• The Journal of Asian Finance, Economics and Business
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• 제9권10호
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• pp.1-13
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• 2022

This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the "weight" of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

• 한국컴퓨터정보학회논문지
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• 제25권7호
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• pp.175-182
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• 2020

연속형 분포로부터 얻은 독립적인 p값들을 통합하는 Fisher의 고전적인 방법은 널리 사용되고 있지만 이산형 확률분포로부터 얻은 p값들을 통합하기에는 적절하지 않다. 대신에 유사 Fisher의 통합방법이 이산형 확률분포의 p값들을 통합하는 대안으로 사용된다. 본 논문에서는 첫째, 여러 표본들의 위치검정(Fisher-Pitman 검정과 Kruskal-Wallis 검정) 데이터와 관련된 이산형 확률분포로 부터 퍼뮤테이션 방법에 의해 p값들을 구하고, 둘째로 이 p값들을 유사 Fisher의 통합방법을 이용하여 통합한다. 그리고 Fisher의 고전적인 방법과 유사 Fisher의 통합방법의 결과를 비교한다.

• 한국컴퓨터정보학회논문지
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• 제23권7호
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• pp.99-104
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• 2018

In this paper, we compare Fisher's continuous method with an exact discrete analog of Fisher's continuous method from permutation tests for combining p values. The discrete analog of Fisher's continuous method is known to be adequate for combining independent p values from discrete probability distributions. Also permutation tests are widely used as alternatives to conventional parametric tests since these tests are distribution-free, and yield discrete probability distributions and exact p values. In this paper, we obtain permutation p values from discrete probability distributions using Mann-Whitney test data sets (real data and hypothetical data) and combine p values by the exact discrete analog of Fisher's continuous method.

• 한국정보통신학회논문지
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• 제8권2호
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• pp.281-288
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• 2004

본 논문에서는 저속 페이딩 환경 하에서 다중 심볼 차동 복조기의 다이버시티 수신 방법에 대하여 연구한다. MSDD(Multiple Symbol Differential Detection)를 이용하여 다이버시티 수신을 할 경우 복조 블럭의 길이를 크게 할수록 차동 부호화된 MPSK의 Maxim -Ratio-Combining(MRC) 다이버시티 수신기 성능에 수렴하지만 복잡도가 지수적으로 증가하여 현실적으로 구현이 불가능하다. 본 논문에서는 MSDD 수신기에 입력하기 전에 수신 신호들을 정렬 시켜서 결합하는 pre-combining 방식을 제안하였다. 여기서 제안된 pre-combined MSDD 다이버시티 수신기는 준최적 수신기로서 수신기의 복잡도가 복조 블록의 길이에 선형적으로 증가하는 효율적인 MSDD 복조를 가능케 한다. 따라서 고속의 버스트 모뎀과 같이 동기 복조의 어려움이 있을 경우, 채널에 대한 정보에 의존치 않고도 다이버시티 수신을 할 수 있으며 기존의 차동 복조 방식에 비하여 큰 성능 향상을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1949-1952
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• 2004

GPS is widely used for outdoor positioning in many applications. But it is not suitable for positioning in an obstacle environment such as urban area, tunnels and so on, due to variable signal level. So new technology of the positioning is required to provide the consistent error level regardless of any changes in any environment. Abrupt changes of GPS signal can be detected by various fault detection and isolation methods. Conventional FDI (Fault Detection and Isolation) methods are categorized into two approaches. One approach is the snapshot method that uses measurements only at present step. The other approach is the filtering method that uses measurements stacked from previous step to present step. The FDI result of the snapshot method can be considered reliable independently with previous results and the FDI result of the filtering method is more reliable and detection time is a little longer. Therefore combining approach of two methods is proposed for increasing FDI performance in this paper. Three approaches that are the snapshot method, the filtering method and the combining method are compared to show the probability of correct FDI in simulations. The combining approach presents best result of FDI among them and shows the consistent accuracy irrespective of any changes in outdoor environment.

• 대한산업공학회지
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• 제26권3호
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• 한국위성정보통신학회논문지
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• 제12권2호
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• pp.38-41
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• 2017

이동형 위성단말의 운용 환경에서는 장애물로 수신 성능이 감소한다. 하나의 방법으로 Diversity를 적용하여 수신 성능을 향상시킬 수 있다. 본 논문에서는 Diversity방법 중 Equal Gain Combining(EGC)방식과 Selective Combining(SC)방식을 적용하여 성능을 분석한다. 분석을 위해 이동형 위성단말로 측정한 결과를 활용한다. 분석결과 SC방식을 사용 시 성능향상을 확인할 수 있었다. 하지만 EGC방식은 rural지역에선 성능향상을 보이지만, urban지역에서는 성능이 나빠지는 결과를 확인할 수 있었다.

• 한국군사과학기술학회지
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• 제17권5호
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• pp.611-619
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• 2014

Combining similar data provides larger data sets through conducting test for homogeneity of several samples under various production processes or samples from different LOTs. The test for homogeneity has been applied to either variable or attribute data, and for variable data set physical homogeneity has been tested without consideration of the specification to the set. This paper proposes a method for test of homogeneity based on quality level through using both variable data and the specification. Quality-based test for homogeneity as a way of combining data is implemented by test for coefficient of variation in the proposed method. The method was verified through the application to the data set in open literature. And possibility to combine performance data for various types of thermal battery was discussed in order to estimate operation reliability.

• 대한안전경영과학회지
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• 제18권4호
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• pp.161-169
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• 2016

In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.

• 방송공학회논문지
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• 제11권2호
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• pp.222-228
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• 2006

이 논문에서는 동일채널 간섭이 존재하는 채널 환경에서 OFDM(Orthogonal Frequency Division Multiplexing) 시스템의 수신 다이버시티 결합 방법을 제시한다. 제시한 방법에서 각 수신 안테나로부터의 수신 신호는 주파수 영역에서 부반송파 단위로 결합하며, 잡음과 간섭 전력을 고려한 MRC(Maximum Ratio Combining)를 적용한다. 잡음과 간섭 전력은 채널의 제한된 지연 확산에 기인하는 주파수 대역에서의 상관특성(coherency)을 이용하여 상관성이 큰 일정구간 이내의 부채널에 대해 잡음과 간섭 전력의 평균을 취함으로써 더 정확한 추정치를 얻는다. IEEE 802.11a 무선 LAN 규격에서 모의실험한 결과 제안방법은 간섭전력을 이용하지 않는 방식에 비해 신호대잡음비를 2-3.5dB 개선하였으며, 정확하게 잡음 및 간섭 전력을 추정한 경우에 대해 1dB 이내로 접근하는 결과를 나타내었다.