eBook - Simulation and Analysis of Mathematical Methods in Real-Time Engineering Applications

  • ISBN: 9789373323787
  • 368 pages

Available Exclusively as an eBook | Part of the AI eBook Collection | Only for Institutional Purchase | Publication Year: 2021

Description

This volume covers the state-of-the-art real-time applications of computer science using advanced mathematical methods. It focuses on security, privacy, AI, machine learning, and soft computing techniques in engineering and technology fields. Suitable for researchers, academicians, and students, it serves as a comprehensive reference and practical guide for advancing science and engineering applications.

About the Author

T. Ananth Kumar is an assistant professor at the IFET College of Engineering, Anna University, Chennai.

Table of Contents

1 Certain Investigations on Different Mathematical Models in Machine Learning and Artificial Intelligence

2 Edge Computing Optimization Using Mathematical Modeling, Deep Learning Models, and Evolutionary Algorithms

3 Mathematical Modelling of Cryptographic Approaches in Cloud Computing Scenario

4 An Exploration of Networking and Communication Methodologies for Security and Privacy Preservation in Edge Computing

5 Nature Inspired Algorithm for Placing Sensors in Structural Health Monitoring System - Mouth Brooding Fish

6 Heat Source/Sink Effects on Convective Flow of a Newtonian Fluid Past an Inclined Vertical Plate in Conducting

7 Application of Fuzzy Differential Equations in Digital Images Via Fixed Point

8 The Convergence of Novel Deep Learning Approaches in Cybersecurity and Digital Forensics

9 Mathematical Models for Computer Vision in Cardiovascular Image Segmentation

10 Modeling of Diabetic Retinopathy Grading Using Deep Learning

11 Novel Deep-Learning Approaches for Future Computing Applications and Services

12 Effects of Radiation Absorption and Aligned Magnetic Field on MHD Cassion Fluid Past an Inclined Vertical Porous Plate in Porous Media

13 Integrated Mathematical Modelling and Analysis of Paddy Crop Pest Detection Framework Using Convolutional Classifiers

14 A Novel Machine Learning Approach in Edge Analytics with Mathematical Modeling for IoT Test Optimization

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