• 제목/요약/키워드: Exponential Smoothing Method

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실시간 BIS자료를 이용한 간선도로의 버스도착시간 예측모형구축에 관한 연구 (Predictive Modeling of the Bus Arrival Time on the Arterial using Real-Time BIS Data)

  • 김태곤;안현철;김승길
    • 대한토목학회논문집
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    • 제29권1D호
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    • pp.1-9
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    • 2009
  • 버스정보시스템(bus information system, BIS)은 지능형교통시스템(intelligent transportation systems, ITS)의 일환으로서 버스정류장에서 버스를 기다리고 있는 이용자들에게 실시간의 버스교통정보를 제공하는 첨단대중교통시스템의 하나이다. 그러나 본 연구대상지역인 울산광역시를 포함하여 버스정보시스템을 운영하고 있는 대부분의 도시에서는 아직 적정의 버스도착시간 예측모형이 구축되어 있지 않기 때문에 현재의 버스위치, 이용자들의 버스 기다리는 시간, 버스 도착시간 등의 보다 정확한 버스정보가 버스 이용자들에게 제공되지 않는 상황이다. 따라서 본 연구에서는 연구대상 간선도로에 대해 실시간의 버스교통특성 자료를 조사하여 버스운행특성을 확인하고, 연구대상구간을 버스 정류장, 교차로 및 순행구간의 단위구간으로 세분하여 각 단위구간에 대해 지수평활법, 가중평활법 및 Kalman Filter법을 적용하여 최적의 단위구간 통행시간 예측모형을 구축하며, 마지막으로 버스정류장에서 실시간의 버스도착시간을 예측하기 위한 최적의 통합모형을 제시하고자 한다.

수요예측 모형의 비교분석과 적용 (A Comparative Analysis of Forecasting Models and its Application)

  • 강영식
    • 산업경영시스템학회지
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    • 제20권44호
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    • pp.243-255
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    • 1997
  • Forecasting the future values of an observed time series is an important problem in many areas, including economics, traffic engineering, production planning, sales forecasting, and stock control. The purpose of this paper is aimed to discover the more efficient forecasting model through the parameter estimation and residual analysis among the quantitative method such as Winters' exponential smoothing model, Box-Jenkins' model, and Kalman filtering model. The mean of the time series is assumed to be a linear combination of known functions. For a parameter estimation and residual analysis, Winters', Box-Jenkins' model use Statgrap and Timeslab software, and Kalman filtering utilizes Fortran language. Therefore, this paper can be used in real fields to obtain the most effective forecasting model.

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범용 Database를 이용한 단기전력수요예측 시스템 개발 (The Development of Short-term Load Forecasting System Using Ordinary Database)

  • 김병수;하성관;송결빈;박정도
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 A
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    • pp.683-685
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    • 2004
  • This paper introduces a basic design for the short-term load forecasting system using a commercial data base. The proposed system uses a hybrid load forecasting method using fuzzy linear regression for forecasting of weekends and Monday and general exponential smoothing for forecasting of weekdays. The temperature sensitive is used to improve the accuracy of the load forecasting during the summer season. MS-SQL Sever has been used a commercial data base for the proposed system and the database is operated by ADO(ActiveX Data Objects) and RDO(Remote Data Object). Database has been constructed by altering the historical load data for the past 38 years. The weather iDormation is included in the database. The developed short-term load forecasting system is developed as a user friendly system based on GUI(Graphical User interface) using MFC(Microsoft Foundation Class). Test results show that the developed system efficiently performs short-term load forecasting.

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Profit-Maximizing Virtual Machine Provisioning Based on Workload Prediction in Computing Cloud

  • Li, Qing;Yang, Qinghai;He, Qingsu;Kwak, Kyung Sup
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권12호
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    • pp.4950-4966
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    • 2015
  • Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.

Further Advances in Forecasting Day-Ahead Electricity Prices Using Time Series Models

  • Guirguis, Hany S.;Felder, Frank A.
    • KIEE International Transactions on Power Engineering
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    • 제4A권3호
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    • pp.159-166
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    • 2004
  • Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York: New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

기하학적 적응제어에 의한 엔드밀링머시인의 안내면 오차 규명 (Identification of guideway errors in the end milling machine using geometric adaptive control algorithm)

  • 정성종;이종원
    • 대한기계학회논문집
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    • 제12권1호
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    • pp.163-172
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    • 1988
  • 본 논문에서는 GAC방법을 이용하여 공작기계의 안내면오차를 수치제어 공작기계가 가지고 있는 가공조건의 조절 능력을 이용하여 가공오차를 보상제어 함으로써 규명(identification)할 수 있는 방법을 제시한다.

