• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.181-189
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• 1993

Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.

• Journal of the FoodService Safety
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• v.2 no.2
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• pp.91-96
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• 2021

This study was performed to provide fundamental data on hygiene and quality control of ready-to-eat sandwiches. Predictive models were developed to the kinetics of Staphylococcus aureus growth in these sandwiches as a function of temperature (10, 15, 25, and 35℃). The result of the primary model that used the Gompertz equation showed that the lag phase duration (LPD) and generation time (GT) decreased and the exponential growth rate (EGR) increased with increasing storage temperature. The secondary model showed an R² for M and B of 0.9967 and 09916, respectively. A predictive growth model of the growth degree as a function of temperature was developed. L(t)=A+Cexp(-exp(-B(t-M))) (A=Initial contamination level, C=MPD-A, B=0.473166-0.045040*Temp-0.001718*Temp*Temp, M=19.924824-0.627442*Temp-0.004493*Temp*Temp, t=time, Temp=temperature). This model showed an R² value of 0.9288. All the models developed in this study showed a good fit.

• Environmental and Resource Economics Review
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• v.26 no.3
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• pp.287-317
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• 2017

Asbestos has been actively used for various places. Since it was designated as the first grade carcinogen in the 1970s, strict regulations on using asbestos has been implemented globally. Considering long-term latent periods between asbestos exposure and environmental diseases, we analyze the time lag between asbestos consumption and the incidence of mesothelioma in Korea and estimate the long-run relationship. In addition, we conduct a comparative analysis on the effectiveness of asbestos regulations in the United Kingdom and the United States, which have accumulated long-term time-series observations. The latent period analysis indicates that the consumption of asbestos and the incidence of the disease are highly correlated in all three countries, being long-term lags of more than 30 years. Also, we find a long-run equilibrium relationship between asbestos consumption and the incidence of mesothelioma in the presence of long-term lags between the variables in all three countries. Furthermore, using a distributed lag model, asbestos consumption has statistically significant positive effects on mesothelioma with a long-term lag.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.3
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• pp.67-73
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• 1994

This paper is to validate the proposed models for the real-time forecasting for the Keum river estuary dam such as tidal-level forecasting model, one-dimensional unsteady flood routing model, and Kalman filter models. The tidal-level forecasting model was based on semi-range and phase lag of four tidal constituents. The dynamic wave routing model was based on an implicit finite difference solution of the complete one-dimensional St. Venant equations of unsteady flow. The Kalman filter model was composed of a processing equation and adaptive filtering algorithm. The processng equations are second ordpr autoregressive model and autoregressive moving average model. Simulated results of the models were compared with field data and were reviewed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.90-96
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• 2018

This paper proposed data driven techniques to forecast the time point of water management of the water reservoir without measuring manganese concentration with the empirical data as Juam Dam of years of 2015 and 2016. When the manganese concentration near the surface of water goes over the criteria of 0.3mg/l, the water management should be taken. But, it is economically inefficient to measure manganese concentration frequently and regularly. The water turnover by the difference of water temperature make manganese on the floor of water reservoir rise up to surface and increase the manganese concentration near the surface. Manganese concentration and water temperature from the surface to depth of 20m by 5m have been time plotted and exploratory analyzed to show that the water turnover could be used instead of measuring manganese concentration to know the time point of water management. Two models for forecasting the time point of water turnover were proposed and compared as follow: The regression model of CR20, the consistency ratio of water temperature, between the surface and the depth of 20m on the lagged variables of CR20 and the first lag variable of max temperature. And, the Box-Jenkins model of CR20 as ARIMA (2, 1, 2).

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.5
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• pp.641-644
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• 2000

In vitro true digestibility of cup-plant (Silphium perfoliatum L.) is higher than other alternative forages and comparative to alfalfa (Medicago sativa L.) even at the high neutral detergent fiber (NDF) concentration. This study was conducted to determine whether the digestion kinetic parameters of cup-plant could explain high in vitro true digestibility of cup-plant at the several NDF levels. Cup-plant and alfalfa were both collected in Arlington and Lancaster, Wisconsin to meet the NDF content within 40 to 50% range. The collected samples were incubated with rumen juice to investigate the digestion kinetics at 3, 6, 9, 14, 20, 28, 36, 48, and 72 h. Kinetics was estimated by the model $R=D_0\;e-k(t-L)+U$ where R is residue remaining at time t, and $D_0$ is digestible fraction, k is digestion rate constant, L is discrete lag time, and U is indigestible fraction. Parameters of the model were estimated by the direct nonlinear least squares (DNLS) method. Digestion rate and potential extent of digestion were not statistically different in either forage. However, alfalfa had shorter lag time (p<0.05). The indigestible fraction increased with maturation in alfalfa and in cup-plant (p<0.05). The ratio of indigestible fraction to acid detergent lignin (ADL) was higher in cup-plant than in alfalfa (p<0.05). From the results, alfalfa is probably digested more rapidly than cup-plant, however, cup-plant maintains higher digestibility with maturation due to a relatively slower increase of indigestible fraction in NDF.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.187-198
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• 2008

There are usually plenty of material inventories in a construction site. More inventories can meet unexpected demands, and also they may have an economical advantage by avoiding a probable escalation of raw material costs. On the other hand, these inventories also cause negative aspects to increase costs for storing redundant inventory as well as decreasing construction productivity. Therefore, a proper method of deciding an optimal level of material inventories while considering dynamic variations of resources under uncertainty is very crucial for the economical efficiency of construction projects. This research presents a stochastic modelling method for construction operations, particularly targeting a work process involving on-site fabrication of raw materials like iron-rebar process (delivery, cut and assembly, and placement). To develop the model, we apply the concept of factory physics to depict the overall components of a system. Then, an optimal inventory management model is devised to support purchase decisions where users can make timely actions on how much to order and when to buy raw materials. Also, optimal time lag, which minimizes the storage time for pre-assembled materials, is obtained. To verify this method, a real case is applied to elicit an optimal amount of inventory and time lag. It is found that average values as well as variability of inventory level decreased significantly so as to minimize economic costs related to inventory management under uncertain project condition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.49-57
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• 2020

The forced vibration characteristics for two impulse forces with time lag was discussed in the vehicle dull progress model. Detailed numerical analyses of the time domain were performed systematically. By the two exciting impulse forces, the responses of displacement, the velocity, and the acceleration were investigated in detail for the vehicle's vibration. Notably, the forced vibration responses in the time domain can be used to identify and monitor several vehicle vibration models. In order to define the responses of displacement, the velocity, and the acceleration, we applied a numerical technique (i.e., the Runge-Kutta-Gill method[1,2]). These variables were subsequently used to analyze the vehicle's vibration according to the time lapse and while it passed over a bump stock; moreover, the characteristics of the variables were analyzed in detail according to their force conditions. Finally, the intrinsic characteristics of the forced vibration were discussed in the context of the automobile model. Overall, our results indicate that the tested method can be successfully applied under different damped conditions.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.642-646
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• 1992

Trajectory tracking control problems are described for a two-link robot manipulator with artificial rubber muscle actuators. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with time-lag by the step response. Two control laws such as the feedforward and the computed torque control methods, are experimentally applied for controlling the circular trajectory of an actual robot manipulator.