Segmentation and Clustering of Time Series Data

Abstract

Analyzing time series data had attracted a great deal of interest. To study the basic mechanisms, recognize and measure patterns, decide things, and forecast the upcoming, several ways have also been created to comprehend the insights from the data and get important statistics. The objective of both machine learning as well as representation is information extraction from data. To get the greatest out of equal people and computers, it would be ideal if effective machine learning algorithms (grouping and segmentation) could be integrated into communication platforms. This analysis is also helpful for forecasting electricity load and wind energy. This study aims to define the key ideas behind time series data clusters or classification methods.