Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.811
Moving Average is a known technique used in the analysis of time-series data. Quite commonly its used as a technique to smooth out spikes and highlight the trends over a longer period of time. This paper discusses a series of variants to standard moving average computation, which when used with time series data produce quite effective results and with considerable improvement to computational performance. The topic discussed here uses as 4 point moving average computation algorithm. The algorithm takes only the spikes in the data into consideration and eases out the effect of those spikes. The paper also discusses about a greedy technique with which smoothing can be much better.
Raveendran Vadakkoot, Mitul Devendra Shah, Suyashi Shrivastava, "Enhanced Moving Average Computation", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 541-544, doi:10.1109/CSIE.2009.811