On-line respiratory artefact removal in rheopneumographic measurement via an adaptive moving average method

1993 ◽  
Vol 29 (10) ◽  
pp. 922-923 ◽  
Author(s):  
T.C. Choy ◽  
J. Ye
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Respiratory Artefact ◽  
On Line ◽  
Artefact Removal

scholarly journals Pemisahan Anomali Regional-Residual pada Metode Gravitasi Menggunakan Metode Moving Average, Polynomial dan Inversion

2016 ◽  
Vol 3 (01) ◽  
pp. 10 ◽  
Author(s):  
Jarot Purnomo ◽  
Sorja Koesuma ◽  
Mohtar Yunianto
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Continuation Method ◽  
Inversion Method ◽  
Polynomial Method ◽  
Minimum Error ◽  
Gravity Method ◽  
Upward Continuation ◽  
And Inversion ◽  
Separation Results

<span>It has been done a research about separation of regional-residual anomaly in Gravity method. <span>This research compares the result of three methods i.e. moving average method, polynomial <span>method, and inversion method. The computer program is created using a computer programming <span>Matlab 7. From three methods that have been made, the separation results are compared with<br /><span>results of separation by using Upward Continuation method. From the results of these <span>comparisons will be available an excellent program of regional-residual anomali separation. The <span>results show that in polynomial method of the order 4 obtained similar contour to the separation <span>by Upward Continuation Software. So that the output of this separation will be treated again <span>with Grav2DC software. The output of this software is the density of rock Grav2DC of the study<br /><span>area. Processing results obtained the minimum error of 1.85% for the separation by polynomial <span>method, while for the method of Upward Continuation obtained minimum error of 2.22%. The <span>results obtained show that the separation of regional-residual anomali by polynomial method is <span>similar to separation by Upward Continuation method.</span></span></span></span></span></span></span></span></span></span></span></span><br /></span>

scholarly journals Planning Production Capacity Using Time Series Forecasting Method and Linier Programming

2018 ◽  
Vol 7 (2) ◽  
pp. 20
Author(s):  
M. Tirtana Siregar ◽  
S. Pandiangan ◽  
Dian Anwar
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Demand Forecasting ◽  
Production Capacity ◽  
Mean Absolute Percentage Error ◽  
Programming Method ◽  
Percentage Error ◽  
Absolute Percentage Error ◽  
Forecasting Method ◽  
Planning Production

The objectives of this research is to determine the amount of production planning capacity sow talc products in the future utilizing previous data from january to december in year 2017. This researched considered three forecasting method, there are Weight Moving Average (WMA), Moving Average (MA), and Exponential Smoothing (ES). After calculating the methods, then measuring the error value using a control chart of 3 (three) of these methods. After find the best forecasting method, then do linear programming method to obtain the exact amount of production in further. Based on the data calculated, the method of Average Moving has a size of error value of Mean Absolute Percentage Error of 0.09 or 9%, Weight Moving Average has a size error of Mean Absolute Percentage Error of 0.09 or 9% and with Exponential Method Smoothing has an error value of Mean Absolute Percentage Error of 0.12 or 12%. Moving Average and Weight Moving Average have the same MAPE amount but Weight Moving Average has the smallest amount Mean Absolute Deviation compared to other method which is 262.497 kg. Based on the result, The Weight Moving Average method is the best method as reference for utilizing in demand forecasting next year, because it has the smallest error size and has a Tracking Signal&nbsp; not exceed the maximum or minimum control limit is &le; 4. Moreover, after obtained Weight Moving Average method is the best method, then is determine value of planning production capacity in next year using linier programming method. Based on the linier programming calculation, the maximum amount of production in next year by considering the forecasting of raw materials, production volume, material composition, and production time obtained in one (1) working day is 11,217,379 pcs / year, or 934,781 pcs / month of finished product. This paper recommends the company to evaluate the demand forecasting in order to achieve higher business growth.

scholarly journals Post-Exercise Assessment of Cardiac Repolarization Alternans in Patients With Coronary Artery Disease Using the Modified Moving Average Method

2009 ◽  
Vol 53 (13) ◽  
pp. 1130-1137 ◽  
Author(s):  
Michael P. Slawnych ◽  
Tuomo Nieminen ◽  
Mika Kähönen ◽  
Katherine M. Kavanagh ◽  
Terho Lehtimäki ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Average Method ◽  
Moving Average ◽  
Cardiac Repolarization ◽  
Post Exercise ◽  
Artery Disease
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