• Title/Summary/Keyword: Demand forecasting

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A Study on the Market Analysis & Demand Forecasting of $CO_2$ Reduction and Sequestration Technologies (온실가스 저감 및 처리기술의 시장 분석 및 수요예측 연구)

  • Lee Deok-Ki;Choi Sang-Jin;Park Soo-Uk
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2005.05a
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    • pp.217-233
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    • 2005
  • As the Kyoto Protocol will come into effect starting February 2005, 55 member countries of the Conference of Parties of the Framework Convention on Climate Change (FCCC) will be under obligation to reduce the emissions of Carbon Dioxide $(CO_2)$ by 5.2 Percent from the 1990 levels before the year 2012. Hence the development of technology to prepare for this has been accelerated in Korea. The effect of technology varies with market size of technology, and it is necessary to control technology development period, according to the size and trend of technology market. Moreover it is essential that market analysis be finished before technology development, because market on the $(CO_2)$ Reduction and Sequestration Technology expands internationally. For that reason, it is needed to analyze domestic market and to consider technology development strategy according to analysis results. In this paper, we analyzed the domestic industry and forecasted the market size, both related to the Reduction and Sequestration Technology on $(CO_2)$ emission, which is the major component of global Green House Gas(GHG).

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Analysis of Productivity by Environmental Factors in Regional Base Public Hospitals (지역거점 공공병원의 환경적 요인에 따른 생산성 분석)

  • Lee, Jinwoo
    • Korea Journal of Hospital Management
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    • v.22 no.3
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    • pp.46-60
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    • 2017
  • The purpose of this study is to analyze the difference of productivity according to environmental factors among 25 Regional base public hospitals. Also this study is to propose a method to improve the productivity of Regional base public hospitals in the future by improving the public performance and stable management performance by studying the productivity variables affecting profitability. The survey period was based on the last three years, and 25 Regional base public hospitals were selected for the survey. The dependent variable is the total capital medical marginal profitability and the medical profit marginal profitability which are the indicators of profitability. The independent variable, productivity, is classified into three indicators: capital productivity, labor productivity, and value added productivity. The ANOVA analysis method was used to analyze the productivity difference according to the frequency factor and the environmental factors of the Regional base public hospitals. Finally, we conducted a hierarchical regression analysis to examine the productivity variables affecting profitability. The results of this study showed that there were differences in productivity due to environmental factors such as hospital size, competition in the local medical market, and differences in management performance. The difference in productivity and profitability depending on the environmental factors suggests that it is difficult for Regional base public hospitals in each regional base to perform a balanced public service. In order to overcome this, it is necessary to provide balanced medical services such as government financial support expansion, regional medical demand forecasting and facility infrastructure construction.

Development of Daily Operation Program of Battery Energy Storage System for Peak Shaving of High-Speed Railway Substations (고속철도 변전소 피크부하 저감용 ESS 일간 운전 프로그램 개발)

  • Byeon, Gilsung;Kim, Jong-Yul;Kim, Seul-Ki;Cho, Kyeong-Hee;Lee, Byung-Gon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.3
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    • pp.404-410
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    • 2016
  • This paper proposed a program of an energy storage system(ESS) for peak shaving of high-speed railway substations The peak shaving saves cost of equipment and demand cost of the substation. To reduce the peak load, it is very important to know when the peak load appears. The past data based load profile forecasting method is easy and applicable to customers which have relatively fixed load profiles. And an optimal scheduling method of the ESS is helpful in reducing the electricity tariff and shaving the peak load efficiently. Based on these techniques, MS. NET based peak shaving program is developed. In case study, a specific daily load profile of the local substation was applied and simulated to verify performance of the proposed program.

Design of Capable to Promise Using Lifetime Value (고객생애가치를 이용한 납기확약 모델 구현에 관한 연구)

  • 박재현;양광모;강경식
    • Journal of the Korea Safety Management & Science
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    • v.4 no.2
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    • pp.71-81
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    • 2002
  • Today's environment of enterprise is changing. They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In the Supply chain, The ATP function doesn't only give customers to conformation of delivery. It can be used by the core function with ATP rule that can reconcile supplies and demands on the supply chain. Therefore We can be acquire the conformation about on the due date of supplier by using the ATP function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the ATP. In this paper, It consolidates the necessity on a CTP and analyzes data which is concerned of ATP. Under the these environments, defines the ATP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm.

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.