• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.265-274
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• 2003

Time series data are influenced by the external events such as holiday, strike, oil shock, and political change, so the external events cause a sudden change to the time series data. We regard the observation as outlier that occurred as a result of external events. In general, it is called intervention if we know the period and the reason of external events, and it makes an analyst difficult to establish a time series model. Therefore, it is important that we analyze the styles and effects of intervention. In this paper, we considered the linear time series model with invention and compared with nonlinear time series models such as ARCH, GARCH model and also we compared with the combination prediction method that Tong(1990) introduced. In the practical case study, we compared prediction power with RMSE among linear, nonlinear time series model with intervention and combination prediction method.

• 열처리공학회지
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• 제12권1호
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• pp.40-46
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• 1999

Rotary bending fatigue tests were carried out to investigate the improvement of fatigue limit in annealed and austempered spheroidal graphite cast iron. Main results obtained are as follows. (1) The tensile strength(hardness) of Series C is higher than that of Series B, and fatigue limits are 245MPa in Series C, 230MPa in Series B and 195MPa in Series A, respectively. (2) The fatigue limits of Series B and Series A are mainly governed by the resistance to fatigue crack initiation. Whereas, the fatigue limit of Series C is governed by the resistance to fatigue crack initiation and growth. The defect size and the resistance to crack initiation and growth should be considered to clarify the fatigue properties in spheroidal graphite cast iron. (3) Improvement of fatigue limit by half-austempering is more reasonable than that of full-austempering treatment in multi defective materials as spheroidal graphite cast iron.

• 대한산업공학회지
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• 제25권1호
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• pp.111-124
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• 1999

This evapaper is toluate the forecasting performance of three neural network(NN) approaches against ARIMA model using the famous time series analysis competition data. The first NN approach is to analyze the second Makridakis (M2) Competition Data using Multilayer Perceptron (MLP) that has been the most popular NN model in time series analysis. Since it is recently known that MLP suffers from bias/variance dilemma, two approaches are suggested in this study. The second approach adopts Cascade Correlation Network (CCN) that was suggested by Fahlman & Lebiere as an alternative to MLP. In the third approach, a time series is separated into two series using Noise Filtering Network (NFN) that utilizes autoassociative memory function of neural network. The forecasts in the decomposition analysis are the sum of two prediction values obtained from modeling each decomposed series, respectively. Among the three NN approaches, Decomposition Analysis shows the best forecasting performance on the M2 Competition Data, and is expected to be a promising tool in analyzing socio-economic time series data because it reduces the effect of noise or outliers that is an impediment to modeling the time series generating process.

• 전기학회논문지
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• 제62권7호
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• pp.937-942
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• 2013

Equivalent series impedance of high-voltage pulsed power capacitor is one of the important electrical characteristics both for users and for capacitor manufacturers because it may have serious effects on the performance of pulse forming circuits. In this paper, definition of equivalent series impedance and factors which generate equivalent series impedance are reviewed. Theoretical analysis for the calculation of equivalent series impedance based on differential measurement method is described and calculation program has been developed. In order to acquire data which are necessary to calculate equivalent series impedance from discharging current waveform, charging-dischargig controller has been manufactured. Measurement results of equivalent series impedance for high voltage pulsed power capacitor have been given.

• Industrial Engineering and Management Systems
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• 제14권3호
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• pp.312-317
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• 2015

The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

• Kyungpook Mathematical Journal
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• 제18권2호
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• pp.257-262
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• 1978

In this paper, we obtain two new double infinite series for the H-function of two variables, by which we also obtain a single infinite series involving the H-function of two variable3. On account of the most general nature of the H-functin of two variables, a number of related double infinite series for simpler functions follow as special cases of our results. As an illustration, we obtain here from one of our main series, the corresponding series for $Kamp{\acute{e}}$ de $F{\acute{e}}riet$ function and Fox's H-function. A number of other series involving a very large, spectrum of special functions also follow as special cases of our main series but, we are not recording them here for want of space.

• 한국산학기술학회논문지
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• 제4권4호
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• pp.323-328
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• 2003

본 논문에서는 통신 기지국용 전원으로 사용할 수 있는 직렬 공진형 컨버터 시스템의 새로운 제어방식을 제안하였다. 주파수 제어 직렬 공진형 컨버터 시스템은 병렬 출력 직렬 공진(Parallel Output Series Resonant: POSR)형태이기 때문에 부하변동에 강인하다. 또한 스위칭 주파수를 제어함으로써 입력전압의 변화에도 안정된 출력을 제공한다. 실제 시스템 제작에 앞서 제안된 병렬 출력 직렬 공진형 컨버터 시스템의 분석을 하였고 ACSL(Advanced Continuous Simulation Language)을 이용한 모의실험을 하였다. 또한 실제의 시스템을 제작 및 실험을 통하여 시스템 특성을 확인하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.1437-1440
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• 2007

Many hydroclimatic time series are marked by interannual and longer quasi-period features that are associated with narrow band oscillatory climate modes. A time series modeling approach that directly considers such structures is developed and presented. The essence of the approach is to first develop a wavelet decomposition of the time series that retains only the statistically significant wavelet components, and to then model each such component and the residual time series as univariate autoregressive processes. The efficacy of this approach is demonstrated through the simulation of observed and paleo reconstructions of climate indices related to ENSO and AMO, tree ring and rainfall time series. Long ensemble simulations that preserve the spectral attributes of the time series in each ensemble member can be generated. The usual low order statistics are preserved by the proposed model, and its long memory performance is superior to the direction application of an autoregressive model.

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.264-269
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• 2001

본 논문에서는 악보를 시계열로 해석하여 퍼지 로직을 이용한 모델링에 대하여 다루고자 한다. 악보에 나타난 음악적 기호들은 음의 길이와 높이 등의 많은 정보들은 나타낸다. 본 논문에서는 멜로디, 음높이와 음색들을 사용하여 악보의 시각적 정보를 시계열 자료로 변환한다. 시계열 자료의 특징을 추출하기 위해 시계열 자료에 슬라이딩 윈도우를 통과시켜 다시 한번 새로운 시계열 자료로 변환한다. 변환된 시계열 자료를 분석하기 위해 Box-Jenkins의 시계열 분석 방법을 사용하고 분석된 시계열의 특징을 바탕으로 퍼지 모델을 구성한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.211-214
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• 2001

In this paper, we interpret a score as a time series and deal with the fuzzy logic-based modeling of it. The musical notes in a score represent a lot of information about the length of a sound and pitches, etc. In this paper, using melodies, tones and pitches in a score, we transform data on a score into a time series. Once more, we form the new time series by sliding a window through the time series. For analyzing the time series data, we make use of the Box-Jenkinss time series analysis. On the basis of the identified characteristics of time series, we construct the fuzz model.