• 제목/요약/키워드: average absolute error

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다층 퍼셉트론을 이용한 인버터의 효율 감소 진단 모델에 관한 연구 (Research on Model to Diagnose Efficiency Reduction of Inverters using Multilayer Perceptron)

  • 정하영;홍석훈;전재성;임수창;김종찬;박철영
    • 한국멀티미디어학회논문지
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    • 제25권10호
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    • pp.1448-1456
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    • 2022
  • This paper studies a model to diagnose efficiency reduction of inverter using Multilayer Perceptron(MLP). In this study, two inverter data which started operation at different day was used. A Multilayer Perceptron model was made to predict photovoltaic power data of the latest inverter. As a result of the model's performance test, the Mean Absolute Percentage Error(MAPE) was 4.1034. The verified model was applied to one-year-old and two-year-old data after old inverter starting operation. The predictive power of one-year-old inverter was larger than the observed power by 724.9243 on average. And two-year-old inverter's predictive value was larger than the observed power by 836.4616 on average. The prediction error of two-year-old inverter rose 111.5572 on a year. This error is 0.4% of the total capacity. It was proved that the error is meaningful difference by t-test. The error is predicted value minus actual value. Which means that PV system actually generated less than prediction. Therefore, increasing error is decreasing conversion efficiency of inverter. Finally, conversion efficiency of the inverter decreased by 0.4% over a year using this model.

원영상의 로컬 평균을 이용한 경계강조 오차확산법 (Edge Enhanced Error Diffusion based on Local Average of Original Image)

  • 강태하;황병원
    • 한국정보처리학회논문지
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    • 제7권8호
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    • pp.2565-2574
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    • 2000
  • 오차확산법은 연속계조 영상을 중간조 영상으로 생성시 우수한 재현성을 보인다. 그러나 표시오차의 전력스펙트럼 분석에서 경계정보의 재현성이 다소 떨어지는 특성을 보인다. 이를 개선하기 위해 원영상의 현재화소와 로컬 평균간의 차이정보를 이용하는 경계강조 오차확산법을 제안한다. 제안한 기법은 원영상이 현재화소와 로컬 평균과의 차이정보 및 이를 활용하는 필터의 가중치 함수로 구성된다. 첫째, 원영상의 차이정보는 현재 화소와 이의 인접화소(5x5)의 로컬 평균과의 차이이다. 둘째, 필터의 가중치 함수는 차이정보의 크기를 포함하는 함수와 이의 부호로 구성된다. 제안한 기법을 적용한 중간조 영상은 경계가 강조되어 시각적으로 선명한 결과를 보인다. 환상 평균 전력 스펙트럼 밀도를 이용한 표시오차, 경계상관도 및 로컬 평균 일치도의 평가함수로 제안한 경계강조 오차확산법과 기존의 경계강조 오차확산법의 특성을 비교한다.

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Design and Implementation of an Absolute Position Sensor Based on Laser Speckle with Reduced Database

  • Tak, Yoon-Oh;Bandoy, Joseph Vermont B.;Eom, Joo Beom;Kwon, Hyuk-Sang
    • Current Optics and Photonics
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    • 제5권4호
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    • pp.362-369
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    • 2021
  • Absolute position sensors are widely used in machine tools and precision measuring instruments because measurement errors are not accumulated, and position measurements can be performed without initialization. The laser speckle-based absolute position sensor, in particular, has advantages in terms of simple system configuration and high measurement accuracy. Unlike traditional absolute position sensors, it does not require an expensive physical length scale; instead, it uses a laser speckle image database to measure a moving surface position. However, there is a problem that a huge database is required to store information in all positions on the surface. Conversely, reducing the size of the database also decreases the accuracy of position measurements. Therefore, in this paper, we propose a new method to measure the surface position with high precision while reducing the size of the database. We use image stitching and approximation methods to reduce database size and speed up measurements. The absolute position error of the proposed method was about 0.27 ± 0.18 ㎛, and the average measurement time was 25 ms.

Modeling and Forecasting Saudi Stock Market Volatility Using Wavelet Methods

  • ALSHAMMARI, Tariq S.;ISMAIL, Mohd T.;AL-WADI, Sadam;SALEH, Mohammad H.;JABER, Jamil J.
    • The Journal of Asian Finance, Economics and Business
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    • 제7권11호
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    • pp.83-93
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    • 2020
  • This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

LH-OAT 민감도 분석과 SCE-UA 최적화 방법을 이용한 SWAT 모형의 자동보정 (Automatic Calibration of SWAT Model Using LH-OAT Sensitivity Analysis and SCE-UA Optimization Method)

