• Title/Summary/Keyword: time weighted average model

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Prediction of the long-term deformation of high rockfill geostructures using a hybrid back-analysis method

  • Ming Xu;Dehai Jin
    • Geomechanics and Engineering
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    • v.36 no.1
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    • pp.83-97
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    • 2024
  • It is important to make reasonable prediction about the long-term deformation of high rockfill geostructures. However, the deformation is usually underestimated using the rockfill parameters obtained from laboratory tests due to different size effects, which make it necessary to identify parameters from in-situ monitoring data. This paper proposes a novel hybrid back-analysis method with a modified objective function defined for the time-dependent back-analysis problem. The method consists of two stages. In the first stage, an improved weighted average method is proposed to quickly narrow the search region; while in the second stage, an adaptive response surface method is proposed to iteratively search for the satisfactory solution, with a technique that can adaptively consider the translation, contraction or expansion of the exploration region. The accuracy and computational efficiency of the proposed hybrid back-analysis method is demonstrated by back-analyzing the long-term deformation of two high embankments constructed for airport runways, with the rockfills being modeled by a rheological model considering the influence of stress states on the creep behavior.

Effects of DEM Resolution on Hydrological Simulation in, BASINS-BSPF Modeling

  • Jeon, Ji-Hong;Ham, Jong-Hwa;Chun G. Yoon;Kim, Seong-Joon
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.7
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    • pp.25-35
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    • 2002
  • In this study, the effect of DEM (Digital Elevation Model) resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using the BASINS (Better Assessment Science Integrating point and Nonpoint Source) for the Heukcheon watershed (303.3 ㎢) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might affect on the simulation of water quantity and quality. The area weighted average watershed slope became milder but the length weighted average channel slope became steeper as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation, DEM grid size of 100m is recommended for this range of watershed size.

A Switch-Level CMOS Delay Time Modeling and Parameter Extraction (스위치 레벨 CMOS 지연시간 모델링과 파라미터 추출)

  • 김경호;이영근;이상헌;박송배
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.28A no.1
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    • pp.52-59
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    • 1991
  • An effective and accurate delay time model is the key problem in the simulation and timing verification of CMOS logic circuits. We propose a semi-analytic CMOW delay time model taking into account the configuration ratio, the input waveform slope and the load capacitance. This model is based on the Schichman Hodges's DC equations and derived on the optimally weighted switching peak current. The parameters necessary for the model calculation are automatically determined from the program. The proposed model is computationally effective and the error is typically within 10% of the SPICEA results. Compared to the table RC model, the accuracy is inproved over two times in average.

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Estimation of Exposure to Nitrogen Dioxide in Professional Drivers Using Time Activity Pattern (시간행동 행태을 이용한 영업용 운전자들의 이산화질소 개인 노출량 예측)

  • 방용남;손부순;양원호;박종안;장봉기
    • Journal of Environmental Health Sciences
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    • v.27 no.1
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    • pp.20-26
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    • 2001
  • personal nitrogen dioxide(NO$_2$) exposures for 31 professional drivers were measured using passive sampler and time activity diary in Asan and Chunan area, and were estimated using time-weighted average model. Mean concentrations of driver’s indoor and outdoor were 24.7$\pm$10.7 ppb and 23.3$\pm$8.3 ppb, respectively with indoor/outdoor of 1.1. Mean personal NO$_2$ exposure was 30.3$\pm$9.7 ppb. Personal NO$_2$ exposures were strongly correlated with indoor car NO$_2$ levels ($R^2$=0.80) rather than residential indoor NO$_2$ level ($R^2$=0.55). and outdoor NO$_2$ level ($R^2$=0.50). The driver’s NO$_2$ exposure using LP-gas with 24.4$\pm$8.0 ppb were statistically different from those using diesel with 36.3$\pm$14.1 ppb(p<0.01). The effect of driver’s smoking for personal NO$_2$ exposure was not found. It was considered that the main NO$_2$in driver is transportation. Since drivers mostly spent their times in indoor and inside car, time-weighted average model could be used to estimated personal NO$_2$ exposure using time activity diary, Though we did not measure all microenvironments, the estimated personal NO$_2$ exposures with 26.9$\pm$10.2 ppb were statistically correlated with measured personal NO $_2$ exposures30.3$\pm$9.7 ppb ($R^2$=0.89). The mean and standard deviation of personal NO$_2$ exposure using Mote-Carlo simulation were 26.6$\pm$7.2 ppb.

