Computational Intelligence-based Time Series Analysis
eBook - ePub

Computational Intelligence-based Time Series Analysis

  1. 162 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Computational Intelligence-based Time Series Analysis

About this book

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.

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Yes, you can access Computational Intelligence-based Time Series Analysis by Dinesh C. S. Bisht,Mangey Ram in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half Title page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Preface
  8. List of Figures
  9. List of Tables
  10. List of Contributors
  11. List of Abbreviations
  12. 1 On Dimensionless Dissimilarity Measures for Time Series
  13. 2 The Classification Analysis of Variability of Time Series of Different Origin
  14. 3 A Comparative Study of CNN Architectures for Remaining Useful Life Estimation
  15. 4 The Analysis of Dynamical Changes and Local Seismic Activity of the Enguri Arch Dam
  16. 5 Analysis and Prediction of Daily Closing Price of Commodity Index Using Auto Regressive Integrated Moving Averages
  17. 6 Neural Networks Analysis of Suspended Sediment Transport Time Series Modeling in a River System
  18. 7 Ranking Forecasting Algorithms Using MCDM Methods: A Python Based Application
  19. 8 Rainfall Prediction Using Artificial Neural Network
  20. 9 Statistical Downscaling and Time Series Analysis for Future Scenarios of Temperature in Haridwar District, Uttarakhand
  21. Index
  22. About the Editors