Uncertainty in Computational Intelligence-Based Decision Making

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Éditeur :

Academic Press


Paru le : 2024-09-16

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Description
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
Pages
350 pages
Collection
n.c
Parution
2024-09-16
Marque
Academic Press
EAN papier
9780443214752
EAN PDF
9780443214769

Informations sur l'ebook
Nombre pages copiables
35
Nombre pages imprimables
35
Taille du fichier
25856 Ko
Prix
168,80 €
EAN EPUB SANS DRM
9780443214769

Informations sur l'ebook
Prix
168,80 €

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