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Handling Uncertainty in Artificial Intelligence (SpringerBriefs in Computational Intelligence) - Softcover
Inhaltsangabe
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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Über die Autorin bzw. den Autor
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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Handling Uncertainty in Artificial Intelligence
Verlag:
Springer Nature Singapore, 2023
ISBN 10: 9819953324
ISBN 13: 9789819953325
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ISBN 10: 9819953324
ISBN 13: 9789819953325
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Handling Uncertainty in Artificial Intelligence
ISBN 10: 9819953324
ISBN 13: 9789819953325
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Taschenbuch. Zustand: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 116 pp. Englisch. Artikel-Nr. 9789819953325
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Handling Uncertainty in Artificial Intelligence
Verlag:
Springer Nature Singapore, Springer Nature Singapore, 2023
ISBN 10: 9819953324
ISBN 13: 9789819953325
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This bookdemonstrates 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. Artikel-Nr. 9789819953325
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Handling Uncertainty in Artificial Intelligence
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