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Multivariate GARCH and Its Application to Bivariate Time Series

  • Choi, M.S.;Park, J.A.;Hwang, S.Y.
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.915-925
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    • 2007
  • Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

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Decentralized Moving Average Filtering with Uncertainties

  • Song, Il Young
    • Journal of Sensor Science and Technology
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    • v.25 no.6
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    • pp.418-422
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    • 2016
  • A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

Assessment of Personal Exposure to Nitrogen Dioxide in Primary Schoolchildren

  • Cho Yong-Sung;Lee Jong-Tae;Kim Yoon-Shin
    • Journal of Environmental Health Sciences
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    • v.32 no.3
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    • pp.207-214
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    • 2006
  • This study was designed to assess the level of nitrogen dioxide from several microenvironments including inside the home, outdoors near the home, inside the school, outdoors near the school, and on the road for 42 primary schoolchildren during the month of December 2002 in Seoul, Korea. The average personal, indoor, outdoor $NO_2$ levels, and indoor/outdoor ratio were 45.08 ppb, 27.89 ppb, 30.96 ppb, and 0.89, respectively. The indoor $NO_2$ concentrations were significantly associated with the presence of a smoker with a gas stove. The estimated personal $NO_2$ exposure using time-weighted average equation of $34.64{\pm}5.29$ ppb was significantly lower than the measured personal exposure of $45.08{\pm}5.50$ ppb. Our results indicate that indoor $NO_2$ levels were associated with the presence of a smoker and a gas stove. Moreover, personal $NO_2$ exposure with a gas stove in the house was significantly higher than those without a gas stove.

The Study of Prediction Model of Gas Accidents Using Time Series Analysis (시계열 분석을 이용한 가스사고 발생 예측 연구)

  • Lee, Su-Kyung;Hur, Young-Taeg;Shin, Dong-Il;Song, Dong-Woo;Kim, Ki-Sung
    • Journal of the Korean Institute of Gas
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    • v.18 no.1
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    • pp.8-16
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    • 2014
  • In this study, the number of gas accidents prediction model was suggested by analyzing the gas accidents occurred in Korea. In order to predict the number of gas accidents, simple moving average method (3, 4, 5 period), weighted average method and exponential smoothing method were applied. Study results of the sum of mean-square error acquired by the models of moving average method for 4 periods and weighted moving average method showed the highest value of 44.4 and 43 respectively. By developing the number of gas accidents prediction model, it could be actively utilized for gas accident prevention activities.

Improve the Reliability Measures of Bus Arrival Time Estimation Model (버스도착시간 추정모형의 신뢰도 향상방안 연구)

  • Kim, Jisoo;Park, Bumjin;Roh, Chang-Gyun;Kang, Woneui
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.597-604
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    • 2014
  • In this study, we investigate to show the limitations of current bus arrival time estimation model based on each bus route, and to propose a bus arrival time estimation model based on a bus stop to overcome these limitations. Using the characteristic of bus arrival time calculated on travel time between two bus stops, we develop a model to estimate bus arrival times with the data of all buses traveling the same section regardless of bus route numbers. In the proposed model, an estimated arrival time is calculated by weighted moving average method, and verification between observed value and estimated time is performed on the basis of RMSE. Error was reduced by up to 20% compared to the existing models and the data update period was reduced by more than half that is related to the accuracy of bus arrival time information. We expect to solve the following problems with the suggested method: sudden increase or decrease in arrival time of the bus, the difference of the expected arrival times at the same stop between two or more buses having different route numbers, and impossibility of offering information of a bus if the bus is not operated with the designated schedule.

Real time forecasting of rainfall-runoff using multiple model adaptive estimation (다중모델적응추정방식을 이용한 강우-유출량의 실시간 예측)

  • 최선욱;김운해;김영철
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.24-27
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    • 1996
  • The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

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