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Book synopsis

Applied Artificial Intelligence for Engineering Applications: Empowering Transformative Innovations in Multidisciplinary Engineering offers an integrated view of AI’s transformative potential in multidisciplinary engineering, bridging the gap between AI advances and their applications in various engineering disciplines, including civil, mechanical, electrical, chemical, and robotics. The book starts with an introduction to the field, providing an overview of AI technologies and their relevance to engineering, discussing different AI approaches such as machine learning, reinforcement learning, neural networks, and natural language processing. Computational tools and software used for each of these approaches are covered, as are AI-driven innovations in electronics design and manufacturing as well as the role of AI in the development of advanced sensors and IoT devices. Chapters then cover the deployment of AI in specific engineering disciplines, outlining its use in civil engineering, mechanical engineering, production engineering, and chemical engineering. The use of AI as a solution for energy efficiency and management and renewable energy integration is also discussed.

• Discusses the intersection of AI and multidisciplinary engineering, integrating insights from various engineering disciplines, and providing practical examples of AI applications
• Provides practical frameworks, methodologies, and tools that can be utilized to implement AI-driven solutions
• Presents real-world case studies from various engineering fields, highlighting successful AI implementations and the outcomes achieved

Book details

Book category Books in English Technology, engineering, agriculture Technology: general issues Engineering: general

• Full title: Applied Artificial Intelligence for Engineering Applications
• Subtitle: Empowering Transformative Innovations in Multidisciplinary Engineering
• Author: Tarek Saadawi, Roshan Raman, Sharda Vashisth, Pooja Sabherwal, Aman Garg, Saurabh Sachdeva
• Language: English
• Binding: Paperback
• Number of pages: 350
• EAN: 9780443443381
• ISBN: 0443443386
• ID: 49798229
• Publisher: Elsevier Science
• Weight: 450 g
• Dimensions: 229 × 152 mm
• Date of publishing: 01. May 2026

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