• Journal of Korean Society for Quality Management
• /
• v.35 no.1
• /
• pp.24-34
• /
• 2007

This paper investigates the average run length (ARL) of a selectively moving average (S-MA) control chart. The S-U chart is designed to detect shifts in the process mean. The basic idea of the S-MA chart is to accumulate previous samples selectively in order to increase the sensitivity. The ARL of the S-MA chart was shown to be monotone decreasing with respect to the decision length in a previous research [3]. This paper derives the steady-state ARL in a closed-form and shows that the monotone property is resulted from head-start assumption. The steady-state ARL is shown to be a sum of head-start ARL and an additional term. The statistical design procedure for the S-MA chart is revised according to this result. Sensitivity study shorts that the steady-state ARL performance is still better than the CUSUM chart or the Exponentially Weighted Moving Average (EWMA) chart.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.8 no.4
• /
• pp.170-181
• /
• 2009

When a slow-moving vehicle occupies one of the lanes of a multi-lane highway, it often causes queuing behind, unlike one is caused by an actual stoppage on that lane. This happens when the traffic flow rate upstream from the slow vehicle exceeds a certain critical value. This phenomena is called as the Moving Bottleneck, defined by Gazis and Herman (1992), Newell (1998) [3], and Munoz and Daganzo (2002), who conducted the flow estimates of upstream and downstream and considered slow-moving vehicle speed and the flow ratio exceeding slow vehicle and the microscopic traffic flow characteristics of moving bottleneck. But, a study of delay on moving bottleneck was not conducted until now. So this study provides a average delay time model related to upstream flow and the speed of slow vehicle. We have chosen the two-lane highway and homogeneous traffic flow. A slow-moving vehicle occupies one of the two lanes. Average delay time value is a result of AIMSUN[9], the microscopic traffic flow simulator. We developed a multiple regression model based on that value. Average delay time has a high value when the speed of slow vehicle is decreased and traffic flow is increased. Conclusively, the model is formulated by the negative exponential function.

• The Journal of Engineering Geology
• /
• v.17 no.4
• /
• pp.507-510
• /
• 2007

The correlation between groundwater level(GWL) and the moving average of precipitation was analyzed based on the observation data in Nakdong river watershed. The precipitation data was compared and analyzed with the GWL data from adjacent observation point to the precipitation gauge station. The correlation between the moving average of precipitation with several averaging periods and GWL were analyzed and we could choose the averaging period that produces maximum correlation. A severe drawdown was observed from December to April. The maximum correlations between GWL and the moving average of precipitation were occurred from 20-day to 80-day averaging period.

• Journal of Environmental Science International
• /
• v.30 no.7
• /
• pp.519-527
• /
• 2021

Moving average precipitation provides periodic precipitation patterns by solving precipitation irregularities. However, due to uncertain moving average periods, excessive data smoothing occurs, which limit the possibility to analyze groundwater levels in the short term. Nonetheless, groundwater level fluctuation can compensate these limitations as it can calculate appropriately for unit time and verify the effect of precipitation penetrated into groundwater in a short time period. In this study, the characteristics of groundwater level were evaluated using groundwater level fluctuation to compensate for limitations of groundwater level analysis using moving average precipitation. In addition, the groundwater quality was investigated using the electrical conductivity fluctuation. The study site was Hyogyo-ri, Yesan-si, Chungcheongnam-do. Four observation wells and an automated weather system were used. The correlation between groundwater level fluctuation and precipitation (Case 1) and the correlation between groundwater level and moving average precipitation (Case 3) were compared. In the analysis for 1 hour data, the correlation coefficient of Case 1 was higher than that of Case 3, and in the analysis for 1 day data, the correlation coefficient of Case 3 was higher than that of Case 1.

• Communications of the Korean Mathematical Society
• /
• v.12 no.3
• /
• pp.743-754
• /
• 1997

We introduce a class of finite and infinite moving average (MA) sequences of multivariate random vectors exponential marginals. The theory of dependence is used to show that in various cases the class of MA sequences consists of associated random variables. We utilize positive dependence properties to obtain some probability bounds for the multivariate processes.

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.507-518
• /
• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• Journal of the military operations research society of Korea
• /
• v.8 no.1
• /
• pp.99-107
• /
• 1982

This paper is concerned with the optimality of exponential smoothing applied to the general IMA process with different moving average and differencing orders. Numerical experiments were performed for IMA(m,n) process with various combinations of m and n, and the corresponding forecast errors were compared. Results show that the higher differencing order is more critical to the optimality of exponential smoothing, i.e., the IMA process with the higher moving average order, forecasted by exponential smoothing, has comparatively smaller forecast error. If the difference between the differencing order and the moving average order becomes larger, the accuracy of forecast by exponential smoothing declines gradually.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.7
• /
• pp.962-967
• /
• 2014

In this paper, through a digital potentiometer and exponentially weighted moving average filter, pulse and PPG waveform measurable device was fabricated in radial artery. If this device is not proper about signal size in analog part, MCU can judge easily by adjusted amplification through digital potentiometer, using exponentially weighted moving average filter is able to filter out more clear value of ADC. I presumed pulse rate as value of measuring time between point of maximum contraction from sensing signal in radial artery of wrist. Therefore, this means can measure stable pulse rate and PPG waveform, finger as well as radial artery, whether signal size of each person is different finger as well as radial artery.

• International Journal of Air-Conditioning and Refrigeration
• /
• v.11 no.3
• /
• pp.125-131
• /
• 2003

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this paper, two fault detection methods were considered. One is a generic neural network, and the other is an moving average neural network. In order to compare the performance of fault detection results from these methods, two different types of faults in an air-conditioning system were applied. These are the condenser 30% fouling and the evaporator fan 25% slowdown. Test results showed that the moving average neural network was more effective for the detection of partial faults in the air-conditioning system.

• Journal of Information Processing Systems
• /
• v.10 no.3
• /
• pp.429-442
• /
• 2014

In this paper, we investigated the use of seasonal autoregressive integrated moving average (SARIMA) time series models for fault detection in semiconductor etch equipment data. The derivative dynamic time warping algorithm was employed for the synchronization of data. The models were generated using a set of data from healthy runs, and the established models were compared with the experimental runs to find the faulty runs. It has been shown that the SARIMA modeling for this data can detect faults in the etch tool data from the semiconductor industry with an accuracy of 80% and 90% using the parameter-wise error computation and the step-wise error computation, respectively. We found that SARIMA is useful to detect incipient faults in semiconductor fabrication.