• Title, Summary, Keyword: demanding forecasting

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Data Center Remote Management Service for Demanding Forecasting and Reduction of Energy U sage (에너지 수요예측 및 절감을 위한 데이터 센터 원격 관리 서비스)

  • Han, Jong-Hoon;Jung, Dae-Kyo;Bae, Kwang-Yong
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.9 no.3
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    • pp.107-111
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    • 2010
  • This paper is concerned with data center remote management service for demanding forecasting and reduction of energy usage. More particularly, intelligent server rack, mounted on inside of the data center, collects information about energy usage and temperature per server. Using this information, management platform forecasts energy demand in the future and automatically makes report according green environment raw. By providing the remote management service through remote terminals, users are not tied to a time and place to control device inside the data center. In this way, the data center remote management service enhances operability of the facility.

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A Study on Demanding forecasting Model of a Cadastral Surveying Operation by analyzing its primary factors (지적측량업무 영향요인 분석을 통한 수요예측모형 연구)

  • Song, Myeong-Suk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • pp.477-481
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    • 2007
  • The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

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Working Electrical Energy Forecasting for Peak Load Estimation of Distribution Transformer (주상변압기 최대부하 추정을 위한 수용가 사용전력량 예측)

  • Park, Chang-Ho;Cho, Seong-Soo;Kim, Jae-Cheol;Kim, Du-Bong;Yun, Sang-Yun;Lee, Dong-Jun
    • Proceedings of the KIEE Conference
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    • pp.929-931
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    • 1998
  • This paper describes the peak load forecasting technique of distribution transformers with correlation equation. While customers are demanding safe energy supply, conventional correlation equation that is used for load management of distribution transformers in domestic has some problems. To get accurate correlation equation, se-correlation equation were examined using new collected using the measuring instrument dev for this study. It was recognized that the qua equation was the most accurate for peak forecasting from working electrical energy.

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A Study on Forecasting Spare Parts Demand based on Data-Mining (데이터 마이닝 기반의 수리부속 수요예측 연구)

  • Kim, Jaedong;Lee, Hanjun
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.121-129
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    • 2017
  • Demand forecasting is one of the most critical tasks in defense logistics, because the failure of the task can bring about a huge waste of budget. Up to date, ROK-MND(Republic of Korea - Ministry of National Defense) has analyzed past component consumption data with time-series techniques to predict each component's demand. However, the accuracy of the prediction still needs to be improved. In our study, we attempted to find consumption pattern using data mining techniques. We gathered an 18,476 component consumption data first, and then derived diverse features to utilize them in identification of demanding patterns in the consumption data. The results show that our approach improves demand forecasting with higher accuracy.

A Study on Demand Forecasting of Export Goods Based on Vector Autoregressive Model : Subject to Each Small Passenger Vehicles Quarterly Exported to USA (VAR모형을 이용한 수출상품 수요예측에 관한 연구: 소형 승용차 모델별 분기별 대미수출을 중심으로)

  • Cho, Jung-Hyeong
    • International Commerce and Information Review
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    • v.16 no.3
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    • pp.73-96
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    • 2014
  • The purpose of this research is to evaluate a short-term export demand forecasting model reflecting individual passenger vehicle brands and market characteristics by using Vector Autoregressive (VAR) models that are based on multivariate time-series model. The short-term export demand forecasting model was created by discerning theoretical potential factors that affect the short-term export demand of individual passenger vehicle brands. Quarterly short-term export demand forecasting model for two Korean small vehicle brands (Accent and Avante) were created by using VAR model. Predictive value at t+1 quarter calculated with the forecasting models for each passenger vehicle brand and the actual amount of sales were compared and evaluated by altering subject period by one quarter. As a result, RMSE % of Accent and Avante was 4.3% and 20.0% respectively. They amount to 3.9 days for Accent and 18.4 days for Avante when calculated per daily sales amount. This shows that the short-term export demand forecasting model of this research is highly usable in terms of prediction and consistency.

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The Peak Load Forecast of Pole-Transformers by Working Electrical Energy (사용전력량에 의한 주방변압기의 최대 부하 예측)

  • Lee, Dong-Jun;Han, Sung-Ho;Lee, Wook;Kwak, Hee-Ro;Kim, Jae-Chul
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • pp.101-103
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    • 1996
  • This Paper describes Peak load forecasting technique of pole transformers with correlation equation. While customers are demanding safe energy supply, current correlation equation that is used for load management of pole transformers has some problems. To get accurate correlation equation. several correlation equation were examined using past data and nu data collected using the measuring instrument developed for this study. It was recognized that the quadratic equation was the most accurate for peak load forecasting from working electrical energy.

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Bivariate long range dependent time series forecasting using deep learning (딥러닝을 이용한 이변량 장기종속시계열 예측)

  • Kim, Jiyoung;Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.32 no.1
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    • pp.69-81
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    • 2019
  • We consider bivariate long range dependent (LRD) time series forecasting using a deep learning method. A long short-term memory (LSTM) network well-suited to time series data is applied to forecast bivariate time series; in addition, we compare the forecasting performance with bivariate fractional autoregressive integrated moving average (FARIMA) models. Out-of-sample forecasting errors are compared with various performance measures for functional MRI (fMRI) data and daily realized volatility data. The results show a subtle difference in the predicted values of the FIVARMA model and VARFIMA model. LSTM is computationally demanding due to hyper-parameter selection, but is more stable and the forecasting performance is competitively good to that of parametric long range dependent time series models.

A Feasibility Investigation of adoption for the Seat-type Express Electric railway on the Railroad in Metropolitan area - Focus on the double tracked Seoul-Chuncheon line - (광역철도 좌석형급행열차 도입 타당성에 관한 연구 - 경춘선 복선화구간 중심으로 -)

  • Park, Min-Kyu;Kim, Si-Gon
    • Proceedings of the KSR Conference
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    • pp.1447-1457
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    • 2008
  • The operation of the Seat-type Express Electric railway (SEE) has been watched for an alternative plan according to the increase of competition among the vehicle in metropolitan city. The purpose of this study was to examine a feasibility for the adoption of the SEE by analysis of various condition in the double tracked Souel-Chuncheon line. Fare estimate, station selection for SEE, managerial plan, demanding forecasting and analysis were performed to compute financial efficiency. The results showed financial validity on Revenue Cost Ratio (R/C), Financial Net Present Value (FNPV), Financial Internal Rate of Return (FIRR). This results indicate the evidence that SEE is a new means which is able to complement for finance, transportation capacity in metropolitan city.

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Study on Design for Training Contents about Disaster Management - Design for Training Courses and Subjects Focus on Disaster Field Preparedness and Response - (방재부문 교육 컨텐츠 설계에 관한 연구 - 현장대비 및 대응 중심의 교육과정, 과목 설계 -)

  • Lee, Yong Jae;Nam, Sang Hoon;Lee, Young Jai
    • Journal of Korean Society of Disaster and Security
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    • v.5 no.2
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    • pp.11-20
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    • 2012
  • Recently, inflicted damage for people's life and property from occurred major disaster that landslide by localized downpour and hydrofluoric acid leak from the Gumi. However public needs about safe society is more increasing from disaster because response is unsatisfactory on that. The purpose of this paper is that establish the core foundation for the education contents system of disaster management through cultivating expert. Therefore first, designed the training of course and subject by demand forecast. Next, designed the training course focus on preparedness and response at on-scene.