Freight Forwarders' Entry into UNPM -Subject to International Freight Forwarder & Delivery Service (중소 국제물류주선업체의 유엔 조달시장 물류서비스 부분 진출방안 연구)

  • Shin, Seok-Hyun;Kwak, Kyu-Seok
    • Journal of Navigation and Port Research
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    • v.36 no.8
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    • pp.691-698
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    • 2012
  • Local freight forwarder's circle is suffering worsening profitability and insecure employment from over-competition which caused by a saturated local logistics market. It is emerging UN procurement market for local freight forwarders. However it is needed to study on successful entry, market status and supporting measures from government and research institute. Currently there are no national research data of UN procurement market in logistics sectors but as per the writer's experience and viewpoint to UN bidding, it would seem that appropriate measures should be made such as government's enhanced support for overseas advancement, price competitiveness, building global network and development of education program for trainees associated with current overseas internship program by government.