• 한국컴퓨터정보학회논문지
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• 제28권1호
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• pp.17-26
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• 2023

본 연구논문에서는 LSTM 기반의 학습 모델 적용과 그 효용성을 높일 수 있도록 몇 가지 평활 기법을 비교, 적용하고자 한다. 적용된 평활 기법은 Savitky-Golay, 지수 평활법, 가중치 이동 평균 등이다. 본 연구를 통해 비트코인 데이터에 LSTM모델 적용 시 보여준 결과 값보다 전처리 과정에서 적용된 Savitky-Golay 필터가 적용된 LSTM 알고리즘이 예측 성능에 유의미한 좋은 결과를 보였다. 예측 성능 결과를 확인하기 위해 비트코인 가격 예측에 따른 복잡 요인을 제거하는데 사용된 LSTM의 경우와 Savitzky-Golay LSTM 모델에 따른 학습 손실율과 검증 손실율을 비교하고 그 신뢰성을 높일 수 있도록 20회 평균값으로 실험하였다. 그 결과 (3.0556, 0.00005), (1.4659, 0.00002)의 값을 얻을 수 있었다. 결과적으로는 비트코인과 같은 암호화폐가 주식보다 더한 변동성을 가지는 만큼 데이터 전처리 과정에서 평활 기법(Savitzky-Golay)을 적용하여 잡음(Noise)을 제거하였으며, 전처리 후의 데이터는 LSTM 신경망 학습을 통해서 비트코인 예측률을 높이는데 가장 유의미한 결과를 얻을 수 있었다.

• 한국정보통신학회논문지
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• 제23권5호
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• pp.533-539
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• 2019

본 연구는 본 연구는 Microsoft Malware Classification Challenge 데이터 셋을 사용해 임의의 길이 입력 데이터에 대응할 수 있는 멀웨어 분류 모델을 제안한다. 우리는 기존 연구의 멜웨어 데이터를 이미지화 시키는 것을 기반으로 한다. 제안 모델은 멀웨어 데이터가 큰 경우는 많은 이미지를 생성하고, 작은 데이터는 적은 이미지를 생성한다. 생성된 이미지를 시계열 데이터로 Dynamic RNN으로 학습시킨다. RNN의 출력 값은 Attention 기법을 응용해 가장 가중치가 높은 출력만 사용하고, RNN 출력값을 다시 Residual CNN으로 학습시켜 최종적으로 멀웨어를 분류한다. 제안모델을 실험한 결과 검증 데이터 셋에서 Micro-average F1 score 92%를 기록하였다. 실험 결과 특별한 특징 추출 및 차원 축소 없이 임의 길이의 데이터를 학습 및 분류할 수 있는 모델의 성능을 검증할 수 있었다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.179-184
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

• 한국소음진동공학회논문집
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• 제17권12호
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• pp.1208-1216
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• 2007

Turbomachinery such as turbines, pumps and compressors, which are installed in transportation systems, including aircrafts, ships, and space vehicles, etc., often perform crucial missions and are exposed to potential dangerous impact environments such as base-transferred shock forces. To protect turbomachinery from excessive shock forces, it may be needed to accurately analyze transient responses of their rotors, considering the dynamics of mount designs to be applied. In this study a generalized FE transient response analysis model, introducing relative displacements, is proposed to accurately predict transient responses of a flexible rotor-bearing system with mount systems to base-transferred shock forces. In the transient analyses the state-space Newmark method of a direct time integration scheme is utilized, which is based on the average velocity concept. Results show that for the identical mount systems considered, the proposed FE-based detailed flexible rotor model yields more reduced transient vibration responses to the same shocks than a conventional simple model, obtained by treating a rotor as concentrated lumped mass, equivalent spring and a damper or Jeffcott rotor model. Hence, in order to design a rotor-bearing system with a more compact light-weighted mount system, preparing against any potential excessive shock, the proposed FE transient response analysis model herein is recommended.

• 응용통계연구
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• 제34권4호
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• pp.623-632
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• 2021

본 연구에서는 여러가지 시계열 모형 중 평활법(가법계절지수, 승법계절지수), 계절 ARIMA 모형, ARARCH 그리고 AR-GARCH 회귀모형을 이용하여 최대 전력수요를 예측하는 방법을 연구하였다. 이 때 가중 평균모형으로 추세를 갖는 시계열 모형과 온도에 대한 회귀 모형을 적절한 가중치로 예측 정확도를 높이는 방법도 연구하였다. 결과적으로 AR-GARCH 회귀모형으로 예측하는 것이 가중 우수함을 보였다.

