Artificial Intelligence and Machine Learning Algorithms for Engineering Applications

The text showcases the use of artificial intelligence and machine learning-based algorithms with advanced tools and methodologies for diverse engineering applications. It further discusses topics such as data preprocessing, cross-validation techniques, support vector machines in manufacturing, and reinforcement learning for control systems.

This book comprehensively covers core algorithms and techniques used in artificial intelligence (AI) and machine learning (ML) for engineering applications. It further explores the use of AI in civil and structural engineering, quality control, and product design.

Features:

• Presents autonomous robots using onboard computing and artificial intelligence (AI) algorithms to process the data from their sensors and make real-time decisions
• Discusses nature-based optimization-based computing techniques to enhance the computational speed for solving engineering problems
• Provides conceptual and practical knowledge about the design of modern computation techniques with advanced tools and methodologies
• Highlights the importance of using smart techniques including AI and ML in product design and development
• Covers time series analysis and forecasting in engineering, robotic process automation, and autonomous robots in manufacturing

The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, manufacturing engineering, and environmental engineering.

Contributor: Krishan Arora (Edited by), Himanshu Sharma (Edited by), Aeidapu Mahesh (Edited by)

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