• 제목/요약/키워드: Estimated Mean Error

검색결과 566건 처리시간 0.024초

정규 확률과정을 사용한 공조 시스템의 전력 소모량 예측에 관한 연구 (A Study on the Prediction of Power Consumption in the Air-Conditioning System by Using the Gaussian Process)

  • 이창용;송근수;김진호
    • 산업경영시스템학회지
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    • 제39권1호
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    • pp.64-72
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    • 2016
  • In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

Sparse 채널에서 최소평균오차 경계값 분석을 통한 채널 추정 기법의 성능 비교 (Performance evaluation of estimation methods based on analysis of mean square error bounds for the sparse channel)

  • 김현수;김재영;박건우;최영관;정재학
    • 한국위성정보통신학회논문지
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    • 제7권1호
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    • pp.53-58
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    • 2012
  • 본 논문에서는 sparse 채널에서 대표적인 채널 추정 기법들의 오차 성능을 비교 및 분석한다. 오차 성능을 비교하기 위해 크라머-라오 경계를 이용하여 최소평균자승오차 추정기법의 하한 경계를 구하고 이를 정합 추적 기법의 상한 경계와 분석한다. 분석 결과로부터 추정 탭 개수와 신호 대 잡음비에 따라 기존에 sparse 채널에서 효율적인 추정기법으로 알려진 정합 추적 기법보다 최소평균 자승오차 추정기법의 오차가 적을 수 있음을 보인다. 레일리이 페이딩 분포를 갖는 두 개의 sparse 채널에 대한 전산모의실험 결과 신호 대 잡음비에 따라 두 추정 기법의 오차 성능이 반전되는 경우를 보였다.

Weibull-3 분포모형의 모멘트법 및 L-모멘트법에 의한 홍수빈도비교분석 (Comparative Analysis of Flood Frequncy by Moment and L-moment in Weibull-3 distribution)

  • 이순혁;맹승진;송기헌;류경식;지호근
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 1998년도 학술발표회 발표논문집
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    • pp.331-337
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    • 1998
  • This study was carried out to derive optimal design floods by Weibull-3 distribution with the annual maximum series at seven watersheds along Man, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was acknowledged by the tests of Independence, Homogeneity, detection of Outliers. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in Weibull-3 distribution were compared by the rotative mean error and relative absolute error. It has shown that design floods derived by the method of L-moments using Weibull plotting position formula in Weibull-3 distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions in view of relative mean and relative absolute error.

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The Filtered-x Least Mean Fourth Algorithm for Active Noise Cancellation and Its Convergence Behavior

  • Lee, Kang-Seung
    • 한국통신학회논문지
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    • 제26권12A호
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    • pp.2050-2058
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    • 2001
  • In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of 7he convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

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The Filtered-x Least Mean Fourth Algorithm for Active Noise Control and Its Convergence Analysis

  • Lee, Kang-Seung;Youn, Dae-Hee
    • The Journal of the Acoustical Society of Korea
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    • 제15권3E호
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    • pp.66-73
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    • 1996
  • In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise control(ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

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능동 소음 제어를 위한 Filtered-x 최소평균사승 알고리듬 및 수렴 특성에 관한 연구 (The Filtered-x Least Mean Fourth Algorithm for Active Noise Control and Its Convergence Analysis)

  • 이강승;이재천;윤대희
    • 전자공학회논문지B
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    • 제32B권11호
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    • pp.1506-1516
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    • 1995
  • In this paper, we propose the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

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Filtered-x 최소평균사승 능동 소음 제어기 수렴분석 (Convergence Analysis of a Filtered-x Least Mean Fourth Active Noise Controller)

  • 이강승
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1998년도 학술발표대회 논문집 제5권
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    • pp.80-83
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    • 1998
  • In this paper, we propose a new filtered-x least mean fouth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior or a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the ouput and error signal of the adaptive canceller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct component . Phase estimation error and estimated again. In particular , the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

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단상 계통연계형 인버터의 SRF-PLL 옵셋 오차로 인한 전류 맥동 저감에 관한 연구 (A Study on Current Ripple Reduction Due to Offset Error in SRF-PLL for Single-phase Grid-connected Inverters)

  • 황선환;황영기;권순걸
    • 조명전기설비학회논문지
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    • 제28권11호
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    • pp.68-76
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    • 2014
  • This paper presents an offset error compensation algorithm for the accurate phase angle of the grid voltage in single-phase grid-connected inverters. The offset error generated from the grid voltage measurement process cause the fundamental harmonic component with grid frequency in the synchronous reference frame phase lock loop (PLL). As a result, the grid angle is distorted and the power quality in power systems is degraded. In addition, the dq-axis currents in the synchronous reference frame and phase current have the dc component, first and second order ripples compared with the grid frequency under the distorted grid angle. In this paper, the effects of the offset and scaling errors are analyzed based on the synchronous reference frame PLL. Particularly, the offset error can be estimated from the integrator output of the synchronous reference frame PLL and compensated by using proportional-integral controller. Moreover, the RMS (Root Mean Square) function is proposed to detect the offset error component. The effectiveness of the proposed algorithm is verified through simulation and experiment results.

다중 정현파의 능동소음제어를 위한 Filtered-x 최소 평균제곱 적응 알고리듬 수렴 연구 (Convergence of the Filtered-x Least Mean Square Adaptive Algorithm for Active Noise Control of a Multiple Sinusoids)

  • 이강승
    • 한국소음진동공학회논문집
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    • 제13권4호
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    • pp.239-246
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    • 2003
  • Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

CNN 잡음감쇠기에서 필터 수의 최적화 (Optimization of the Number of Filter in CNN Noise Attenuator)

  • 이행우
    • 한국전자통신학회논문지
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    • 제16권4호
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    • pp.625-632
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    • 2021
  • 본 논문은 잡음감쇠기에서 CNN(Convolutional Neural Network) 계층의 필터 수가 성능에 미치는 영향을 연구하였다 이 시스템은 적응필터 대신 신경망 예측필터를 이용하며 심층학습방법으로 잡음을 감쇠한다. 64-뉴런, 16-커널 CNN 필터와 오차 역전파 알고리즘을 이용하여 잡음이 포함된 음성신호로부터 음성을 추정한다. 본 연구에서 필터 수에 대한 잡음감쇠기의 성능을 검증하기 위하여 Keras 라이브러리를 사용한 프로그램을 작성하고 시뮬레이션을 실시하였다. 시뮬레이션 결과, 본 시스템은 필터 수가 16일 때 MSE(Mean Squared Error) 및 MAE(Mean Absolute Error) 값이 가장 작은 것으로 나타났으며 필터가 4개 일 때 성능이 가장 낮은 것을 볼 수 있다. 그리고 필터가 8개 이상이 되면 필터 수에 따라 MSE 및 MAE 값이 크게 차이나지 않는 것을 보여주었다. 이러한 결과로부터 음성신호의 주요 특징을 표현하기 위해서는 약 8개 이상의 필터를 사용해야 한다는 것을 알 수 있다.