온도특성에 대한 데이터 정제를 이용한 제주도의 단기 전력수요 예측 (Short-term Load Forecasting of Using Data refine for Temperature Characteristics at Jeju Island)

  • 김기수;송경빈
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2008년도 추계학술대회 논문집
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    • pp.225-228
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    • 2008
  • The electricity supply and demand to be stable to a system link increase of the variance power supply and operation are requested in jeju Island electricity system. A short-term Load forecasting which uses the characteristic of the Load is essential consequently. We use the interrelationship of the electricity Load and change of a summertime temperature and data refining in the paper. We presented a short-term Load forecasting algorithm of jeju Island and used the correlation coefficient to the criteria of the refining. We used each temperature area data to be refined and forecasted a short-term Load to an exponential smoothing method.

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철도여객수요예측을 위한 Holt-Winters모형의 초기값 설정방법 비교 (An Empirical Comparison among Initialization Methods of Holt-Winters Model for Railway Passenger Demand Forecast)

  • 최태성;김성호
    • 한국철도학회논문집
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    • 제7권1호
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    • pp.9-13
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    • 2004
  • Railway passenger demand forecasts may be used directly, or as inputs to other optimization models use them to produce estimates of other activities. The optimization models require demand forecasts at the most detailed level. In this environment exponential smoothing forecasting methods such as Holt-Winters are appropriate because it is simple and inexpensive in terms of computation. There are several initialization methods for Holt-Winters Model. The purpose of this paper is to compare the initialization methods for Holt-Winters model.

전력수요 변동률을 이용한 연휴에 대한 단기 전력수요예측 (Short-Term Electric Load Forecasting for the Consecutive Holidays Using the Power Demand Variation Rate)

  • 김시연;임종훈;박정도;송경빈
    • 조명전기설비학회논문지
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    • 제27권6호
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    • pp.17-22
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    • 2013
  • Fuzzy linear regression method has been used for short-term load forecasting of the special day in the previous researches. However, considerable load forecasting errors would be occurring if a special day is located on Saturday or Monday. In this paper, a new load forecasting method for the consecutive holidays is proposed with the consideration of the power demand variation rate. In the proposed method, a exponential smoothing model reflecting temperature is used to short-term load forecasting for Sunday during the consecutive holidays and then the loads of the special day during the consecutive holidays is calculated using the hourly power demand variation rate between the previous similar consecutive holidays. The proposed method is tested with 10 cases of the consecutive holidays from 2009 to 2012. Test results show that the average accuracy of the proposed method is improved about 2.96% by comparison with the fuzzy linear regression method.

중복 통신 채널을 가진 CAN 시스템에서 분산 메시지 할당 방법에 관한 연구 (A Study on Distributed Message Allocation Method of CAN System with Dual Communication Channels)

  • 김만호;이종갑;이석;이경창
    • 제어로봇시스템학회논문지
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    • 제16권10호
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    • pp.1018-1023
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    • 2010
  • The CAN (Controller Area Network) system is the most dominant protocol for in-vehicle networking system because it provides bounded transmission delay among ECUs (Electronic Control Units) at data rates between 125Kbps and 1Mbps. And, many automotive companies have chosen the CAN protocol for their in-vehicle networking system such as chassis network system because of its excellent communication characteristics. However, the increasing number of ECUs and the need for more intelligent functions such as ADASs (Advanced Driver Assistance Systems) or IVISs (In-Vehicle Information Systems) require a network with more network capacity and the real-time QoS (Quality-of-Service). As one approach to enhancing the network capacity of a CAN system, this paper introduces a CAN system with dual communication channel. And, this paper presents a distributed message allocation method that allocates messages to the more appropriate channel using forecast traffic of each channel. Finally, an experimental testbed using commercial off-the-shelf microcontrollers with two CAN protocol controllers was used to demonstrate the feasibility of the CAN system with dual communication channel using the distributed message allocation method.