• 제목/요약/키워드: time series evaluation

검색결과 507건 처리시간 0.024초

초공간을 고려한 SA 508강의 재질열화 시계열 신호의 카오스성 평가 (Chaotic evaluation of material degradation time series signals of SA 508 Steel considering the hyperspace)

  • 고준빈;윤인식;오상균;이영호
    • Journal of Welding and Joining
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    • 제16권6호
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    • pp.86-96
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    • 1998
  • This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

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Performance Evaluation of a Feature-Importance-based Feature Selection Method for Time Series Prediction

  • Hyun, Ahn
    • Journal of information and communication convergence engineering
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    • 제21권1호
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    • pp.82-89
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    • 2023
  • Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

타임 워핑 하의 시계열 서브시퀀스 매칭 기법의 성능 평가 (Performance Evaluation of Methods for Time-Series Subsequence Matching Under Time Warping)

  • 김만순;김상욱
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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    • pp.290-297
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    • 2003
  • 시계열 데이터베이스란 객체의 변화되는 값들의 연속으로 구성된 데이터 시퀀스들의 집합이며, 타임 워핑 하의 서브시퀀스 매칭은 주어진 질의 시퀀스와 타임 워핑 거리가 허용치 이하인 서브시퀀스들을 시계열 데이터베이스로부터 찾아내는 연산이다. 본 논문에서는 먼저 타임 워핑 하의 시퀀스 매칭을 지원하는 기존의 기법들의 특성을 지적하고, 이들을 전체매칭 및 서브시퀀스 매칭에 각각 적용하는 방안에 관하여 논의한다. 또한, 실제 주식 데이터를 이용한 다양한 실험을 통하여 이들에 대한 정량적인 성능평가를 수행한다. 타임 워핑 하의 서브시퀀스 매칭을 위한 기존 기법들의 성능을 상호 비교한 연구 결과는 아직 제시된 바 없다. 따라서 본 연구 결과는 이러한 세 가지 기법들에 대한 성능을 제시하는 좋은 자료로서 사용될 수 있을 것이다.

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어트랙터 해석을 이용한 AISI 304강 열화 신호의 카오스의 평가 (Evaluation of Chaotic evaluation of degradation signals of AISI 304 steel using the Attractor Analysis)

  • 오상균
    • 한국생산제조학회지
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    • 제9권2호
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    • pp.45-51
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    • 2000
  • This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

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Correlation between Velocity Fluctuation and Fluctuation of Hydrogen Concentration in 2-D Air-Hydrogen Supersonic Mixing Layer

  • Sakima, Fuminori;Arai, Takakage;Edward, Shelley-R.;Mori, Yuko
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2004년도 제22회 춘계학술대회논문집
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    • pp.111-116
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    • 2004
  • An experiment was carried out to confirm the validity of time series evaluation of supersonic mixing condition by using catalytic reaction on a platinum wire. Geseous hydrogen was injected parallel to supersonic freestream (M$\infty$ $\approx$ 1.81) from a slit injector, which was located at backward facing step. Time series condition of supersonic mixing was evaluated by using W-type probe which has a platinum wire and reference wire (nickel wire). The evaluation was by simultaneously measuring each electric circuit which kept the temperature of wire constant. Investigations were also conducted for helium, air and no secondary injectant cases to compare with the hydrogen injectant case. The results indicated that it was possible to measure the time series behavior of air and hydrogen supersonic mixing layer or coherent motion of turbulence by using this evaluation.

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시계열 모형을 이용한 통신망 트래픽 예측 기법연구 (Time Series Models for Performance Evaluation of Network Traffic Forecasting)

  • 김삼용
    • 응용통계연구
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    • 제20권2호
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    • pp.219-227
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    • 2007
  • 시계열 모형은 통신망 트래픽의 예측과 분석에 유용하게 쓰여 왔다. 본 논문에서는 통신망 트래픽의 예측을 위하여 다양한 시계열 모형을 소개하고 성능평가를 하고자 한다. 이를 위하여 실제 통신망 트래픽 자료에 선형 및 비선형 시계열모형을 적합 시키고 비선형 시계열모형이 선형 시계열 모형보다 예측의 정확도가 우수함을 보이고자 한다.

Accuracy evaluation of 3D time-domain Green function in infinite depth

  • Zhang, Teng;Zhou, Bo;Li, Zhiqing;Han, Xiaoshuang;Gho, Wie Min
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제13권1호
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    • pp.50-56
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    • 2021
  • An accurate evaluation of three-dimensional (3D) Time-Domain Green Function (TDGF) in infinite water depth is essential for ship's hydrodynamic analysis. Various numerical algorithms based on the TDGF properties are considered, including the ascending series expansion at small time parameter, the asymptotic expansion at large time parameter and the Taylor series expansion combines with ordinary differential equation for the time domain analysis. An efficient method (referred as "Present Method") for a better accuracy evaluation of TDGF has been proposed. The numerical results generated from precise integration method and analytical solution of Shan et al. (2019) revealed that the "Present method" provides a better solution in the computational domain. The comparison of the heave hydrodynamic coefficients in solving the radiation problem of a hemisphere at zero speed between the "Present method" and the analytical solutions proposed by Hulme (1982) showed that the difference of result is small, less than 3%.

The Performance of Time Series Models to Forecast Short-Term Electricity Demand

  • Park, W.G.;Kim, S.
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.869-876
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    • 2012
  • In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).

Performance Evaluation of Time Series Models using Short-Term Air Passenger Data

  • Park, W.G.;Kim, S.
    • 응용통계연구
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    • 제25권6호
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    • pp.917-923
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    • 2012
  • We perform a comparison of time series models that include seasonal ARIMA, Fractional ARIMA, and Holt-Winters models; in addition, we also consider hourly and daily air passenger data. The results of the performance evaluation of the models show that the Holt-Winters methods outperforms other models in terms of MAPE.

Time Series Evaluation of Visual Fatigue and Depth Sensation Using a Stereoscopic Display

  • Kim, Sang-Hyun;Kishi, Shinsuke;Kawai, Takashi;Hatada, Toyohiko
    • Journal of Information Display
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    • 제10권4호
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    • pp.188-194
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    • 2009
  • Conventional stereoscopic (3D) displays using binocular parallax generate unnatural conflicts between convergence and accommodation. These conflicts can affect the observer's ability to fuse binocular images and may cause visual fatigue. In this study, time series changes in visual fatigue and depth sensation when viewing stereoscopic images with changing parallax were examined. In particular, the physiological changes, including the subjective symptoms of visual fatigue, when viewing five parallax conditions, were examined. Then a comparative analysis of the 2D and 3D conditions was performed based on the visual function. To obtain data regarding the visual function, the time series changes in the spontaneous-blinking rate before and during the viewing of 3D images were measured. The time series change results suggest that 2D and 3D images cause significantly different types of visual fatigue over the range of binocular disparity.