• Title/Summary/Keyword: Demand forecasting

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The Preliminary Analysis of Introducing 500 km/h High-Speed Rail in Korea

  • Lee, Kwang-Sub;Eom, Jin Ki;Lee, Jun;Moon, Dae Seop
    • International Journal of Railway
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    • v.6 no.1
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    • pp.26-31
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    • 2013
  • Following the success of the KTX (Korea's first high-speed rail system) with a maximum operating speed of 300 km/h opened in 2004, experts in Korea started a research on the development of key technologies for high-speed rail (HSR) with a top speed of 500 km/h. This paper is a preliminary analysis of the research. It first reviews HSR experiences around the world, in terms of traffic and economic impacts of HSR, and presents a preliminary analysis of 500 km/h HSR in Korea. It is estimated that introduction of 500 km/h HSR with a 54% of travel time reduction will increase HSR passengers to about 9.8 million (about 78% of market share) between Seoul and Busan. It is a 23% of growth compared to the base scenario. Along with conventional rail passengers, air passengers are expected to be significantly impacted by the 500 km/h HSR. As a function of HSR travel time, the estimated market shares of both KTX and 500 km/h HSR compared to air are very comparable with previous international experiences. Based on the forecasted traffic, estimated total benefits are $758 million per year.

The Market result and forecast of Commercial Aircraft industry (세계 상용 항공기 시장 성과와 전망)

  • Chang, Tae-Jin
    • Current Industrial and Technological Trends in Aerospace
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    • v.9 no.1
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    • pp.15-26
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    • 2011
  • The airliners are replacing their old fleet by brand new ones while the air traffic has recovered from the great recession. And the delivery and the backlog get almost highest record still in 2010. The single aisle leads the market and it will show harder competition with more efficient challengers. The recent strong demand of new aircraft reduces MRO and lease market and it makes some worries about the bubble in civil aircraft industry. In the long time forecast, the civil aircraft industry will grow steadily with over 60,000 delivery for 20 years. and the commercial aircraft market will be about 31,000~34,000 of them. And the emerging market will lead the growth.

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A development of water demand forecasting model using multiscale analysis and SVM based nonlinear prediction model (다중스케일 분석과 SVM 비선형 예측 모형을 활용한 상수도 수요량 예측기법 개발)

  • Kwon, Hyun-Han;Kim, Min-Ji;Lee, Bong-Kuk;Koo, Ja-Yong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.367-367
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    • 2012
  • 기후변화로 인해 기온, 강수량, 습도 등의 기후를 예측하고 변화하는 환경에 적응해가며 생활하고 있다. 또한 여러 가지 외부적인 요인들의 영향을 받아 상수도 시설에서의 에너지 사용량도 영향을 많이 받는다. 하지만 이러한 상수도 시설의 사용량 변화로 인해 상수도 수요량의 변화량을 예측하는데 있어서 국내 연구 및 방법이 많이 부족한 상황이다. 이에 본 연구에서는 다중스케일을 기반으로 하는 비선형 예측 모형을 개발하고자 한다. 다중스케일 분석에서도 가장 우수한 분해 능력을 가지는 Wavelet Transform을 적용하여 시계열을 분해한 후 패턴인식 기반의 비선형 예측모형인 Support Vector Machine(SVM)을 적용하였다. 상수도 수요량의 예측 과정은 다음과 같다. 첫째, 상수도 수요량 자료를 Wavelet Transform 기법을 통하여 단순화 시킨다. 둘째, Global Wavelet Spectrum을 통하여 통계적으로 의미 있는 성분만을 추출하고 이를 해석 대상으로 한다. 셋째, 특정 주기를 갖는 유의한 독립성분들에 대해서 최적 지체시간을 결정한 후 SVM모형을 통해 예측 모형을 구축한다. 넷째, 나머지 성분에 대해서도 SVM 모형을 적용하여 예측을 실시한 후 앞서 예측된 성분과 모두 결합하여 최종적으로 예측시계열을 구성한다.

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Predicting the Number of People for Meals of an Institutional Foodservice by Applying Machine Learning Methods: S City Hall Case (기계학습방법을 활용한 대형 집단급식소의 식수 예측: S시청 구내직원식당의 실데이터를 기반으로)

  • Jeon, Jongshik;Park, Eunju;Kwon, Ohbyung
    • Journal of the Korean Dietetic Association
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    • v.25 no.1
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    • pp.44-58
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    • 2019
  • Predicting the number of meals in a foodservice organization is an important decision-making process that is essential for successful food production, such as reducing the amount of residue, preventing menu quality deterioration, and preventing rising costs. Compared to other demand forecasts, the menu of dietary personnel includes diverse menus, and various dietary supplements include a range of side dishes. In addition to the menus, diverse subjects for prediction are very difficult problems. Therefore, the purpose of this study was to establish a method for predicting the number of meals including predictive modeling and considering various factors in addition to menus which are actually used in the field. For this purpose, 63 variables in eight categories such as the daily available number of people for the meals, the number of people in the time series, daily menu details, weekdays or seasons, days before or after holidays, weather and temperature, holidays or year-end, and events were identified as decision variables. An ensemble model using six prediction models was then constructed to predict the number of meals. As a result, the prediction error rate was reduced from 10%~11% to approximately 6~7%, which was expected to reduce the residual amount by approximately 40%.

