• Title/Summary/Keyword: root-mean-square error

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Development of a Linearized Model and Verification of the Exact Solution for the Analysis of a Desiccant Dehumidifier (제습기 성능분석을 위한 선형화 모델 및 해석해의 검증)

  • 이길봉;이대영;김민수
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.16 no.9
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    • pp.811-819
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    • 2004
  • A silica gel desiccant dehumidifier is studied theoretically in this paper adopting several linearization assumptions. The governing equations are linearized with the assumptions, and the exact solutions to the temperature and the humidity ratio are obtained. In spite of the assumptions, the theoretical results are found to agree well with those from the numerical analysis without any assumption. In typical operation ranges of the desiccant dehumidifier, the time-averaged errors in the process air temperature and humidity ratio are less than 4% and 7%, respectively, and the corresponding root-mean-square values are less than 5% and 15%, respectively The analytical solutions are expected to contribute to the fundamental understanding of the dehumidification and regeneration processes and the correlation analysis of the numerous parameters influencing the dehumidifier operation.

Theoretical Prediction Method of Subcooled Flow Boiling CHF

  • Kwon, Yong-Min;Cahng, Soon-Heung
    • Proceedings of the Korean Nuclear Society Conference
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    • 1998.05a
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    • pp.449-456
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    • 1998
  • A theoretical critical heat flux (CLE) model. based on lateral bubble coalescence on the heated wall, is proposed to predict the subcooled flow boiling CHF in a uniformly heated vertical tube. The model is based on the concept that a single layer of bubbles contacted to the heated wall events a bulk liquid from reaching the wall at near CHF condition. Comparisons between the model predictions and experimental data result in satisfactory agreement within less than 9.73 % root-mean-square error by the appropriate choice of the critical void fraction in the bubbly layer. The present model shows comparable performance with the CHF look-up table of Groeneveld et al.

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Development of Knot Quantification Method to Predict Bending Strength Using X-ray Scanner

  • Oh, Jung-Kwon;Kim, Kwang-Mo;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • v.36 no.5
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    • pp.33-41
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    • 2008
  • This study was aimed to develop the knot quantification method to predict bending strength, using x-ray scanner. The bending strength prediction model was proposed in this paper. The model was based on Knot Depth Ratio (KDR) and closely-spaced knot was taken into account. The previous paper reported that KDR is the ratio of the knot and transit zone to the lumber thickness. Even though KDR involves transit zone, it was verified that the ratio of the moment of inertia for knot to gross cross section ($I_k/I_g$) based on KDR was a good predictor for bending strength of lumber. To take closely-spaced knot into account, a projection method was also proposed. This projection method improved the predictive accuracy significantly. It showed coefficient of determinant of 0.65 and root mean square error (RMSE) of 9.17.

Accuracy on the Edge Detection Using High-Resolution Satellite Image (고해상도 위성 영상을 이용한 경계검출에 대한 정확도 분석)

  • 박운용;문두열;홍순헌;윤경철
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.529-534
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    • 2004
  • 고해상도 위성영상을 이용하여 수치지도를 제작함에 있어 가장 큰 문제점은 레스터 자료인 위성영상에서 경계검출을 통해 벡터자료의 형태로 제작하는 어려움이 있다. 본 연구에서는 경계검출을 통하여 위성영상에서 지형의 경계를 검출해내고, 이를 스크린 디지 타이징 기법을 적용하여 벡터라이징 한 후 나타난 결과를 국토지리정보원의 수치지도와 비교하여 정확도를 비교ㆍ평가하였다. 대상 범위는 대전광역시 유성구 가정동 일부지역을 IKONOS로 촬영된 공간해상도 1m의 위성영상을 사용하였다. 위성영상의 전처리는 기하보정과 정사보정을 거친 후 영상강조를 하였고, 여러 가지의 필터링을 적용하여 경계검출을 수행하였다. 경계검출 방법 중에 하나인 Sobel 연산자를 적용한 후 축척 1:5,000 수치지도와의 중첩을 통하여 표준편차(Root Mean Square Error : RMSE)를 산출하여 비교ㆍ분석하였다. 그리고 스크린 디지타이징 기법을 적용하여 추출한 벡터자료를 건물, 도로 및 임야로 분류하여 수치지도와 중첩하여 정확도를 분석하였다. 그 결과 건물과 도로의 경우에는 공공측량 작업규정에서 정하고 있는 축척 1:5,000의 평면위치 허용오차 기준을 만족하고 있지만, 임야의 경우는 축척 1:10,000 이상의 허용오차기준에 만족되고 있음을 알 수 있었다.

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3D face recognition based on facial surface information (얼굴 표면의 형태정보를 이용한 3차원 얼굴인식)

  • Lee, Dong-Joo;Shin, Hyoung-Chul;Sohn, Kwang-Hoon
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.423-424
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    • 2006
  • This paper describes a 3D face recognition using different devices for 3D faces and input faces which include several different pose. Before the recognition stage, through the EC-SVD, all data have to be preprocessed and normalized. At recognition stage, we propose the multi-point signature method for measuring facial surface information. And we use the root mean square error for matching. From the experiment results, we have 92.5% recognition rate.

