Time series motifs are repeated segments in a long time series that, if exist, carry precise
information about the underlying source of the time series. Motif discovery in time series data …

Time series shapelets are a recent promising concept in time series data mining. Shapelets
are time series snippets that can be used to classify unlabeled time series. Shapelets not …

Time series shapelets are small, local patterns in a time series that are highly predictive of a
class and are thus very useful features for building classifiers and for certain visualization …

This chapter focuses on individual univariate time series sampled uniformly through time. It
describes the use of time-series features for tackling time-series forecasting. The chapter …

Time series analysis is a key technique for extracting and predicting events in domains as
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …

Multivariate time series (MTS) classification has gained importance with the increase in the
number of temporal datasets in different domains (such as medicine, finance, multimedia …

In recent years, dynamic time warping (DTW) has begun to become the most widely used
technique for comparison of time series data where extensive a priori knowledge is not …

In order to improve the prediction accuracy of chaotic time series, a prediction method based
on wavelet transform and multiple models fusion is proposed. The chaotic time series is …

Autonomous detection of desired events from large databases using time series
classification is becoming increasingly important in civil engineering as a result of continued …

All over the world, time series‐based anomaly prediction plays a vital role in all walks of life
such as medical monitoring in hospitals and climate and environment risks. In the present …