Economic Ripple Effect of the TKR on the Logistics Industry

  • KIM, Sun-Ju
    • Journal of Distribution Science
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    • v.19 no.3
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    • pp.25-34
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    • 2021
  • Purpose: The purpose of this study is to analyze the economic ripple effect(ERE) of logistics industry by construction of Trans-Korea Railway (TKR) and present policy measures to minimize the economic loss of South Korea (SK). Research design, data and methodology: As the analysis method, exponential smoothing was used for demand forecasting, Input-Output analysis was used to estimate the economic ripple effect coefficient, and scenario analysis was used to an efficient way to invest in TKR to minimize SK's economic losses. Results: 1) the production(logistics fares) of TKR for 10 years after its completion is about 11.42 trillion won in positive relations, and 26.89 billion won in negative relations. 2) the ERE of SK in positive relations is 24.32 trillion won in production inducement effect, 8.1 trillion won in value-added inducement effect, 3.54 trillion won in import inducement effect, and 70,930 persons in employment inducement effect. But the ERE was insufficient in the negative relations. 3) SK's efficient investment method is providing materials and equipment by SK and building the TKR by North Korea in positive inter-Korea relations. Conclusions: For the successful operation of TKR, international cooperation, legalization and stable peace settlement on the Korean Peninsula are required.

Factors Affecting Income from Public Agricultural Land Use: An Empirical Study from Vietnam

  • PHAM, Phuong Nam;TRAN, Thai Yen
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.6
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    • pp.1-9
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    • 2022
  • The study aims to determine the factors and their influence on the income from using public agricultural land of households. Public agricultural land is agricultural land, including land for growing annual crops, perennial crops, and land for aquaculture, leased by commune-level People's Committees with a lease term of not more than 5 years. Secondary data were collected for the 2017-2021 period at state agencies. Primary data were collected from a survey of 150 households renting public agricultural land. The regression model assumed that there were 28 factors belonging to 7 groups. The test results show that 25 factors affect income, and 03 factors do not. The group of COVID-19 pandemic factors has the strongest impact, followed by the groups of agricultural product market factors, land factors, capital factors, production cost factors, labor factors, and climatic factors. The impact rate of COVID-19 pandemic factors is the largest (23.00%); The impact rate of climatic factors is the smallest (6.04%). Proposals to increase income include good implementation of disease prevention and control; increasing the land lease term; accurately forecasting the supply and demand of the agricultural market; raising the level of the household head; ensuring sufficient production capital, and adapting to the climate.

Effects of Macroeconomic Conditions and External Shocks for Port Business: Forecasting Cargo Throughput of Busan Port Using ARIMA and VEC Models

  • Nam, Hyung-Sik;D'agostini, Enrico;Kang, Dal-Won
    • Journal of Navigation and Port Research
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    • v.46 no.5
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    • pp.449-457
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    • 2022
  • The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

Web-system development for the feasibility of national road

  • Park, T.;Shin, E.;Kang, T.;Park, W.;Lee, Y.
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.698-699
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    • 2015
  • For last three years, our research team have conducted the project named "Development of construction project management technology based on BIM/GIS platform. "We developed construction cost estimation system as well as 3D modeling engine at the first two year and established a web-system which could estimate the benefits of the project and further analyze the economic and financial feasibility of the project. This paper mainly focused on the functions and specifications of web-system. The system was composed of two modules: economic feasibility estimation module and financial feasibility estimation module. While the economic feasibility estimation module determines economic feasibility of the project based on traffic demand forecasting from the public's perspective, the financial feasibility estimation module determine financial viability of the project using toll fee of the road from private entity's perspective. Compared with traditional feasibility study, the proposed system provide users with better flexibility which can make users easily to validate the project upon the change of project environments. The system was also verified with an already accomplished project. The verification showed that proposed system could provide satisfactory accurate results with reduced time and resources.

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Energy Forecasting Information System of Optimal Electricity Generation using Fuzzy-based RERNN with GPC

  • Elumalaivasan Poongavanam;Padmanathan Kasinathan;Karunanithi Kandasamy;S. P. Raja
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2701-2717
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    • 2023
  • In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

Does Urbanization Affect Bilateral Trade? (양국의 도시화가 무역에 미치는 영향: 중력 모형의 활용)

  • EunJung Lim;Sunghee Jun
    • Korea Trade Review
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    • v.45 no.3
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    • pp.119-132
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    • 2020
  • In this paper we explore the two analyses to know the urbanization effect on trade. First, the granger causality test to examine the relationship between trade and urbanization. The Granger causality test is a statistical hypothesis test for determining whether one time series is useful for forecasting another. The results indicated that the existence of a bidirectional causality running from trade to urbanization when six lags were applied. When eight lags were applied, we found unidirectional causality running from urbanization to trade. Second, gravity models were used to investigate the urbanization effect on trade. The production cost and specification are affected by the economies of scale, and the economies of scale increased as the greater geographically agglomeration. However, the gravity model to explain the bilateral trade flows ignores the urbanization variables. Therefore we added the urbanization variable represented as the geographically agglomeration into gravity model. The results show that the degree of urbanization of both countries has statistically positive effect on trade (export and import) and the bigger coefficients of trade partner's urbanization. The reason is that the trade share of industrial supplies, intermediate goods and capital goods is much higher than finished consumer goods. The urbanization is more important the improved the efficiency of production than demand market.