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On Asymmeticity for Power Transformed TARCH Model

  • Kim, Sahm-Yong;Lee, Sung-Duck;Jeong, Ae-Ran
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.271-281
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    • 2005
  • Zokian(1993) and Li and Li(1996) developed TARCH(Threshold ARCH) model, considering the asymmetries in volatility. The models are based on Engle(1982)'s ARCH model and Bollerslev(1986)'s GARCH model. However, two TARCH models can be expressed a common model through Box Cox Power transformation, which was used by Higgins and Bera(1992) for developing NARCH(nonlinear ARCH) model. This article shows the PTARCH(Power transformation TARCH) model is necessary in some condition, and it checks the fact that PTARCH model has better performance comparing estimates and RMSE(Root Mean Square Error) with those of Zakoian's TARCH model and Li and Li's TARCH model. PTARCH model would give contribution in asymmetric study as well as heteroscedastic study.

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Developing the Traffic Accident Models of Arterial Link Sections by Driving Type (운전 유형에 따른 가로구간 사고모형 개발)

  • Kim, Kyung-Hwan;Park, Byung-Ho
    • Journal of the Korean Society of Safety
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    • v.25 no.6
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    • pp.197-202
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    • 2010
  • This study deals with the accident models of arterial link sections by driving type. The objectives is to develop models by driving type using the accident data of 24 arterial links in Cheong-ju. In pursuing the above, this study gives particular emphasis to modeling such the accidents as the straight, lane change and others. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 59% in straight, 31% in lane change and 10% in others. Second, the number of left-turn lane as common variables, and the ADT, number of pedestrian crossings, connecting roads and link length as specific variables are selected in developing models(number of accident and EPDO). Third, 8 models which are all statistically significant are developed. Finally, RMSE of the driving type models was analyzed to be better than that of dummy variable.

A Practical Approach to the Real Time Prediction of PM10 for the Management of Indoor Air Quality in Subway Stations (지하철 역사 실내 공기질 관리를 위한 실용적 PM10 실시간 예측)

  • Jeong, Karpjoo;Lee, Keun-Young
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.12
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    • pp.2075-2083
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    • 2016
  • The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).

SOC and SOH Estimation Method for the Lithium Batteries Using Single Extended Kalman Filter (단일 확장 칼만 필터를 이용한 리튬배터리의 SOC 및 SOH 추정법)

  • Ko, Younghwi;Choi, Woojin
    • Proceedings of the KIPE Conference
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    • 2019.11a
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    • pp.79-81
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    • 2019
  • 전기자동차(EV)뿐만 아니라 ESS(Energy Storage System) 등의 사용량이 증가하면서 리튬이온배터리의 중요성은 점점 커지고 있다. 리튬 이온 배터리의 정확한 상태를 추정하는 것은 배터리의 안전하고 신뢰성 있는 작동을 위해 매우 중요하다. 본 논문에서는 AEKF(Adaptive Extended Kalman Filter)를 이용한 배터리 파라미터와 충전상태(SOC, State of Charge)를 추정하고, 이를 활용하여 배터리의 건강상태(SOH, State of Health)를 추정하는 간단한 알고리즘을 제시한다. AEKF에 파라미터 값을 적용하여 SOC를 추정하고, 추정된 SOC값과 전류 적산을 이용하여 SOH를 추정한다. SOC 오차에 따른 SOH 추정 값의 편차는 SOC 연산 간격을 늘리고 가중치 필터를 적용하여 최소화시킴으로써 결과의 정확성을 향상했다. 다양한 자동차의 표준 주행 패턴을 적용한 실험을 통해 제안된 방법을 이용하여 얻어진 SOH 추정 결과는 RMSE(Root Mean Square Error) 1.428% 이내임을 검증하였다.

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Using radial basis function neural networks to model torsional strength of reinforced concrete beams

  • Tang, Chao-Wei
    • Computers and Concrete
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    • v.3 no.5
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    • pp.335-355
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    • 2006
  • The application of radial basis function neural networks (RBFN) to predict the ultimate torsional strength of reinforced concrete (RC) beams is explored in this study. A database on torsional failure of RC beams with rectangular section subjected to pure torsion was retrieved from past experiments in the literature; several RBFN models are sequentially built, trained and tested. Then the ultimate torsional strength of each beam is determined from the developed RBFN models. In addition, the predictions of the RBFN models are also compared with those obtained using the ACI 318 Code equations. The study shows that the RBFN models give reasonable predictions of the ultimate torsional strength of RC beams. Moreover, the results also show that the RBFN models provide better accuracy than the existing ACI 318 equations for torsion, both in terms of root-mean-square error and coefficients of determination.