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E-grāmata: Meta-Heuristic Algorithms for Advanced Distributed Systems

Edited by , Edited by (BMIET, India), Edited by , Edited by , Edited by (BMIET, India)
  • Formāts: EPUB+DRM
  • Izdošanas datums: 12-Mar-2024
  • Izdevniecība: John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781394188086
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Meta-Heuristic Algorithms for Advanced Distributed SystemsPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 12-Mar-2024
  • Izdevniecība: John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781394188086
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Discover a collection of meta-heuristic algorithms for distributed systems in different application domains

Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems—generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly.

Meta-Heuristic Algorithms for Advanced Distributed System offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable.

Meta-Heuristic Algorithms for Advanced Distributed System readers will also find:

  • Analysis of security issues, distributed system design, stochastic optimization techniques, and more
  • Detailed discussion of meta-heuristic techniques such as the genetic algorithm, particle swam optimization, and many others
  • Applications of optimized distribution systems in healthcare and other key industries

Meta-Heuristic Algorithms for Advanced Distributed System is ideal for academics and researchers studying distributed systems, their design, and their applications.

Chapter 1: The Future of Business Management with the Power of Distributed Systems and Computing

Chapter 2: Applications of Optimised Distributed Systems in Healthcare.

Chapter 3: The Impact of Distributed Computing on Data Analytics and Business Insights.

Chapter 4: MACHINE LEARNING AND ITS APPLICATION IN EDUCATIONAL AREA.

Chapter 5: Approaches and Methodologies for the Distributed Systems: Threats, Challenges, and Future Directions.

Chapter 6: Efficient driven approaches related to Meta-Heuristic Algorithms using Machine Learning Techniques.

Chapter 7: Security and Privacy issues in Distributed Healthcare system- A Survey.

Chapter 8: Implementation and Analysis of Proposed Model in a Distributed e-Healthcare System.

Chapter 9: Implementation and Analysis of Proposed Model in a Distributed e-Healthcare System.

Chapter 10: Advances in Education Policy through the Integration of Distributed Computing Approaches.

Chapter 11: Revolutionizing Data Management and Security with the Power of Blockchain and Distributed System.

Chapter 12: Enhancing Business Development, Ethics, and Governance with the Adoption of Distributed Systems.

Chapter 13: Leveraging Distribution Systems for Advanced Fraud Detection and Prevention in Finance.

Chapter 14: Advances in E-commerce through the Integration of Distributed Computing Approaches.

Chapter 15: The Impact of Distributed Computing on Online Shopping and Consumer Experience.

Chapter 16: Wireless Sensor Based IoT System with Distributed Optimization for Healthcare.

Chapter 17: Optimizing Financial Transactions and Processes through the Power of Distributed Systems.

Chapter 18: Leveraging Distributed Systems for Improved Market Intelligence and Customer Segmentation.

Chapter 19: The Future of Financial Crime Prevention and Cybersecurity with Distributed Systems and Computing Approaches.

Chapter 20: Innovations in Distributed Computing for Enhanced Risk Management in Finance.

Chapter 21: Leveraging Blockchain and Distributed Systems for Improved Supply Chain Traceability and Transparency.

Chapter 22: Advances in Resource Management through the Integration of Distributed Computing Approaches.

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