Handling Uncertainty in Artificial Intelligence - Couverture souple

Livre 291 sur 472: SpringerBriefs in Applied Sciences and Technology

Chaki, Jyotismita

 
9789819953325: Handling Uncertainty in Artificial Intelligence

Synopsis

This book demonstrates different methods (as well as real-life examples) of handling uncertainty like probability and Bayesian theory, Dempster-Shafer theory, certainty factor and evidential reasoning, fuzzy logic-based approach, utility theory and expected utility theory. At the end, highlights will be on the use of these methods which can help to make decisions under uncertain situations. This book assists scholars and students who might like to learn about this area as well as others who may have begun without a formal presentation. The book is comprehensive, but it prohibits unnecessary mathematics.

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À propos de l?auteur

JYOTISMITA CHAKI, PhD. is an Associate Professor in School of Computer Science and Engineering at Vellore Institute of Technology, Vellore, India. Her research interests include: Computer Vision and Image Processing, Pattern Recognition, Medical Imaging, Soft computing, Artificial Intelligence and Machine learning. She has authored and edited many international conferences, journal papers and books. Currently she is the editor of Engineering Applications of Artificial Intelligence Journal, Elsevier, academic editor of PLOS ONE journal and associate editor of Array journal, Elsevier, IET Image Processing, Applied Computational Intelligence and Soft Computing and Machine Learning with Applications journal, Elsevier.

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Autres éditions populaires du même titre

9789819953349: Handling Uncertainty in Artificial Intelligence

Edition présentée

ISBN 10 :  9819953340 ISBN 13 :  9789819953349
Editeur : Springer, 2023
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