• Title/Summary/Keyword: ensemble 평균

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Development and Evaluation of an Ensemble Forecasting System for the Regional Ocean Wave of Korea (앙상블 지역 파랑예측시스템 구축 및 검증)

  • Park, JongSook;Kang, KiRyong;Kang, Hyun-Suk
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.30 no.2
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    • pp.84-94
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    • 2018
  • In order to overcome the limitation of deterministic forecast, an ensemble forecasting system for regional ocean wave is developed. This system predicts ocean wind waves based on the meteorological forcing from the Ensemble Prediction System for Global of the Korea Meteorological Administration, which is consisted of 24 ensemble members. The ensemble wave forecasting system is evaluated by using the moored buoy data around Korea. The root mean squared error (RMSE) of ensemble mean showed the better performance than the deterministic forecast system after 2 days, especially RMSE of ensemble mean is improved by 15% compared with the deterministic forecast for 3-day lead time. It means that the ensemble method could reduce the uncertainty of the deterministic prediction system. The Relative Operating Characteristic as an evaluation scheme of probability prediction was bigger than 0.9 showing high predictability, meaning that the ensemble wave forecast could be usefully applied.

Deep Learning Forecast model for City-Gas Acceptance Using Extranoues variable (외재적 변수를 이용한 딥러닝 예측 기반의 도시가스 인수량 예측)

  • Kim, Ji-Hyun;Kim, Gee-Eun;Park, Sang-Jun;Park, Woon-Hak
    • Journal of the Korean Institute of Gas
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    • v.23 no.5
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    • pp.52-58
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    • 2019
  • In this study, we have developed a forecasting model for city- gas acceptance. City-gas corporations have to report about city-gas sale volume next year to KOGAS. So it is a important thing to them. Factors influenced city-gas have differences corresponding to usage classification, however, in city-gas acceptence, it is hard to classificate. So we have considered tha outside temperature as factor that influence regardless of usage classification and the model development was carried out. ARIMA, one of the traditional time series analysis, and LSTM, a deep running technique, were used to construct forecasting models, and various Ensemble techniques were used to minimize the disadvantages of these two methods.Experiments and validation were conducted using data from JB Corp. from 2008 to 2018 for 11 years.The average of the error rate of the daily forecast was 0.48% for Ensemble LSTM, the average of the error rate of the monthly forecast was 2.46% for Ensemble LSTM, And the absolute value of the error rate is 5.24% for Ensemble LSTM.

Ensemble Design of Machine Learning Technigues: Experimental Verification by Prediction of Drifter Trajectory (앙상블을 이용한 기계학습 기법의 설계: 뜰개 이동경로 예측을 통한 실험적 검증)

  • Lee, Chan-Jae;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.3
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    • pp.57-67
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    • 2018
  • The ensemble is a unified approach used for getting better performance by using multiple algorithms in machine learning. In this paper, we introduce boosting and bagging, which have been widely used in ensemble techniques, and design a method using support vector regression, radial basis function network, Gaussian process, and multilayer perceptron. In addition, our experiment was performed by adding a recurrent neural network and MOHID numerical model. The drifter data used for our experimental verification consist of 683 observations in seven regions. The performance of our ensemble technique is verified by comparison with four algorithms each. As verification, mean absolute error was adapted. The presented methods are based on ensemble models using bagging, boosting, and machine learning. The error rate was calculated by assigning the equal weight value and different weight value to each unit model in ensemble. The ensemble model using machine learning showed 61.7% improvement compared to the average of four machine learning technique.

Classification Algorithm for Liver Lesions of Ultrasound Images using Ensemble Deep Learning (앙상블 딥러닝을 이용한 초음파 영상의 간병변증 분류 알고리즘)

  • Cho, Young-Bok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.4
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    • pp.101-106
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    • 2020
  • In the current medical field, ultrasound diagnosis can be said to be the same as a stethoscope in the past. However, due to the nature of ultrasound, it has the disadvantage that the prediction of results is uncertain depending on the skill level of the examiner. Therefore, this paper aims to improve the accuracy of liver lesion detection during ultrasound examination based on deep learning technology to solve this problem. In the proposed paper, we compared the accuracy of lesion classification using a CNN model and an ensemble model. As a result of the experiment, it was confirmed that the classification accuracy in the CNN model averaged 82.33% and the ensemble model averaged 89.9%, about 7% higher. Also, it was confirmed that the ensemble model was 0.97 in the average ROC curve, which is about 0.4 higher than the CNN model.

Generation of runoff ensemble members using the shot noise process based rainfall-runoff model (Shot Noise Process 기반 강우-유출 모형을 이용한 유출 앙상블 멤버 생성)

  • Kang, Minseok;Cho, Eunsaem;Yoo, Chulsang
    • Journal of Korea Water Resources Association
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    • v.52 no.9
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    • pp.603-613
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    • 2019
  • This study proposes a method to generate runoff ensemble members using a rainfall-runoff model based on the shot noise process (hereafter the rainfall-runoff model). The proposed method was applied to generate runoff ensemble members for three drainage basins of Daerim 2, Guro 1 and the Jungdong, whose results were then compared with the observed. The parameters of the rainfall-runoff model were estimated using the empirical formulas like the Kerby, Kraven II and Russel, also the concept of modified rational formula. Gamma and exponential distributions were used to generate random numbers of the parameters of the rainfall-runoff model. Especially, the gamma distribution is found to be useful to generate various random numbers depending on the pre-assigned relationship between mean and standard deviation. Comparison between the generated runoff ensemble members and the observed shows that those runoff ensemble members generated using the gamma distribution with its standard deviation twice of the mean properly cover the observed runoff.

