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Mathematical Modeling in Computational Intelligence and Generative AI

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Mathematical Modeling in Computational Intelligence and Generative AI Synopsis

This proceedings volume discusses topics on generative AI-one of the most trending topics and application in every field of science and engineering-and machine intelligence. Chapters of this proceedings were presented at the International Conference on Mathematical Modeling in Computational Intelligence and Generative AI (Math-CIGAI), held at Koneru Lakshmaiah Education Foundation, Hyderabad, India, from 19-20 June 2025. The book also discusses how to develop new products and automate the system by generating the new and improved models and improve decision making systems. It also discusses the applications of machine intelligence and generative AI in healthcare decision making, drug discovery, personalized care, synthetic data generation, automations, and many more. Topics on mathematical models such as adversarial networks and variational autoencoders are also discusses which are deployed to produce images for data augmentation, improving disease diagnosis and advanced medical imaging research areas. This volume is intended for researchers, academicians, and professionals.

About This Edition

ISBN: 9789819245789
Publication date:
Author: YuChen Hu, Debnath Bhattacharyya, Jaroslav Frnda, Rajib Ghosh
Publisher: Springer an imprint of Springer Nature Singapore
Format: Hardback
Pagination: 423 pages
Series: Springer Proceedings in Mathematics & Statistics
Genres: Mathematical modelling
Numerical analysis
Maths for engineers
Artificial intelligence

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