  • 이도훈
    • 한국수자원학회논문집
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    • 제39권8호
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    • pp.677-690
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    • 2006
  • 본 연구에서는 LH-OAT (Latin Hypercube Ore factor At a Time) 민감도분석 방법과 SCE-UA (Shuffled Complex Evolution at University of Arizona) 최적화 기법을 적용하여 보청천 유역에서 SWAT모형에 대한 자동보정 방법을 제시하였다. LH-OAT 방법은 전역 민감도분석과 부분 민감도 분석의 장점을 조합하여 가용매개변수 공간에 대하여 효율적으로 매개변수의 민감도 분석이 가능하게 하였다. LH-OAT민감도 분석으로부터 결정된 매개변수의 민감도 등급은 SWAT 모형의 자동보정 과정에서 요구되는 보정대상 매개변수의 선택에 유용하게 적용될 수 있다. SCE-UA 방법을 적용한 SWAT모형의 자동보정 해석결과는 보정자료, 보정매개변수, 통계적 오차의 선택에 따라서 모형의 성능이 좌우되었다. 보정기간과 보정매개변수가 증가함에 따라 검증기간에 대한 RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), NMSE (Normalized Mean Square Error) 등의 모형오차는 감소하였지만, NAE (Normalized Average Error) 및 SDR(Standard Deviation Ratio)은 개선되지 않았다. SWAT모형의 보정에 적용되는 보정자료, 보정매개변수 및 모형평가를 위한 통계적 오차 선택이 해석결과에 미치는 복잡한 영향을 이해하기 위하여 다양한 대표유역을 대상으로 추가적인 연구가 필요하다.

만성 뇌졸중 환자들의 Step Test의 상대적·절대적 신뢰도와 타당도 (The Relative·Absolute Reliability and Validity of Step Test in Patients with Chronic Stroke)

  • 이병권;최현수;안승헌
    • 대한통합의학회지
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    • 제5권1호
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    • pp.43-53
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    • 2017
  • Purpose : To examine the relative absolute reliability and validity of step test (ST) scores in subjects with chronic stroke. Method : A total of 27 stroke patients, participated in the study. A relative reliability index (intraclass correlation coefficient, ICC) was used to examine the level of agreement of inter-rater test-retest reliability for ST score. Absolute reliability indices, including the standard error of measurement(SEM) and the minimal detectable change (MDC), and limits of agreement by Bland and Altman analysis. The validity was demonstrated by spearman correlation of ST score with 10 m Walk Test (10mWT), Fugl-Meyer Assessment-Lower/Extremity (FMA-L/E)-total score, Berg Balance Scale (BBS)-total score. Result : An excellent inter-rater reliability in ST scores was found (paretic, ICC=0.993~0.996; nonparetic, ICC=0.982~0.991). In addition, excellent test-retest reliability was found (paretic, ICC=0.992; nonparetic, ICC=0.967). It all showed acceptable SEM of the ST score as paretic and nonparetic were 0.22 and 0.46 respectively (average score <10 %), and the MDC of the paretic and nonparetic were 0.61 and 1.27 respectively (possible highest score <20 %). indicating that measures had a small and acceptable measurement error. The ST score of paretic and nonparetic were also found to be significantly associated with 10MWT (r=0.77~0.79), FMA-LE scores (r=0.73~0.81) and BBS scores (r=0.72~0.76). Conclusion : The ST showed highly sufficient Inter-rater test-retest agreement and validity and acceptable measurement errors caused by due to chance variation in measurement. It also can be used by clinicians and researchers to assess the balance and mobility performance and monitor functional change in chronic stroke patients.

Development of simulation model of an electric all-wheel-drive vehicle for agricultural work

  • Min Jong Park;Hyeon Ho Jeon;Seung Yun Baek;Seung Min Baek;Dong Il Kang;Seung Jin Ma;Yong Joo Kim
    • 농업과학연구
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    • 제51권3호
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    • pp.315-329
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    • 2024
  • This study was conducted for simulation model development of an electric all-wheel-drive vehicle to adapt the agricultural machinery. Data measurement system was installed on a four-wheel electric driven vehicle using proximity sensor, torque-meter, global positioning system (GPS) and data acquisition (DAQ) device. Axle torque and rotational speed were measured using a torque-meter and a proximity sensor. Driving test was performed on an upland field at a speed of 7 km·h-1. Simulation model was developed using a multi-body dynamics software, and tire properties were measured and calculated to reflect the similar road conditions. Measured and simulated data were compared to validate the developed simulation model performance, and axle rotational speed was selected as simulation input data and axle torque and power were selected as simulation output data. As a result of driving performance, an average axle rotational speed was 115 rpm for each wheel. Average axle torque and power were 4.50, 4.21, 4.04, and 3.22 Nm and 53.42, 50.56, 47.34, and 38.07 W on front left, front right, rear left, and rear right wheel, respectively. As a result of simulation driving, average axle torque and power were 4.51, 3.9, 4.16, and 3.32 Nm and 55.79, 48.11, 51.62, and 41.2 W on front left, front right, rear left, and rear right wheel, respectively. Absolute error of axle torque was calculated as 0.22, 7.36, 2.97, and 3.11% on front left, front right, rear left, rear right wheel, respectively, and absolute error of axle power was calculated as 4.44, 4.85, 9.04, and 8.22% on front left, front right, rear left, and rear right wheel, respectively. As a result of absolute error, it was shown that developed simulation model can be used for driving performance prediction of electric driven vehicle. Only straight driving was considered in this study, and various road and driving conditions would be considered in future study.

