Coverart for item
The Resource Practical issues of intelligent innovations, Vassil Sgurev, Vladimir Jotsov, Janusz Kacprzyk, editors

Practical issues of intelligent innovations, Vassil Sgurev, Vladimir Jotsov, Janusz Kacprzyk, editors

Label
Practical issues of intelligent innovations
Title
Practical issues of intelligent innovations
Statement of responsibility
Vassil Sgurev, Vladimir Jotsov, Janusz Kacprzyk, editors
Contributor
Editor
Subject
Language
eng
Summary
This book presents recent advances in the field of intelligent systems. Composed of fourteen selected chapters, it covers a wide range of research that varies from applications in industrial data science to those in applied science. Today the word INNOVATION is more and more connected with the words INTELLIGENT and SECURITY, as such the book discusses the theory and applications of hot topics such as big data, education applications of robots with different levels of autonomy, knowledge-based modeling and control of complex dynamical systems, sign-based synthesis of behavior, security issues with intelligent systems, innovative intelligent control design, neuromorphic computation, data-driven classification, intelligent modeling and measurement innovations, multisensor data association, personal education assistants, a modern production architecture, study of peer review and scientometrics, intelligent research on bug report data, and clustering non-Gaussian data. The broad and varied research discussed represents the mainstream of contemporary intelligent innovations that are slowly but surely changing the world
Member of
Cataloging source
N$T
Dewey number
006.3
Illustrations
illustrations
Index
no index present
LC call number
Q342
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Sgurev, Vasil
  • Jotsov, Vladimir
  • Kacprzyk, Janusz
Series statement
Studies in systems, decision and control
Series volume
volume 140
http://library.link/vocab/subjectName
  • Computational intelligence
  • Intelligent control systems
  • Expert systems (Computer science)
  • Artificial intelligence
  • Engineering
  • Computational Intelligence
  • Artificial Intelligence (incl. Robotics)
  • Robotics and Automation
Label
Practical issues of intelligent innovations, Vassil Sgurev, Vladimir Jotsov, Janusz Kacprzyk, editors
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Contents; Non-conventional Control Design by Sigmoid Generated Fixed Point Transformation Using Fuzzy Approximation; 1 Introduction; 2 Combination of Fuzzy Modeling and Sigmoid Generated Fixed Point Transformation; 2.1 The Concept of Sigmoid Generated Fixed Point Transformation; 2.2 Application Example: Adaptive Control of the Inverted Pendulum; 2.3 Realization of the Proposed Method; 3 Simulation Investigations; 3.1 Performance Using the Affine Model; 3.2 Performance Using the Soft Computing-Based Model; 3.3 Performance Using the Fully Soft Computing-Based Model
  • 4 ConclusionsReferences; 2 From von Neumann Architecture and Atanasoff's ABC to Neuromorphic Computation and Kasabov's NeuCube. Part II: Applications; Abstract; 1 Introduction; 2 Application of NeuCube in Brain Data Modelling; 3 NeuCube and Brain Computer Interfaces (BCI) with Neurofeedback for Neurorehabilitation; 4 NeuCube Personalized Modelling in Neuroinformatics and Bio-informatics; 5 Risk of Stroke Prediction; 6 Predicting and Understanding Response to Treatment in Biomedical Environment: A Case Study of Clozapine Monotherapy; 7 Seismic Data Modelling for Earthquake Prediction
  • 8 NeuCube Spatio-Temporal Pattern Recognition from Satellite Images Remote Sensing9 Conclusions; Acknowledgements; References; Data-Driven Interval Type-2 Fuzzy Modelling for the Classification of Imbalanced Data; 1 Introduction; 2 Overview of the Rail Production Data; 2.1 Rail Manufacturing Data; 3 Data-Driven Fuzzy Modelling (DDFM); 3.1 Fast Correlation-Based Filter (FCBF) for Feature Selection; 3.2 Iterative Information Granulation; 3.3 Bootstrapping; 3.4 Parameter Identification of the NFM via the Application of an Oversampling Bootstrapping; 4 Simulation Results; 5 Conclusion
