The sequential analysis of data and information gathered from past to
present is called time series analysis. Time series data are of high
dimension, large size and updated continuously. A time series depends on
various factors like trend, seasonality, cycle and irregular data set,
and is basically a series of data points well-organized in time. Time
series forecasting is a significant area of machine learning. There are
various prediction problems that are time-dependent and these problems
can be handled through time series analysis. Computational intelligence
(CI) is a developing computing approach for the forthcoming several
years. CI gives the litheness to model the problem according to given
requirements. It helps to find swift solutions to the problems arising
in numerous disciplines. These methods mimic human behavior. The main
objective of CI is to develop intelligent machines to provide solutions
to real world problems, which are not modelled or are too difficult to
model mathematically. This book aims to cover the recent advances in
time series and applications of CI for time series analysis.