• Title/Summary/Keyword: Forecasting error

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Operation Scheduling in a Commercial Building with Chiller System and Energy Storage System for a Demand Response Market (냉각 시스템 및 에너지 저장 시스템을 갖춘 상업용 빌딩의 수요자원 거래시장 대응을 위한 운영 스케줄링)

  • Son, Joon-Ho;Rho, Dae-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.8
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    • pp.312-321
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    • 2018
  • The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

Development of a Freeway Travel Time Estimating and Forecasting Model using Traffic Volume (차량검지기 교통량 데이터를 이용한 고속도로 통행시간 추정 및 예측모형 개발에 관한 연구)

  • 오세창;김명하;백용현
    • Journal of Korean Society of Transportation
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    • v.21 no.5
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    • pp.83-95
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    • 2003
  • This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

The Utilization Probability Model of Expressway Service Area based on Individual Travel Behaviors Using Vehicle Trajectory Data (차량궤적자료를 활용한 통행행태 기반 고속도로 휴게소 이용 확률 모형 개발)

  • Bang, DaeHwan;Lee, YoungIhn;Chang, HyunHo;Han, DongHee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.4
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    • pp.63-75
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    • 2018
  • A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.

An Improvement on the Analysis Techniques of Environmental Radioactivity Around Nuclear Power Plants (원전주변 환경방사능 분석기술의 개선(I))

  • Kim, Soong-Pyung;Chae, Gyung-Sun;Chung, Woon-Kwan
    • Journal of Radiation Protection and Research
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    • v.20 no.1
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    • pp.8-15
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    • 1995
  • An estimate of a change in radioactivity's circumstances around the nuclear power plant is validated with the results of the radioactivity measurements are compared. In this study, to further enhance the reliability of the results obtained from the environmental radioactivity measurements and analysis around the nuclear power plants that have been carried out up to the present. In the korea standard, there is the technical analysis guide for general stable chemical element's, but there is not the technical analysis guide for the radionuclei. therefore the environmental sample collection, the pretreatment of the sample and radionuclide analysis in the sample, the result's of the environmental radioactivity measurements by each organization, etc. are different. It is not sufficient for the database to forecasting a change in radioactivity's circumstances. A comparative study of collection and pretreatment techniques for the soil sample, the results by comparison, the method of minimizing the relative error are proposed. At one side of sample collection, there are going to considered that the surroundings of sample collection like the lay of the land, the provision of the selection standard for the area and pathway of radionuclide adhesion, the coherence of sample collection, etc.. at another side of pretreatment of the sample and measurement in the case of soil sample, how to do homogeneously the soil particle size and the standard tools, i.e. kinds of meshes, must to be selected.

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Chaotic Disaggregation of Daily Rainfall Time Series (카오스를 이용한 일 강우자료의 시간적 분해)

  • Kyoung, Min-Soo;Sivakumar, Bellie;Kim, Hung-Soo;Kim, Byung-Sik
    • Journal of Korea Water Resources Association
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    • v.41 no.9
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    • pp.959-967
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    • 2008
  • Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.

Estimation and assessment of long-term drought outlook information using the long-term forecasting data (장기예보자료를 활용한 장기 가뭄전망정보 산정 및 평가)

  • So, Jae-Min;Oh, Taesuk;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.50 no.10
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    • pp.691-701
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    • 2017
  • The objective of this study is to evaluate the long-term drought outlook information based on long-term forecast data for the 2015 drought event. In order to estimate the Standardized Precipitation Index (SPI) for different durations (3-, 6-, 9-, 12-months), we used the observation precipitation of 59 Automated Synoptic Observing System (ASOS) sites, forecast and hindcast data of GloSea5. The Receiver Operating Characteristic (ROC) analysis and statistical analysis (Correlation Coefficient, CC; Root Mean Square Error, RMSE) were used to evaluate the utilization of drought outlook information for the forecast lead-times (1~6months). As a result of ROC analysis, ROC scores of SPI(3), SPI(6), SPI(9) and SPI(12) were estimated to be over 0.70 until the 2-, 3-, 4- and 5-months. The CC and RMSE values of SPI(3), SPI(6), SPI(9) and SPI(12) for forecast lead-time were estimated as (0.60, 0.87), (0.72, 0.95), (0.75, 0.95) and (0.77, 0.89) until the 2-, 4-, 5- and 6-months respectively.

Simulation of Air Quality Over South Korea Using the WRF-Chem Model: Impacts of Chemical Initial and Lateral Boundary Conditions (WRF-Chem 모형을 이용한 한반도 대기질 모의: 화학 초기 및 측면 경계 조건의 영향)