  • 3 Correcting the Error Due to Drift of a TC CC4 The Method for Improving the Accuracy of Temperature Measurements Using Thermocouples with Inhomogeneous Legs; 5 The Furnace to Control the Temperature Field Profile Control of the TCPTF; 6 Computation of the Furnace Heaters' Power; 7 Computation of the Parameters of the TCPTF Heaters; 8 Controlling the Temperature Field of the TCPTF with a System of Linear Equations; 9 Using a Neural Network for Temperature Field Profile Control; 10 Essential Features of Proposed Puzzle Methods; 10.1 Different Types of Binding Constraints
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319784373
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
  • 10.1007/978-3-319-78437-3
  • 9783319784366
Other physical details
illustrations.
http://library.link/vocab/ext/overdrive/overdriveId
9783319784366
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1043830981
  • (OCoLC)1043830981
Label
Practical issues of intelligent innovations, Vassil Sgurev, Vladimir Jotsov, Janusz Kacprzyk, editors
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Contents; Non-conventional Control Design by Sigmoid Generated Fixed Point Transformation Using Fuzzy Approximation; 1 Introduction; 2 Combination of Fuzzy Modeling and Sigmoid Generated Fixed Point Transformation; 2.1 The Concept of Sigmoid Generated Fixed Point Transformation; 2.2 Application Example: Adaptive Control of the Inverted Pendulum; 2.3 Realization of the Proposed Method; 3 Simulation Investigations; 3.1 Performance Using the Affine Model; 3.2 Performance Using the Soft Computing-Based Model; 3.3 Performance Using the Fully Soft Computing-Based Model
  • 4 ConclusionsReferences; 2 From von Neumann Architecture and Atanasoff's ABC to Neuromorphic Computation and Kasabov's NeuCube. Part II: Applications; Abstract; 1 Introduction; 2 Application of NeuCube in Brain Data Modelling; 3 NeuCube and Brain Computer Interfaces (BCI) with Neurofeedback for Neurorehabilitation; 4 NeuCube Personalized Modelling in Neuroinformatics and Bio-informatics; 5 Risk of Stroke Prediction; 6 Predicting and Understanding Response to Treatment in Biomedical Environment: A Case Study of Clozapine Monotherapy; 7 Seismic Data Modelling for Earthquake Prediction
  • 8 NeuCube Spatio-Temporal Pattern Recognition from Satellite Images Remote Sensing9 Conclusions; Acknowledgements; References; Data-Driven Interval Type-2 Fuzzy Modelling for the Classification of Imbalanced Data; 1 Introduction; 2 Overview of the Rail Production Data; 2.1 Rail Manufacturing Data; 3 Data-Driven Fuzzy Modelling (DDFM); 3.1 Fast Correlation-Based Filter (FCBF) for Feature Selection; 3.2 Iterative Information Granulation; 3.3 Bootstrapping; 3.4 Parameter Identification of the NFM via the Application of an Oversampling Bootstrapping; 4 Simulation Results; 5 Conclusion
  • 3 Correcting the Error Due to Drift of a TC CC4 The Method for Improving the Accuracy of Temperature Measurements Using Thermocouples with Inhomogeneous Legs; 5 The Furnace to Control the Temperature Field Profile Control of the TCPTF; 6 Computation of the Furnace Heaters' Power; 7 Computation of the Parameters of the TCPTF Heaters; 8 Controlling the Temperature Field of the TCPTF with a System of Linear Equations; 9 Using a Neural Network for Temperature Field Profile Control; 10 Essential Features of Proposed Puzzle Methods; 10.1 Different Types of Binding Constraints
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319784373
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
  • 10.1007/978-3-319-78437-3
  • 9783319784366
Other physical details
illustrations.
http://library.link/vocab/ext/overdrive/overdriveId
9783319784366
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1043830981
  • (OCoLC)1043830981

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