항공디지털카메라 영상을 이용한 수치지도 갱신 (Updating Digital Map using Images from Airborne Digital Camera)

  • 황원순;김감래
    • 한국측량학회지
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    • 제25권6_2호
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    • pp.635-643
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    • 2007
  • 국내에 고해상도 지도제작용 항공디지털카메라 영상의 도입 및 공급이 현실화됨에 따라 항공디지털카메라 영상을 이용한 수치지도의 제작 및 갱신에 많은 관심이 모아지고 있다. 본 연구는 푸쉬부룸 항공디지털카메라 영상을 이용하여 기존의 1/1,000 수치지도의 갱신방법을 제시하고자 하였다. GPS측량성과를 이용하여 기하보정을 수행하고, 수치도화를 위해 수치사진측량시스템을 이용하였다. 수치도화는 건물 및 도로를 묘사하였고, GPS측량성과를 이용하여 절대위치정확도 평가와 해석도화에 의해 제작된 수치지도를 이용하여 상대위치정확도 평가를 수행하였다. 절대위치정확도 평가결과, RMSE가 X, Y축으로 각각 ${\pm}0.172m,\;{\pm}0.127m$, 평균거리오차는 0.208m, 상대위치정확도 평가결과, RMSE가 X, Y축으로 각각 ${\pm}0.238m,\;{\pm}0.281m$, 평균거리오차는 0.337m로 나타났다. 따라서, 본 연구에서 제시한 항공디지털카메라 영상을 이용한 수치지도 갱신방법은 국토지리정보원 규정의 허용오차 이내였으므로, 향후 국가기본도 제작은 물론 지자체의 GIS사업 및 다양한 분야에 활용할 수 있다.

A technique for predicting the cutting points of fish for the target weight using AI machine vision

  • Jang, Yong-hun;Lee, Myung-sub
    • 한국컴퓨터정보학회논문지
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    • 제27권4호
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    • pp.27-36
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    • 2022
  • 본 논문에서는 이러한 어류 가공 현장의 문제점을 개선하기 위해서 AI 머신 비전을 이용한 어류의 목표 중량 절단 예측기법을 제안한다. 제안하는 방법은 먼저 입력된 물고기의 평면도와 정면도를 촬영하여 이미지기반의 전처리를 수행한다. 그런 다음 RANSAC(RANdom SAMmple Consensus)를 사용하여 어류의 윤곽선을 추출한 다음 3D 모델링을 사용하여 물고기의 3D 외부 정보를 추출한다. 이어서 추출된 3차원 특징 정보와 측정된 중량 정보를 머신러닝하여 목표 중량에 대한 절단 지점을 예측하기 위한 신경망 모델을 생성한다. 마지막으로 제안기법을 통해 예측된 절단 지점으로 직접 절단한 뒤 그 중량을 측정하였다. 그리고 측정된 무게를 목표 무게와 비교하여 MAE(Mean Absolute Error) 와 MRE(Mean Relative Error)와 같은 평가 방법을 사용해 성능을 평가하였다. 그 결과, 목표 중량과 비교해 3% 이내의 평균 오차율을 달성하였다. 제안된 기법은 향후 자동화 시스템과 연계되어 수산업 발전에 크게 기여할 것으로 전망한다.

증발량 산정을 위한 입사태양복사식 비교 (Comparison of incoming solar radiation equations for evaporation estimation)

  • 임창수
    • 농업과학연구
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    • 제38권1호
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    • pp.129-143
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    • 2011
  • In this study, to select the incoming solar radiation equation which is most suitable for the estimation of Penman evaporation, 12 incoming solar radiation equations were selected. The Penman evaporation rates were estimated using 12 selected incoming solar radiation equations, and the estimated Penman evaporation rates were compared with measured pan evaporation rates. The monthly average daily meteorological data measured from 17 meteorological stations (춘천, 강능, 서울, 인천, 수원, 서산, 청주, 대전, 추풍령, 포항, 대구, 전주, 광주, 부산, 목포, 제주, 진주) were used for this study. To evaluate the reliability of estimated evaporation rates, mean absolute bias error(MABE), root mean square error(RMSE), mean percentage error(MPE) and Nash-Sutcliffe equation were applied. The study results indicate that to estimate pan evaporation using Penman evaporation equation, incoming solar radiation equation using meteorological data such as precipitation, minimum air temperature, sunshine duration, possible duration of sunshine, and extraterrestrial radiation are most suitable for 11 study stations out of 17 study stations.