• 한국정보과학회논문지:정보통신
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• 제34권3호
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• pp.156-167
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• 2007

본 논문에서는 VBR(Variable-Bit-Rate) 트래픽의 비선형적이고 버스티한 특성을 모델화 한 GOP ARIMA(ARIMA for Group Of Pictures) 모델을 칼만 필터 알고리즘을 이용하여 실시간으로 예측하는 기법을 제안한다. 칼만 필터를 이용한 예측 기법은 GOP ARIMA의 상태공간 모델링 과정과 향후 N초 간의 트래픽을 예측하는 과정으로 구성된다. 실험을 위해 GOP의 크기가 각각 15인 세 가지 종류의 MPEG VBR 트래픽(뉴스, 드라마, 스포츠)을 제작하였고, 칼만 필터를 이용한 세 가지 종류의 트래픽의 예측 결과를 선형 예측법과 이중 지수 평활법을 이용해 예측한 결과와 비교해 예측 성능이 상대적으로 우수함을 확인할 수 있었다. 또한 예측값에 신뢰 구간을 설정하는 신뢰 구간 분석법을 통해 트래픽 관점에서 장면 변화를 예측하는 방법을 제시하였다. 본 논문의 칼만 필터 기반의 예측 알고리즘은 MPEG 기반 VBR 트래픽을 비롯한 기타 인터넷 트래픽을 실시간으로 예측하는 방법과 이를 이용해 인터넷 서버의 설계 및 자원 할당 정책 등을 위한 트래픽 엔지니어링 연구에 기여할 수 있을 것이다.

• 실천공학교육논문지
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• 제14권2호
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• pp.305-312
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• 2022

본 논문에서는 기초적인 데이터 예측 모델을 만들고 최적화하는 교육에 초점을 맞추었다. 그리고 데이터 예측 모델을 최적화하는 데 널리 사용되는 머신러닝의 경사하강법 교육 방법을 제안하였다. 미분법을 적용하여 데이터 예측 모델에 필요한 파라미터 값들을 최적화하는 과정에 사용되는 경사하강법의 전체 동작과정을 시각적으로 보여주며, 수학의 미분법이 머신러닝에 효과적으로 사용되는 것을 교육한다. 경사하강법의 전체 동작과정을 시각적으로 설명하기위해, 스프레드시트로 경사하강법 SW를 구현한다. 본 논문에서는 첫번째로, 2변수 경사하강법 교육 방법을 제시하고, 오차 최소제곱법과 비교하여 2변수 데이터 예측모델의 정확도를 검증한다. 두번째로, 3변수 경사하강법 교육 방법을 제시하고, 3변수 데이터 예측모델의 정확도를 검증한다. 이후, 경사하강법 최적화 실습 방향을 제시하고, 비전공자 교육 만족도 결과를 통해, 제안한 경사하강법 교육방법이 갖는 교육 효과를 분석하였다.

• 한국기계가공학회지
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• 제21권2호
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• pp.46-53
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• 2022

This paper presents the design and manufacture of a Solid State Relay (SSR) life prediction device that can predict the lifetime of an SSR, which is a key component of a glass forming machine. The lifetime of an SSR is over when the current supplied to the relay is overcurrent (20 A or higher), and the operating time is 100,000 h or longer. Therefore, the life prediction device for the SSR was designed using DSP to accurately read the current and temperature values from the current and temperature sensors, respectively. The characteristic test of the manufactured non-contact relay life prediction device confirmed that the current and temperature were safely measured. Thus, the SSR lifetime prediction device developed in this study can be used to predict the lifetime of an SSR attached to a glass forming machine.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2008년도 추계학술대회 논문집
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• pp.42-45
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• 2008

Recently, aluminum is widely used to reduce the vehicle weight. Aluminum curved extruded products are used for the design of automotive frame parts. This study focuses on the determination of process condition fur automotive bumper beam with various curvatures. In this study, a curvature prediction model has been proposed considering the geometric relationship and the characteristic of the curvature extrusion equipment. Using the proposed model and FE analysis, the appropriated process condition was determined to produce the bumper beam. Finally, curvature extrusion experiment was carried out to verify the effectiveness of the proposed curvature prediction model and the process condition.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 춘계학술대회논문집
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• pp.180-183
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• 2003

In this research, on-line model for prediction of effective strain distribution hi strip on finishing mill process is prescribed. It has been developed using several selected non-dimensional parameters and previously made average effective strain model via series of finite element process simulations, $\Delta$$\varepsilon$ was introduced to describe the effective strain distribution in strip. To confirm adequate non-dimensional variables uniqueness test was done. And to decide the order of polynomial in on-line model equation tendency test for each variables was done. The prediction accuracy of the proposed model is examined through comparison with finite element calculation results.

• 한국경영과학회지
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• 제26권1호
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2000년도 특별강연 및 춘계학술발표대회 개요집
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• pp.251-255
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• 2000

Recently, the improvement of computer capacities and artificial intelligence ware caused to employ for prediction of residual stresses and strength evaluation. There are a lot of researches regarding the measurement and prediction of residual stresses for weldment using a neural network in the advanced countries, but in our country, a neural network as a technical part, has only been used on the possibilities of employment for welding area. Furthermore, the relationship between residual stress and process parameters using a neural network was wholly lacking. Therefore development of a new technical method for the optimized process parameters on the reduction of residual stress and applyment of real-time production line should be developed. The objectives of this paper is to measure the residual stress of butt welded specimen using strain gage sectioning method and to apply them to a neural network for prediction of residual stresses on a given process parameter. Also, the assessment of the developed system using a neural network was carried out

• ETRI Journal
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• 제26권4호
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• pp.297-306
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• 2004

A plasma is a collection of charged particles and on average is electrically neutral. In fabricating integrated circuits, plasma etching is a key means to transfer a photoresist pattern into an underlayer material. To construct a predictive model of plasma-etching processes, a polynomial neural network (PNN) is applied. This process was characterized by a full factorial experiment, and two attributes modeled are its etch rate and DC bias. According to the number of input variables and type of polynomials to each node, the prediction performance of the PNN was optimized. The various performances of the PNN in diverse environments were compared to three types of statistical regression models and the adaptive network fuzzy inference system (ANFIS). As the demonstrated high-prediction ability in the simulation results shows, the PNN is efficient and much more accurate from the point of view of approximation and prediction abilities.

• 한국군사과학기술학회지
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• 제12권3호
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• pp.354-359
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• 2009

In this paper, the Autocoast algorithm is proposed for EOTS to overcome the target occlusion status. Coast mode, one of tracking modes, is to maintain the servo slew rate with the tracking rate right before the loss of track. The Autocoast algorithm makes decision of entering coast mode by the prediction of target occlusion and tries to refind target after the coast time. This algorithm composes of 3 steps, the first step is the prediction process of the occlusion by target-like background, the second one is the check process of the occlusion happened after background intensity variation, and the last one is the process of refinding target. The result of computer simulation, test under laboratory, and real test with EOTS shows the applicability for the automatic video tracking system.

• 한국정밀공학회지
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• 제32권5호
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• pp.441-446
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• 2015

Chattering during the milling process causes severe problems on both the workpiece and cutting tools. However, chatter vibration is the inevitable phenomenon that operators require the prediction before the process or monitoring system to avoid the chatter in real-time. To predict the chatter vibration with the stability lobe diagram, the dynamic parameters of machine tool are extracted by considering cutting conditions and adapting the material properties. In this study, experimental verifications were taken for various aluminum types with different feed rates to observe the effect of the key parameters. The comparison between experimental results and the predictions was also performed.