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Cyber-Physical Systems: Intelligent Models and Algorithms

  • Book
  • © 2022

Overview

Editors:
  1. Alla G. Kravets

    1. r.B-1406, Volgograd State Technical University, Volgograd, Russia

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  2. Alexander A. Bolshakov

    1. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

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  3. Maxim Shcherbakov

    1. Apt 8, Volgograd State Technical University, Volgograd, Russia

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  • Defines the activities in the modelling technologies field leverage the exploitation of artificial intelligence
  • Describes fuzzy models and algorithms as well as implementation of these technologies in the different domains
  • Includes the development of predicting models, considering the increasing complexity of the business processes

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 417)

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About this book

This book is devoted to intelligent models and algorithms as the core components of cyber-physical systems. The complexity of cyber-physical systems developing and deploying requires new approaches to its modelling and design. Presents results in the field of modelling technologies that leverage the exploitation of artificial intelligence, including artificial general intelligence (AGI) and weak artificial intelligence. Provides scientific, practical, and methodological approaches based on bio-inspired methods,  fuzzy models and algorithms, predictive modelling, computer vision and image processing. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research or applications of intelligent models and algorithms in cyber-physical systems for various domains.

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Table of contents (22 chapters)

  1. Front Matter

    Pages i-ix
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  2. Bio-inspired Modelling

    1. Front Matter

      Pages 1-1
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    2. An Extension of the Neural Additive Model for Uncertainty Explanation of Machine Learning Survival Models

      • Lev Utkin, Andrei Konstantinov
      Pages 3-13

    3. Biocomputation Using Molecular Agents Moving in Microfluidic Channel Networks: An Alternative Platform for Information Technology

      • Thomas Blaudeck, Christoph R. Meinecke, Danny Reuter, Sönke Steenhusen, Archa Jain, Sascha Hermann et al.
      Pages 15-27

    4. Artificial Immune Systems—Models and Applications

      • Yuriy Skobtsov
      Pages 29-42

    5. The Analysis of Technology Development Trends Based on the Network Semantic Structure “Subject-Action-Object”

      • Veronika Kolesnikova, Dmitriy Korobkin, Sergey Fomenkov, Eduard Rayushkin, Vsevolod Glushkin
      Pages 43-53

    6. Machine Learning of Diagnostic Neural Network for Railway Track Monitoring

      • Sergey Orlov, Antonina Piletskaya, Nadezhda Kusakina, Andrey Tyugashev
      Pages 55-65

    7. Neural Network Analysis of Electromagnetic Field Effect on the Thermofluctuation Characteristics Measurement in the Power Cable Insulating Materials

      • N. K. Poluyanovich, M. N. Dubyago, N. V. Azarov, A. V. Ogrenichev
      Pages 67-80

  3. Fuzzy Models and Algorithms

    1. Front Matter

      Pages 81-81
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    2. Algorithm for Configuring Sugeno-Type Fuzzy Inference Systems Based on the Nearest Neighbor Method for Use in Cyber-Physical Systems

      • Mikhail Golosovskiy, Alexey Bogomolov, Mikhail Balandov
      Pages 83-97

    3. Construction of Membership Functions for Fuzzy Management of Security Information and Events

      • Igor Kotenko, Igor Parashchuk
      Pages 99-110

    4. Building a Fuzzy Model to Automate the Search for Product Names in Procurement Documentation for a Shipbuilding Plant

      • Lilia Emaletdinova, Aigul Kabirova, Ivan Kulagin
      Pages 111-119

    5. Synthesis of a Neuro-Fuzzy Model in the Structure of an Automatic Rolling Stock Control System

      • Konstantin Yurenko, Pavel Kharchenko, Evgeniy Fandeev, Ivan Yurenko
      Pages 121-132

  4. Predictive Modelling

    1. Front Matter

      Pages 133-133
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    2. Predicting the Equipment Useful Lifetime Based on the Deep Neural Networks

      • Maxim Dli, Andrey Puchkov, Ekaterina Lobaneva
      Pages 135-144

    3. Operational Model Predictive Control on the Example of the Stabilization Process for Hydro Treatment of Oil Fractions

      • I. V. Gogol, N. A. Kalashnikov, O. A. Remizova, V. V. Syrokvashin, A. L. Fokin
      Pages 145-156

    4. The Models for Predictive Maintenance of Robotic Agricultural Vehicles

      • Sergey Susarev, Sergey Orlov, Elizaveta Bizyukova, Roman Uchaikin
      Pages 157-168

    5. Development of a Cyber-Physical System for Neurofuzzy Prediction of the Concentration of the Contained Prime During Transportation of Oil Wells Emulsion

      • Artur Sagdatullin, Gennady Degtyarev
      Pages 169-180

    6. Non-life Insurance Reserve Prediction Using LightGBM Classification and Regression Models Ensemble

      • Vladimir Soloviev, Vadim Feklin
      Pages 181-188

    7. Machine Learning-Based Cyber-Physical Systems for Forecasting Short-Term State of Unstable Systems

      • Alexander Musaev, Dmitry Grigoriev
      Pages 189-200
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Editors and Affiliations

  • r.B-1406, Volgograd State Technical University, Volgograd, Russia

    Alla G. Kravets

  • Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Alexander A. Bolshakov

  • Apt 8, Volgograd State Technical University, Volgograd, Russia

    Maxim Shcherbakov

Bibliographic Information

  • Book Title: Cyber-Physical Systems: Intelligent Models and Algorithms

  • Editors: Alla G. Kravets, Alexander A. Bolshakov, Maxim Shcherbakov

  • Series Title: Studies in Systems, Decision and Control

  • DOI: https://doi.org/10.1007/978-3-030-95116-0

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Hardcover ISBN: 978-3-030-95115-3Published: 29 March 2022

  • Softcover ISBN: 978-3-030-95118-4Published: 30 March 2023

  • eBook ISBN: 978-3-030-95116-0Published: 29 March 2022

  • Series ISSN: 2198-4182

  • Series E-ISSN: 2198-4190

  • Edition Number: 1

  • Number of Pages: IX, 279

  • Number of Illustrations: 51 b/w illustrations, 60 illustrations in colour

  • Topics: Cyber-physical systems, IoT, Computational Intelligence, Data Engineering

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