• 제목/요약/키워드: Demand Variable

검색결과 569건 처리시간 0.023초

가변 비트율 주문형 비디오 서버에서 선반입자 캐슁을 이용한 버퍼 관리 기법 (A Buffer Management Scheme Using Prefetching and Caching for Variable Bit Rate Video-On-Demand Servers)

  • 김순철
    • 한국산업정보학회논문지
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    • 제4권4호
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    • pp.32-39
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    • 1999
  • 주문형 비디오 시스템에서 가변 비트율로 압축된 데이타들은 압축 대상이 되는 데이타의 내용 변화와 압축 기법의 특성으로 인해 단위 시간 당 처리해야 할 데이타 크기가 일정하지 않다. 그러나, 대부분의 주문형 비디오 서버들은 가변 비트율로 압축된 데이타를 실시간에 처리하기 위해 가변 데이타 크기의 최대값으로 시스템 자원을 예약하기 때문에 자원의 활용률이 떨어진다. 본 논문에서는 주문형 비디오 서버에서 시스템 자원의 활용률을 향상시켜 더 많은 사용자를 수용할 수 있는 버퍼 관리 기법을 제안한다. 제안된 버퍼 관리 기법은 데이타에 대한 캐슁 기법과 함께 가변 비트율로 압축된 데이타를 예약할 때 선반입 기법을 적용함으로써 비디오 데이타의 가변성을 줄이고 디스크 대역폭과 서버 버퍼에 대한 활용률을 극대화하였다. 본 논문에서 제안한 버퍼 관리 기법의 효율성은 모의 실험을 통해 확인하였다.

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건구온파를 오인한 장기최대전력수요예측에 관한 연구 (Long-Term Maximum Power Demand Forecasting in Consideration of Dry Bulb Temperature)

  • 고희석;정재길
    • 대한전기학회논문지
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    • 제34권10호
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    • pp.389-398
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    • 1985
  • Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

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Development of the Plywood Demand Prediction Model

  • Kim, Dong-Jun
    • 한국산림과학회지
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    • 제97권2호
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    • pp.140-143
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    • 2008
  • This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.

우리나라 목재수요의 장기예측에 관한 연구 (A Study on the Long-Term Forecast of Timber demand in Korea)

  • 이병일;김세빈;권용대
    • 농업과학연구
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    • 제25권1호
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    • pp.41-51
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    • 1998
  • This study not only carried out to grasp about the sununarized characteristics of the relationship between international timber market and production trend of wood products, but also focused on the analysis of korean wood demand and the long-term forecast with econometric analysis. The result of regression analysis for wood demand in Korea is that coniferous roundwood demand(CIWD) is explained by coniferous foreign roundwood price(CWRI), Gross domestic product(GDP), a dummy variable. Non-coniferous roundwood demand(NCIWD)is explained by non-coniferous roundwood price(NCWRI), coniferous roundwood price(CWRI), a dummy variable. As the result of long-term forecast by base case, the total roundwood demand was forecasted $11,107,000m^3$ in the year 2000, $11,781,000m^3$ in 2005, $12,565,000m^3$ in 2010. As the result of scenario 1, total roundwood demand was forecasted $11,027,000m^3$ in 2000, $11,435,000m^3$ in 2005, $11,952,000m^3$ in 2010. And as the result by scenario 2, total roundwood demand was forecasted $11,341,000m^3$ in 2000, $12,208,000m^3$ in 2005 $13,257,000m^3$ in 2010.

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AIDS 모형을 이용한 국내산 및 수입산 새우 수요체계 분석 (A Study on Demand System of Domestic and Imported Shrimp using AIDS model)

  • 강한애;박철형
    • 수산경영론집
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    • 제54권2호
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    • pp.31-44
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    • 2023
  • This study examines the demand system of shrimp imported from top four countries and domestically produced by using AIDS (Almost Ideal Demand System) model. Top four import countries are Vietnam, Ecuador, China, and Malaysia based on the value of imports in 2021. As results of the analysis, the demand system of shrimp turn out to be below. First, the relationship of domestic shrimp and imported shrimp (Ecuadorian and Vietnamese) is identified as complements or substitutes depending on whether the income effect is considered. This result implies that imported shrimp supplements domestic supply against excess demand while homogeneous shrimp products competes with domestic shrimp in fish market. Second, the relationship among imported shrimps turned out to be both substitutes and complements. Especially, the Vietnamese shrimp is complementary with Chinese and Malaysian shrimp, but substitutes of Ecuadorian. It is assumed that adjoining Asian countries shares similar shrimp species and processing system which differentiates from Ecuadorian. Finally, the study included quarter as dummy variable and GDP as instrumental variable of expenditure in the model. The result confirmed that domestic shrimp is highly on demand during the main production season while imported shrimp is mainly demanded during the rest of the season.