  • Lee, Jae-Hyeong;Chang, Lim-Seok;Lee, Sang-Hyun
    • Atmosphere
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    • v.25 no.4
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    • pp.639-657
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    • 2015
  • There is an increasing need to improve the air quality over South Korea to protect public health from local and remote anthropogenic pollutant emissions that are in an increasing trend. Here, we evaluate the performance of the WRF-Chem (Weather Research and Forecasting-Chemistry) model in simulating near-surface air quality of major Korean cities, and investigate the impacts of time-varying chemical initial and lateral boundary conditions (IC/BCs) on the air quality simulation using a chemical downscaling technique. The model domain was configured over the East Asian region and anthropogenic MICS-Asia 2010 emissions and biogenic MEGAN-2 emissions were applied with RACM gaseous chemistry and MADE/SORGAM aerosol mechanism. Two simulations were conducted for a 30-days period on April 2010 with chemical IC/BCs from the WRF-Chem default chemical species profiles ('WRF experiment') and the MOZART-4 (Model for OZone And Related chemical Tracers version 4) ('WRF_MOZART experiment'), respectively. The WRF_MOZART experiment has showed a better performance to predict near-surface CO, $NO_2$, $SO_2$, and $O_3$ mixing ratios at 7 major Korean cities than the WRF experiment, showing lower mean bias error (MBE) and higher index of agreement (IOA). The quantitative impacts of the chemical IC/BCs have depended on atmospheric residence time of the pollutants as well as the relative difference of chemical mixing ratios between the WRF and WRF_MOZART experiments at the lateral boundaries. Specifically, the WRF_MOZART experiment has reduced MBE in CO and O3 mixing ratios by 60~80 ppb and 5~10 ppb over South Korea than those in the WRF-Chem default simulation, while it has a marginal impact on $NO_2$ and $SO_2$ mixing ratios. Without using MOZART-4 chemical IC, the WRF simulation has required approximately 6-days chemical spin-up time for the East Asian model domain. Overall, the results indicate that realistic chemical IC/BCs are prerequisite in the WRF-Chem simulation to improve a forecast skill of local air quality over South Korea, even in case the model domain is sufficiently large to represent anthropogenic emissions from China, Japan, and South Korea.

Establishing a Demand Forecast Model for Container Inventory in Liner Shipping Companies (정기선사의 컨테이너 재고 수요예측모델 구축에 대한 연구)

  • Jeon, Jun-woo;Jung, Kil-su;Gong, Jeong-min;Yeo, Gi-tae
    • Journal of Korea Port Economic Association
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    • v.32 no.4
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    • pp.1-13
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    • 2016
  • This study attempts to establish a precise forecast model for the container inventory demand of shipping companies through forecasts based on equipment type/size, ports, and weekly system dynamics. The forecast subjects were Shanghai and Yantian Ports. Only dry containers (20, 40) and high cubes (40) were used as the subject container inventory in this study due to their large demand and valid data computation. The simulation period was from 2011 to 2017 and weekly data were used, applying the actual data frequency among shipping companies. The results of the model accuracy test obtained through an application of Mean Absolute Percentage Error (MAPE) verified that the forecast model for dry 40' demand, dry 40' high cube demand, dry 20' supply, dry 40' supply, and dry 40' high cube supply in Shanghai Port provided an accurate prediction, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Shanghai Port was otherwise verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model for dry 40' high cube demand and dry 20' supply in Yantian Port was accurate, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Yantian Port was generally verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model in this study also had relatively high accuracy when compared with the actueal data managed in shipping companies.

The Rearch Of Method in the Appropriate number of Demand and Supply of OMD (한의사인력(韓醫師人力) 공급(供給)의 적정화방안(適定化方案) 연구(硏究))

  • Lee, Jong-Soo
    • The Journal of Korean Medicine
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    • v.19 no.1
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    • pp.299-326
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    • 1998
  • 1. Comparison of demand and supply A. Assumption of estimation of demand and supply we will briefly assumptions used for presumption once more before comparing the result of estimation of demand and supply examined previously 1) supply - The average applying rate for state. examination of graduate: ${\alpha}$=1.03109 - The ratio of successful applicants of state examinations: ${\beta}$=0.97091 - Mortality classified by age : presumed data of the Bureau of statistics - Emigrating rate: 0 % - Time of retire: unconsidered - An army doctor number: unconsidered and regard number of employed oriental medicine doctor. - Standard of 1995 : The number of survival oriental medicine doctor is 8195. the number of employed oriental medicine doctor is 7419. 2) demand - derivated demand method Daily the average amount of medical treatment: according to medical insurance federation data. there is 16 or 6 non allowance patient, we consider amount of medical treatment as 22 persons in practical because 21.94 persons (founded practical examination) are converted to allowance in comming demand. Daily the proper amount of medical treatment: 7 hours form -35 persons 5 hours 30 minutes form -28 persons. Yearly medical treatment days: 229 days. 255 days. 269 days . Increasing rate of visiting hospital days: -1996 year. 1997 year. 1998 year- . Rate of applying insurance: yearly average 71.51% (among the investigated patient) B. Comparison of total sum result 1) supply (provision) Table Ⅳ-1 below shows the estimation of the oriental medicine doctor in the future.

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  • Evaluation of Long-Term Seasonal Predictability of Heatwave over South Korea Using PNU CGCM-WRF Chain (PNU CGCM-WRF Chain을 이용한 남한 지역 폭염 장기 계절 예측성 평가)

    • Kim, Young-Hyun;Kim, Eung-Sup;Choi, Myeong-Ju;Shim, Kyo-Moon;Ahn, Joong-Bae
      • Atmosphere
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      • v.29 no.5
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      • pp.671-687
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      • 2019
    • This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.


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