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Tofigh Allahviranloo, Witold Pedrycz, Amir Seyyedabbasi

Decision-Making Models

Name: Decision-Making Models
Author: Tofigh Allahviranloo

A Perspective of Fuzzy Logic and Machine Learning

Paperback Engels 2024 9780443161476

157,-

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Samenvatting

Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems.

Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty.

Specificaties

ISBN13:9780443161476

Taal:Engels

Bindwijze:Paperback

Uitgever:Elsevier Science

Serie:Uncertainty, Computational Techniques, and Decision Intelligence

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Inhoudsopgave

Section 1: Decision Making: New Developments 1. Neural networks 2. Artificial intelligent algorithms, motivation and terminology 3. Decision processes 4. Learning theory Section 2: Metaheuristic Algorithms 5. Nature-inspired algorithms 6. Physic-based algorithms 7. evolution-based algorithms 8. swarm-based algorithms 9. Multi-objective algorithms 10. Unconstrained / constrained nonlinear optimization 11. Evolutionary Computing Section 3: Optimization Problems 12. Mathematical Programming 13. Discrete and Combinatorial Optimization 14. Optimization and Data Analysis 15. Applied optimization problems 16. Engineering problems Section 4: Machine Learning 17. Deep Learning 18. (Artificial) Neural Networks 19. Reinforcement Learning Algorithms 20. Classification and clustering Section 5: Soft Computation 21. Uncertainty theory 22. Fuzzy sets 23. Computation with words 24. Soft modelling 25. Uncertain optimization models 26. Chaos theory and chaotic systems Section 6: Data Analysis 27. Data mining and knowledge discovery 28. Categories of techniques of data analysis 29. Numerical analysis 30. Risk analysis Section 7: Fuzzy Decision System 31. Fuzzy Control 32. Approximate Reasoning 33. Effectiveness in Fuzzy Logics 34. Neuro-fuzzy Systems 35. Fuzzy rule-based systems

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