환승지체 및 가변수요를 고려한 대중교통 운행빈도 모형 개발 (Transit Frequency Optimization with Variable Demand Considering Transfer Delay)

  • 유경상;김동규;전경수
    • 대한교통학회지
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    • 제27권6호
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    • pp.147-156
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    • 2009
  • 본 논문에서는 기 운영되고 있는 도시부 대중교통을 대상으로 노선의 운행빈도 설계 문제의 모델링 및 해법 개발을 위한 방법론을 제시하였다. 개발된 운행빈도 모형은 이중구조 모형으로서 상위 운영자 모형은 이용 가능한 총 차량 대수제약과 최소/최대 운행빈도 제약 하에 비용과 수익을 모두 포함한 순비용을 최소화하는 비선형 최적화 모형이고, 하위 사용자 모형은 가변수요와 용량제약으로 인한 노선의 혼잡, 그리고 노선 간환승에 따른 지체를 고려한 확률적 사용자 평형수단/경로선택 모형이다. 모형의 해법으로는 상위 모형의 경우 목적함수의 그레디언트를 기반으로 하는 "그레디언트 투사 해법"을 제안하였고, 하위모형의 경우는 기존의 "반복조정해법"을 활용하였다. 또한, 구축된 모형과 해법을 소규모 예제네트워크에 적용하여 그 수렴성과 도출된 해를 분석하였다. 본 논문의 운행빈도 설계방법론은 노선의 운영 효율성을 진단 평가하고, 투입 차량대수 제약 하에 대중교통 운영 효율을 개선하는 방안을 마련하는 데 있어 이론적인 토대로 활용될 수 있을 것으로 기대된다.

트랙터, 콤바인, 이앙기의 수요 함수 추정 (Estimating Demand Functions of Tractor, Combine and Rice Transplanter)

  • 김관수;박창근;김경욱;김병갑
    • Journal of Biosystems Engineering
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    • 제31권3호
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    • pp.194-202
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    • 2006
  • Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.

가변 비트율 주문형 비디오 서버에서 자원 활용률을 높이기 위한 버퍼 관리 기법 (A Buffer Management Scheme to Maximize the Utilization of System Resources for Variable Bit Rate Video-On-Demand Servers)

  • 김순철
    • 한국산업정보학회논문지
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    • 제9권3호
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    • pp.1-10
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    • 2004
  • 주문형 비디오 시스템에서 가변 비트율로 압축된 데이터들은 압축 대상이 되는 데이터의 내용 변화와 압축 기법의 특성으로 인해 단위 시간 당 처리해야 할 데이터 크기가 일정하지 않다. 그러나, 대부분의 주문형 비디오 서버들은 가변 비트율로 압축된 데이터를 실시간에 처리하기 위해 가변 데이터 크기의 최대값으로 시스템 자원을 예약하기 때문에 자원의 활용률이 떨어진다. 본 논문에서는 가변 비트율로 압축된 데이터를 예약할 때 선반입을 사용하여 서버의 사용자 수용 가능성을 극대화할 수 있음을 증명하고 이를 구현한 버퍼 관리 기법을 제안한다. 제안된 버퍼 관리 기법은 현실적으로 가능한 최대의 블록들을 사용 순서에 따라 버퍼에 반입한다 또한, 소비 시점이 먼 블록부터 반출하고 소비 시점이 가까운 블록부터 반입함으로써 비디오 서버의 자원 활용률을 최대화할 수 있다. 본 논문에서 제안한 버퍼 관리 기법의 효율성은 모의 실험을 통해 확인하였다.

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An Econometric Analysis of Imported Softwood Log Markets in South Korea - on the Basis of the Lagged Dependent Variable -

  • Park, Yong Bae;Youn, Yeo-Chang
    • 한국산림과학회지
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    • 제98권2호
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    • pp.148-155
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    • 2009
  • The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

Prediction of Global Industrial Water Demand using Machine Learning

  • Panda, Manas Ranjan;Kim, Yeonjoo
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.156-156
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    • 2022
  • Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

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