Artificial Intelligence and Machine Learning Techniques in Engineering and Management

Srinivasa Raju, Komaragiri; Nagesh Kumar, Dasika

The present book covers various facets of Artificial Intelligence, Machine Learning, and Fuzzy Logic. It includes a brief discussion on performance indicators, Classical and Advanced Machine Learning algorithms, Fuzzy logic-based modelling algorithms, Emerging Research Areas, including Blockchain, recent ML techniques, Evolutionary Algorithms, Large Language Model (LLM)-based Generative AI, the Internet of Things, Big Data, Decision Support Systems, Taguchi design of experiments, data augmentation, and Cross-Validation, and representative case studies. The appendix covers representative AI tools, data sources, books, and journals on AI. The present book can support undergraduate, postgraduate, and Ph.D. students in Artificial Intelligence, Generative Artificial Intelligence, Machine Learning, Data Sciences, Soft Computing, and Fuzzy Logic in Engineering and Management and allied fields. The proposed book has immense value in the interdisciplinary and cross-disciplinary context.

Details

Published by: Springer

Publication Date: 2025-05-22

Format: Hardcover

ISBN-13: 9789819626205

DOI: 10.1007/978-981-96-2621-2

Dimensions: 235cm x155cm

Pages: 266