Handling Uncertainty in Artificial Intelligence: SpringerBriefs in Applied Sciences and Technology
Autor Jyotismita Chakien Limba Engleză Paperback – 7 aug 2023
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Specificații
ISBN-13: 9789819953325
ISBN-10: 9819953324
Pagini: 101
Ilustrații: XIII, 101 p. 42 illus., 2 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.2 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seriile SpringerBriefs in Applied Sciences and Technology, SpringerBriefs in Computational Intelligence
Locul publicării:Singapore, Singapore
ISBN-10: 9819953324
Pagini: 101
Ilustrații: XIII, 101 p. 42 illus., 2 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.2 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seriile SpringerBriefs in Applied Sciences and Technology, SpringerBriefs in Computational Intelligence
Locul publicării:Singapore, Singapore
Cuprins
Introduction to handling uncertainty in artificial intelligence.- Probability and Bayesian Theory to Handle Uncertainty in artificial intelligence.- The Dempster-Shafer Theory to handle uncertainty in artificial intelligence.- Certainty factor and evidential reasoning to handle uncertainty in artificial intelligence.- A fuzzy logic-based approach to handle uncertainty in artificial intelligence.- Decision-making under uncertainty in artificial intelligence.- Applications of different methods to handle uncertainty in artificial intelligence.
Notă biografică
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.
Caracteristici
Demonstrates different numeric and symbolic methods of handling uncertainty in artificial intelligence Highlights on making decisions under uncertain situation Includes examples of real-life uncertain situations which will enhance the understandability of the reader