• 대한안전경영과학회지
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• 제16권3호
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• pp.451-469
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• 2014

The purpose of this study is to implement and develop the integrated Economic Value Added (EVA) and Time-Driven Activity-Based Costing (TDABC) model to seek both improvement of Net Operating Profit Less Adjusted Tax (NOPLAT) and reduction of Capital Charge (CC). Net Operating Profit Less Adjusted Tax (NOPLAT) can be maximized by reducing the indirect cost of an unused resource capacity increased by Cost Capacity Ratio (CCR) of TDABC. On the other hand, Capital Charge (CC) can be minimized by improving the efficiency of Invested Capital (IC) considered by Weighted Average Cost of Capital (WACC) of EVA. In addition, the integrated system of TDABC using Balance Scorecard (BSC) and EVA is developed by linking between the lagging indicators and the three leading indicators. The three leading indicators include customer, internal process and growth and learning perspectives whereas the lagging indicator includes NOPLAT and CC in terms of financial perspective. When the Critical Success Factor (CSF) of BSC is cascading as a cause and an effect relationship, time driver of TDABC and capital driver of EVA can be used efficiently as Key Performance Indicator (KPI) of BSC. For a better understanding of the proposed EVA/TDABC model and BSC/EVA/TDABC model, numerical examples are derived from this paper. From the proposed model, the time driver of TDABC and the capital driver of EVA are known to lessen indirect cost from comprehensive income statement when increasing the efficiency of operating IC from the statement of financial position with unified KPI cascading of aligned BSC CSFs.

• 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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.387-392
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• 2007

Turbomachinery such as turbines, pumps and compressors, which are installed in transportation systems such as warships, submarines and space vehicles, etc., often perform crucial missions and are exposed to potential dangerous impact environments such as base-transferred shock forces. To protect turbomachinery from excessive shock forces, it may be needed to accurately analyze transient responses of rotors, considering the dynamics of mount designs to be applied with. In this study a generalized FE transient response analysis model, introducing relative displacements, is firstly proposed to accurately predict transient responses of a flexible rotor-bearing system with mount systems to base-transferred shock forces. In the transient analyses the state-space Newmark method of a direct time integration scheme is utilized, which is based on the average velocity concept. Results show that for the identical mount systems considered, the proposed FE-based detailed flexible rotor model yields more reduced transient vibration responses to the same shocks than a conventional simple model or a Jeffcott rotor. Hence, in order to design a rotor-bearing system with a more compact light-weighted mount system, preparing against any potential excessive shock, the proposed FE transient response analysis model herein is recommended.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.64-88
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• 2024

Security and reliability are the utmost importance facts in intelligent networked vehicles. Stochastic Petri Net and Z (SPZN) as an excellent formal verification tool for modeling concurrent systems, can effectively handles concurrent operations within a system, establishes relationships among components, and conducts verification and reasoning to ensure the system's safety and reliability in practical applications. However, the application of a system with numerous nodes to Petri Net often leads to the issue of state explosion. To tackle these challenges, a refinement and abstraction method based on SPZN is proposed in this paper. This approach can not only refine and abstract the Stochastic Petri Net but also establish a corresponding relationship with the Z language. In determining the implementation rate of transitions in Stochastic Petri Net, we employ the interval average and weighted average method, which significantly reduces the time and space complexity compared to alternative techniques and is suitable for expert systems at various levels. This reduction facilitates subsequent comprehensive system analysis and module analysis. Furthermore, by analyzing the properties of Markov Chain isomorphism in the case study, recommendations for minimizing system risks in the application of intelligent parking within the intelligent networked vehicle system can be put forward.

• 환경위생공학
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• 제16권1호
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• pp.1-8
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• 2001

Since most people spend over 80% of their time indoor, indoor air quality tends to be the dominant contributor to personal exposure. In this study, indoor and outdoor $NO_2$concentrations were measured and compared with simultaneously personal exposures of 27 house-wives and female workers of kindergarten. Time activity pattern and house characteristics were used to determine the effects of these factors on personal exposure. Since house-wives student spent most their times in indoor with mean of 89.8%, their $NO_2$ exposure was associated with indoor $NO_2$ level(r= 0.92) rather than outdoor $NO_2$ level(r= 0.87). female workers were also associated with indoor $NO_2$ level(r= 0.70) though sample number were small. Using time-weighted average model, $NO_2$ exposures of house-wives were estimated by $NO_2$ measurements in indoor home and outdoor home levels. Estimated $NO_2$ personal exposures were significantly correlated with measured $NO_2$ personal exposures (r= 0.90). These results might mean that air pollutants exposure of old and feeble persons, and infants could be estimated by measuring concentrations of indoor home.