Enhancement of Evoked Potential Waveform using Delay-compensated Wiener Filtering (지연보상 위너 필터링에 의한 유발전위 파형개선)

  • Lee, JeeEun;Yoo, Sun K.
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.12
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    • pp.261-269
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    • 2013
  • In this paper, the evoked potential(EP) was represented by additive delay model to comply with the variational noisy response of stimulus-event synchronization. The hybrid method of delay compensated-Wiener filtered-ensemble averaging(DWEA) was proposed to enhance the EP signal distortion occurred during averaging procedure due to synchronization timing mismatch. The performance of DWEA has been tested by surrogated simulation, which is composed of synthesized arbitrary delay and arbitrary level of added noise. The performance of DWEA is better than those of Wiener filtered-ensemble averaging and of conventional ensemble averaging. DWEA is endurable up to added noise gain of 7 for 10 % mean square error limit. Throughout the experimentation observation, it has been demonstrated that DWEA can be applied to enhance the evoked potential having the synchronization mismatch with added noise.

Measurement of Flow Field through a Staggered Tube Bundle using Particle Image Velocimetry (PIV기법에 의한 엇갈린 관군 배열 내부의 유동장 측정)

  • 김경천;최득관;박재동
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.13 no.7
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    • pp.595-601
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    • 2001
  • We applied PIV method to obtain instantaneous and ensemble averaged velocity fields from the first row to the fifth row of a staggered tube bundle. The Reynolds number based on the tube diameter and the maximum velocity was set to be 4,000. Remarkably different natures are observed in the developing bundle flow. Such differences are depicted in the mean recirculating bubble length and the vorticity distributions. The jet-like flow seems to be a dominant feature after the second row and usually skew. However, the ensemble averaged fields show symmetric profiles and the flow characteristics between the third and fourth measuring planes are not so different. comparison between the PIV data and the RANS simulation yields severe disagreement in spite of the same Reynolds number. It can be explained that the distinct jet-like unsteady motions are not to be accounted in th steady numerical analysis.

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Field observation of sediment suspension in the surf zone (쇄파대의 저질부유에 관한 현지관측)

  • 신승호;율산서소
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2003.05a
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    • pp.141-146
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    • 2003
  • Time seres of suspended sediment concentration, surface elevation and velocity were measured and analysed to investigate the role of waves and the predominance of infra-gravity wave component for sediment suspension phenomena in the surf zone. For the investigation in detail, we adopted the cross spectral analysis method between sediment concentration and the characteristic values of wave, and ensemble average analysis method about long-period wave component, which is dominant to sediment suspension in the measurement point. The obtained results are summarized as follows: 1) The relationship between sediment concentration and the characteristic values of wave is stronger for the long-period standing wave components(about 60s and 30s) than the long wave components(about 100s), which have the most energetic power, 2) and also, it is cleared that sediment concentration is increased in the case of the phase, the velocity components of the first mode long-period standing wave(60sec) were accelerated toward on-shore direction, that is, the water surface in offshore side is higher than on-shore side.

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Characteristics of in-cylinder flow near the spark-plug for different engine speeds (엔진속도 변화에 따른 연소실내 Spark Plug 주위의 유동특성 고찰)

  • Seong, Baek-Gyu;Jeon, Gwang-Min
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.20 no.7
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    • pp.2289-2297
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    • 1996
  • Flows in the combustion chamber near the spark plug are measured using LDv.A single cylinder DOHC S.I. engine of compression ratio 9.5:1 with a transparent quartz window piston is used. Combustion chamber shape is semi-wedge type. Measured data are analyzed using the ensemble averaged analysis and the cycle resolved analysis which uses FFT Filtering. Turbulent intensity and mean velocity are studied in the main flow direction and the normal to main flow direction as a function of engine speeds. The results shows that the turbulent intensity obtained by the ensemble averaged analysis is greater than that calculated by the cycle resolved analysis. Especially, the ensemble averaged analysis shows increase in turbulence at the end of compression stroke although the cycle resolved analysis shows increase only in the cycle-by-cycle variation with no noticeable increase in turbulence. The mean velocity in the main flow direction increase as engine speed increase. But the mean velocity normal to the main flow does not show such increase. Turbulent intensity in both direction increase in proportion to engine speeds. The magnitude of turbulent intensity is about 0.3 ~ 0.4 times the mean piston speeds at the end of the compression stroke.

Noise Reduction Technique by Three-Points Ensemble Averaging in Uroflowmetry (삼점 신호 평균기법에 의한 요속신호의 잡음 축소 기법)

  • Choi, Seong-Su;Lee, In-Kwang;Lee, Sang-Bong;Park, Jun-Oh;Lee, Su-Ok;Cha, Eun-Jong;Kim, Kyung-Ah
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.8
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    • pp.1638-1643
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    • 2009
  • Uroflowmetry is a convenient clinical test to screen the benign prostatic hyperplasia(BPH) common in the aged men. A load cell is located beneath the urine container to measure the weight of urine. However, it is sensitive to the impact applied on the bottom of the container by the urine stream, which could be a noise source lowering the reliability of the system. With this aim, our study proposed a noise reduction technique by computing ensemble average of the weighted signals that were acquired from three-load cells forming a regular triangle beneath the urine container. Simulated urination experiment was performed with three different collection methods, all of which demonstrated significant noise reduction by ensemble averaging. Furthermore, the best results can be obtained without any special urine collection devices. Thus, our novel method can be usefully applied to uroflowmetry for enhancing measurement in terms of accuracy and reliability.