rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Computational intelligence-based time series analysis
  name:
    name part: Bisht, Dinesh C. S.
    role:
      role term: editor.
  name:
    name part: Ram, Mangey
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: 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 too difficult to model mathematically. This book aims to cover the recent advances in time series and applications of CI for time series analysis.
  table of contents: Preface xi List of Figures xiii List of Tables xix List of Contributors xxi List of Abbreviations xxv 1 On Dimensionless Dissimilarity Measures for Time Series 1 1.1 Introduction 1 1.2 Classical Dissimilarity Measures 3 1.3 Classical Entropy-type Dissimilarity Measures 4 1.4 Dissimilarity Measures for Time Series Data 5 1.4.1 Standard Dissimilarity Measures 6 1.4.2 Advanced Dissimilarity Measures 12 1.5 Conclusions 15 2 The Classification Analysis of Variability of Time Series of Different Origin 19 2.1 Introduction 20 2.2 Used Datasets and Methods of Analysis 21 2.3 Results and Discussions 25 2.4 Summary 33 3 A Comparative Study of CNN Architectures for Remaining Useful Life Estimation 37 3.1 Introduction 38 3.2 CNN Architectures and Hyperparameters 40 3.3 Numerical Experiments 42 3.3.1 Dataset 42 3.3.2 Pre-processing 43 3.3.2.1 Labelling 44 3.3.2.2 Scaling of data 44 3.3.2.3 Splitting of data 44 3.3.2.4 Time series to recurrence plots 45 3.4 Results 46 3.5 Conclusion 47 4 The Analysis of Dynamical Changes and Local Seismic Activity of the Enguri Arch Dam 53 4.1 Introduction 54 4.2 Main Text 56 4.2.1 Methods and Results 56 4.3 Conclusion 61 5 Analysis and Prediction of Daily Closing Price of Commodity Index Using Auto Regressive Integrated Moving Averages 65 5.1 Introduction 66 5.2 Literature Review 67 5.3 Objectives and Study 69 5.4 Data and Methodology 69 5.5 Data Decomposition 69 5.5.1 Seasonality 69 5.5.2 Trend 69 5.5.3 Cyclicity 70 5.6 Augmented Dicky Fuller (ADF) Test 70 5.6.1 Auto-correlation function (ACF) 71 5.6.2 Partial Autocorrelation Function (PACF) 73 5.6.3 ARIMA Model 73 5.7 Results and Analysis 74 5.8 Conclusion and Future Work 77 6 Neural Networks Analysis of Suspended Sediment Transport Time Series Modeling in a River System 81 6.1 Introduction 82 6.2 Artificial Neural Networks 83 6.3 Hydrological Study Area 85 6.4 Methodology 87 6.4.1 Mathematics of SRC 89 6.5 Results 89 6.6 Hysteresis of Sediment Transport Process 93 6.7 Conclusions 94 6.8 Ackno…
  note: editors, Dinesh C.S. Bisht, Mangey Ram.
  note: Dr Dinesh C. S. Bisht received his PhD with a major in Mathematics and a minor in Electronics and Communication Engineering from G. B. Pant University of Agriculture and Technology, Uttarakhand, India. Before joining the Jaypee Institute of Information Technology he worked as an assistant professor at ITM University, Gurgaon, India. He has been a Faculty Member for around eleven years and has taught several core courses in applied mathematics and soft computing at undergraduate and master levels. His major research interests include soft computing and nature inspired optimization. He has published more than 38 research papers in national and international journals of repute. He is the Associate Editor for International Journal of Mathematical, Engineering and Management Sciences, ESCI and SCOPUS indexed journals. He is the editor of the book Computational Intelligence: Theoretical Advances and Advanced Applications published by Walter de Gruyter GmbH & Co KG. He has also published seven book chapters in reputed book series. Dr Bisht is a member of the International Association of Engineers in Hong Kong and Soft Computing Research Society, India. He has been awarded for outstanding contributions in reviewing by the editors of Applied Soft Computing Journal, Elsevier. Professor (Dr) Mangey Ram received his PhD with a major in Mathematics and minor in Computer Science from G. B. Pant University of Agriculture and Technology, Pantnagar, India. He has been a Faculty Member for around twelve years and has taught several core courses in pure and applied mathematics at undergraduate, postgraduate, and doctorate levels. He is currently the Research Professor at Graphic Era (Deemed to be University), Dehradun, India. Before joining Graphic Era, he was a Deputy Manager (Probationary Officer) with the Syndicate Bank for a short period. He is Editor-in-Chief of International Journal of Mathematical, Engineering and Management Sciences, Journal of Reliability and Statistical Stud…
  subject:
    topic: Computational intelligence
  subject:
    topic: Time-series analysis
  subject:
    topic: Intelligence informatique
  subject:
    topic: Série chronologique
  subject:
    topic: SCIENCE / Energy
  subject:
    topic: TECHNOLOGY / Electricity
  subject:
    topic: Computational intelligence
  subject:
    topic: Time-series analysis
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: COMPUTATIONAL INTELLIGENCE-BASED TIME SERIES ANALYSIS
    origin info:
      publisher: [Place of publication not identified] : RIVER PUBLISHERS, 2022
    identifier: (OCoLC)1284288772
  related item:
    title info:
      title: River Publishers series in automation, control and robotics
  identifier: 9788770224161
  identifier: 8770224161
  identifier: 9781003337676
  identifier: 1003337678
  identifier: 9781000793819
  identifier: 1000793818
  identifier: 1000796973
  identifier: 9781000796971
  identifier: 877022417X
  identifier: 9788770224178
  identifier: 9796065 IEEE
  identifier: 9781003337676 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: IEEEE
    record creation date: 220701
    record change date: 20241108165930.9
    record identifier: in00005524991
    language of cataloging:
      language term: eng