• Journal of the Korean Statistical Society
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• 제35권1호
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• pp.37-47
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• 2006

Recently, as a result of the growing interest in modeling stationary processes with discrete marginal distributions, several models for integer valued time series have been proposed in the literature. One of these models is the integer-valued autoregressive (INAR) models. However, when modeling with integer-valued autoregressive processes, the distributional properties of forecasts have been not yet discovered due to the difficulty in handling the Steutal Van Ham thinning operator 'o' (Steutal and van Ham, 1979). In this study, we derive the mean squared error of h-step-ahead prediction from a Poisson INAR(1) process, reflecting the effect of the variability of parameter estimates in the prediction mean squared error.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 춘계학술발표대회 논문집
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• pp.304-310
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• 2008

Currently energy use planning council system is mandatory especially for the urban development project planned on a specified scale or more. The goal of existing demand prediction was to calculate the maximum load by multiplying energy load per unit area by building size. The result of this method may be exaggerated and has a limit in the information of period load. The paper suggests a new forecasting process based on standard unit household in order to upgrade the limit in demand prediction method of multi-family housing complex. The new process was verified by comparing actual using amount of multi-family housing complex to forecasting value of energy use plan.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 제5회 압연심포지엄 신 시장 개척을 위한 압연기술
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• pp.368-377
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• 2004

A mathematical model was developed for the prediction of the average temperature and RDT(RM Delivery temperature) in a roughing mill. The model consisted of three parts as follows (1) The intermediate numerical model calculated the deformation and heat transfer phenomena in the rolling: region by steady state FEM and the heat transfer phenomena in the interpass region by unsteady state FEM (2) The Off-line prediction model was derived from non-linear regression analysis based on the results of intermediate numerical model considering the various rolling conditions, (3) Using the heat flux in rolling region, temperature profile along thickness direction was calculated. For validation of the presented model, the rolling force per pass and RDT measued in on-line process was compared with those of model and the results showed close agreement with the existing data. In order to demonstrate the effectiveness of the proposed model, the various rolling conditions was tested.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.15-16
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• 2006

In-process surface roughness prediction is studied in this research. To implement in-process prediction, spindle displacement is introduced. Machined surface's roughness is assumed to be expressed in terms of spindle displacement. In-process measurement of spindle displacement is conducted using CCDS (cylindrical capacitive displacement sensor). Two prediction models are developed. One is simple linear model between measured surface roughness and values by spindle displacement. The other is multiple regression model including machining parameters like spindle speed, fee rate and radial depth of cut. Relation between machined surface roughness and roughness by spindle displacement are verified.

• 한국안전학회지
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• 제23권6호
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• pp.7-13
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• 2008

It is important to prevent roll failure in hot rolling process for reducing maintenance cost and production loss. The relationship between rolling pass schedule and the work roll wear profile will be presented. The roll wear pattern is related with roll catastrophic failure. The irregular and deep roll wear pattern should be removed by On-line Roll Grinder(ORG) for roll failure prevention. In this study, a computer roll wear prediction model under real process working condition is developed and evaluated with hot rolling pass schedule. The method of building wear calculation functions for center portion abrasion and marginal abrasion respectively was used to develop a work roll wear prediction mathematical model. The three type rolling schedule are evaluated by wear prediction model. The optimum roll grinding methods is suggested for schedule tree rolling technique.

• 한국정밀공학회지
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• 제10권3호
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• pp.69-80
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• 1993

It is important to prevent roll failure in hot rolling process for reducing maintenance coat and production loss. Roll material and rolling conditions such as the roll force and torque have been intensively investigated to overcome the roll failures. In this study, a computer roll life prediction system under working condition is developed and evaluated on IBM-PC level. The system is composed and fatigue estimation models which are stress analysis, crack propagation, wear and fatigue estimation. Roll damage can be predicted by calculating the stress anplification, crack depth propagation and fatigue level in the roll using this computer model. The developed system is applied to a work roll in actual hot rolling process for reliability evaluation. Roll failures can be diagnosed and the propriety of current working condition can be determined through roll life prediction simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1193-1215
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• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• 대한전자공학회논문지SD
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• 제47권5호
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• pp.1-9
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• 2010

이 논문에서는, 풀 HD 영상을 실시간에 처리가능한 새로운 화면 내 예측 및 DCTQ 하드웨어구조를 제안한다. 화면내 예측,.$4{\times}4$ 을 처리하기 위한 예측과 변환, 양자화, 역양자화, 역변환및 복원의 전체 cycle 을 줄일 수 있는 방법을 제안한다. $4{\times}4$ 예측 부호화 cycle을 줄이기 위해, 양자화과정을 예측 사이클에서 적용할 수 있도록 하였으며, 회로의 크기를 줄이기 위하여 9가지 모드 중 2개의 모드를 먼저 선택하는 알고리듬을 사용하였다. 또한 $16{\times}16$ 예측과 $8{\times}8$ 예측 과정를 하나의 코어를 이용하여 설계하므로 크기를 줄였다. 제안된 구조는 108Mhz 클럭에서 full HD영상을 30frame/sec에서 동작하며, 한 매크로블록의 처리 cycle 은 425 cycle이다.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.243-248
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• 1995

In this article we show that a class of random coefficient autoregressive processes including the NEAR (New exponential autoregressive) process has the strong mixing property in the sense of Rosenblatt with mixing order decaying to zero. The result can be used to construct model free prediction interval for the future observation in the NEAR processes.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2000년도 춘계학술대회논문집
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• pp.52-55
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• 2000

Investigated via a series of finite element process simulation is the effect of diverse process variables on some selected non-dimensional parameters characterizing the strip in hot strip rolling. Then on the basis of these parameters an on-line model is derived for the precise prediction of roll and roll power. The prediction accuracy of the proposed model is examined through comparison with predictions from a finite element process model.