Welcome to Journal of Network Communications and Emerging Technologies (JNCET)

Volume 12, Issue 3, March (2022)                               Cover Page and Table of Contents

S.No	Title & Authors	Full Text
1	Adaptive Window Size Selection in Piecewise Aggregate Approximation on Univariate Time-Series Data Dinesh R, Anitha A Abstract - Time series data need to represent to understand the data, reduce the dimensionality of the data and predict the future event. Many time series representation methods are available to present the time series. This research work took Piecewise Aggregate Approximation (PAA) for our research. PAA divides the time series into a number of the different and used aggregate function to reduce the dimensionality. The previous researchers used the window size of the PAA as a fixed value. It may lead to the wrong representation of the data. Our research suggested adaptive window size selection in piecewise aggregate approximation in time series representation. Our work is not with the PAA method but with adaptive window size selection of PAA. Our method first PAA and Simple Moving Average (SMA). Then do clustering analysis with Euclidean distance and cosine distance. Then choose adaptive PAA based on performance in similarity measures and processing time. The performance of the research work compared with different univariate time-series datasets.	Download