New Paradigms in Computational Modeling and Its Applications

New Paradigms in Computational Modeling and Its Applications

by Snehashish Chakraverty
Released January 2021
Publisher(s): Academic Press
ISBN: 9780128221686

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Book description

In general, every problem of science and engineering is governed by mathematical models. There is often a need to model, solve and interpret the problems one encounters in the world of practical problems. Models of practical application problems usually need to be handled by efficient computational models.

New Paradigms in Computational Modeling and Its Applications deals with recent developments in mathematical methods, including theoretical models as well as applied science and engineering. The book focuses on subjects that can benefit from mathematical methods with concepts of simulation, waves, dynamics, uncertainty, machine intelligence, and applied mathematics. The authors bring together leading-edge research on mathematics combining various fields of science and engineering. This perspective acknowledges the inherent characteristic of current research on mathematics operating in parallel over different subject fields.

New Paradigms in Computational Modeling and Its Applications meets the present and future needs for the interaction between various science and technology/engineering areas on the one hand and different branches of mathematics on the other. As such, the book contains 13 chapters covering various aspects of computational modeling from theoretical to application problems. The first six chapters address various problems of structural and fluid dynamics.

The next four chapters include solving problems where the governing parameters are uncertain regarding fuzzy, interval, and affine. The final three chapters will be devoted to the use of machine intelligence in artificial neural networks.

  • Presents a self-contained and up to date review of modelling real life scientific and engineering application problems
  • Introduces new concepts of various computing techniques to handle different engineering and science problems
  • Demonstrates the efficiency and power of the various algorithms and models in a simple and easy to follow style, including numerous examples to illustrate concepts and algorithms

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Preface
  7. Chapter 1: Nanostructural dynamics problems with complicating effects
    1. Abstract
    2. Acknowledgment
    3. 1.1: Introduction
    4. 1.2: Proposed model
    5. 1.3: Solution procedure
    6. 1.4: Results and discussion
    7. 1.5: Conclusion
  8. Chapter 2: Vibration of functionally graded piezoelectric material beams
    1. Abstract
    2. Acknowledgments
    3. Chapter points
    4. 2.1: Introduction
    5. 2.2: Functionally graded piezoelectric beam
    6. 2.3: Constitutive relation
    7. 2.4: Mathematical formulation
    8. 2.5: Numerical results
    9. 2.6: Conclusions
  9. Chapter 3: Vibration of microstructural elements
    1. Abstract
    2. Acknowledgment
    3. 3.1: Introduction
    4. 3.2: Formulation of proposed model
    5. 3.3: Analytical solution to the proposed model
    6. 3.4: Results and discussion
    7. 3.5: Concluding remarks
  10. Chapter 4: Coupled shallow water wave equations
    1. Abstract
    2. 4.1: Introduction
    3. 4.2: Homotopy perturbation transform method
    4. 4.3: Solution of CSWWE using HPTM
    5. 4.4: Conclusion
  11. Chapter 5: Natural convection in a nanofluid flow
    1. Abstract
    2. Acknowledgment
    3. 5.1: Introduction
    4. 5.2: Problem formulation
    5. 5.3: Galerkin’s method [13–15]
    6. 5.4: Implementation of Galerkin’s method
    7. 5.5: Results and discussions
    8. 5.6: Conclusion
  12. Chapter 6: Fractional fluid mechanics systems
    1. Abstract
    2. Acknowledgment
    3. 6.1: Outline and motivations
    4. 6.2: Preliminaries
    5. 6.3: Implementation of HPZZTM
    6. 6.4: Applications of HPZZTM
    7. 6.5: Conclusion
  13. Chapter 7: Inverse problems in diffusion processes with uncertain parameters
    1. Abstract
    2. 7.1: Introduction
    3. 7.2: Preliminaries
    4. 7.3: Fuzzy inverse iteration method
    5. 7.4: Estimating fuzzy parameters of diffusion problem by FIIM
    6. 7.5: Results and discussions
    7. 7.6: Conclusion
  14. Chapter 8: Affine approach in solving linear structural dynamic problems with uncertain parameters
    1. Abstract
    2. 8.1: Introduction
    3. 8.2: Preliminaries
    4. 8.3: Affine arithmetic
    5. 8.4: Proposed methodology
    6. 8.5: Numerical examples
    7. 8.6: Conclusion
  15. Chapter 9: Numerical solution of Langevin stochastic differential equation with uncertain parameters
    1. Abstract
    2. 9.1: Introduction
    3. 9.2: Preliminaries
    4. 9.3: Numerical solution of SDEs
    5. 9.4: Fuzzy arithmetic
    6. 9.5: The solution of FSDE
    7. 9.6: Example problem
    8. 9.7: Conclusions
  16. Chapter 10: Fuzzy eigenvalue problems of structural dynamics using ANN
    1. Abstract
    2. 10.1: Introduction
    3. 10.2: Fuzzy eigenvalue problem
    4. 10.3: ANN procedure
    5. 10.4: Examples related to fuzzy eigenvalue problem
    6. 10.5: Conclusion
  17. Chapter 11: Artificial neural network approach for solving fractional order applied problems
    1. Abstract
    2. 11.1: Artificial neural network
    3. 11.2: Overview of fractional differential calculus
    4. 11.3: General ANN formulation for FDEs
    5. 11.4: Single-layer Chebyshev neural network model for FDEs
    6. 11.5: Numerical examples and results
    7. 11.6: Conclusion
  18. Chapter 12: Speech emotion recognition using deep learning
    1. Abstract
    2. 12.1: Introduction
    3. 12.2: Proposed model
    4. 12.3: Experiment and results
    5. 12.4: Conclusion
  19. Chapter 13: A user independent hand gesture recognition system using deep CNN feature fusion and machine learning technique
    1. Abstract
    2. Acknowledgments
    3. 13.1: Introduction
    4. 13.2: Related works
    5. 13.3: Benchmark datasets
    6. 13.4: Theoretical backgrounds
    7. 13.5: Methodology
    8. 13.6: Experimental evaluation and results
    9. 13.7: Conclusions
  20. Chapter 14: A survey on group modeling strategies for recommender systems
    1. Abstract
    2. 14.1: Introduction
    3. 14.2: Group modeling strategies
    4. 14.3: Comparative study on group modeling strategies for recommender systems
    5. 14.4: Conclusion
  21. Chapter 15: Extraction of glacial lakes in the Himalayan region using landsat imagery
    1. Abstract
    2. 15.1: Introduction
    3. 15.2: Proposed framework
    4. 15.3: Experimental results
    5. 15.4: Conclusion
  22. Index

Product information

  • Title: New Paradigms in Computational Modeling and Its Applications
  • Author(s): Snehashish Chakraverty
  • Release date: January 2021
  • Publisher(s): Academic Press
  • ISBN: 9780128221686