Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making
eBook - ePub

Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making

Artificial Intelligence Applications

  1. 256 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making

Artificial Intelligence Applications

About this book

This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.

This book:

  • Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computing
  • Presents a comparative analysis of machine learning algorithms for power consumption prediction
  • Discusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environment
  • Illustrates a data-driven optimization concept for modeling environmental and economic sustainability
  • Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals

The text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering.

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Yes, you can access Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making by Irfan Ali,Umar Muhammad Modibbo,Asaju La'aro Bolaji,Harish Garg,Asaju La’aro Bolaji in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Computer Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Table of Contents
  7. About the editors
  8. List of contributors
  9. 1 Linking green supply chain management practices with competitiveness, Industry 4.0, and social responsibility
  10. 2 Comparative analysis of machine learning algorithms for the power consumption prediction
  11. 3 Prediction of cardiovascular disease using information gain, artificial neural network, and CART 5.0 algorithms
  12. 4 Weighting of logistics management factors by SWARA and DELPHI methods
  13. 5 Evaluation of daily management with standard deviation and MOOSRA tools in hospitals
  14. 6 Machine learning-based multi-objective optimization technique for load balancing in integrated fog-cloud environment
  15. 7 Perishable inventory fuzzy optimization model with uncertain deterioration and preservation investment
  16. 8 Employing fuzzy inference system in ant colony optimization for travelling salesman problems
  17. 9 Type-2 Gaussian neuro-fuzzy VIKOR technique in multi-criteria decision-making for medical diagnostic
  18. 10 Overview of AI and explainable AI decision-making (XAIDM)
  19. 11 Harnessing the power of Industry 4.0: Synergizing smart manufacturing, supply chain, and reshoring strategies
  20. 12 Digital revolution in cold supply chain management related to the food industry
  21. 13 The impact of blockchain technology and decentralized supply chain on production
  22. Index