Uncertainty in Computational Intelligence-Based Decision Making
eBook - PDF

Uncertainty in Computational Intelligence-Based Decision Making

  1. 350 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Uncertainty in Computational Intelligence-Based Decision Making

About this book

Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science. - Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms - Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design - Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision

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Yes, you can access Uncertainty in Computational Intelligence-Based Decision Making by Ali Ahmadian,Soheil Salahshour,Valentina Emilia Balas,Dumitru Baleanu in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Front Cover
  2. Uncertainty in Computational Intelligence-Based Decision Making
  3. Copyright
  4. Contents
  5. Contributors
  6. Chapter 1: TOPSIS for the selection of the prediction model in forensic ink analysis
  7. Chapter 2: Effectiveness of artificial intelligence in determining foot pathologies and designing insoles using plain rad ...
  8. Chapter 3: Outbound logistics business process modeling: Analytic perspective with BPMN 2.0
  9. Chapter 4: Revolutionizing diabetic foot ulcer treatment prediction: Harnessing the power of artificial intelligence and ...
  10. Chapter 5: A systematic review on personalized hybrid diet recommendations
  11. Chapter 6: Impact of number and type of criteria on ranking abnormality in MCDM techniques
  12. Chapter 7: Comparison between some methods in fuzzy linear regression
  13. Chapter 8: Artificial intelligence and decision making in climate change studies: A review
  14. Chapter 9: Computational decision intelligence approaches for drought prediction: A review
  15. Chapter 10: A review of the applications of computational decision intelligence approaches in agrometeorology
  16. Chapter 11: A fuzzy logic design for self-driving vehicle to avoid obstacles
  17. Chapter 12: K-means clustering over distributed environment: A review
  18. Chapter 13: Advanced frequent itemset mining algorithm (AFIM)
  19. Chapter 14: TEAM: Trust evaluation and analysis of misbehavior in WSNs
  20. Chapter 15: Computational intelligence in decision support: Scope and techniques
  21. Chapter 16: Automatic parallelization for multicore architectures: Role, importance, and opportunities
  22. Chapter 17: Using tensor processing units to identify the relationship between hypothesis and premise: A case of natural ...
  23. Chapter 18: Secure and cost-effective key management scheme for the Internet of Things-supported WSN
  24. Chapter 19: A deep learning-based integrated voice assistance system for partially disabled people
  25. Index
  26. Back Cover