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portada Artificial Intelligence and Machine Learning Algorithms for Engineering Applications
Formato
Libro Físico
Editorial
Año
2025
N° páginas
296
Encuadernación
Tapa Dura
Dimensiones
23.40 x 15.60 cm
ISBN13
9781032900520

Artificial Intelligence and Machine Learning Algorithms for Engineering Applications

Aeidapu Mahesh;Krishan Arora;Himanshu Sharma (Autor) · CRC Press · Tapa Dura

Artificial Intelligence and Machine Learning Algorithms for Engineering Applications - Aeidapu Mahesh;Krishan Arora;Himanshu Sharma

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Reseña del libro "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.

The book comprehensively covers core algorithms and techniques used in artificial intelligence and machine learning for engineering applications. It further explores the use of artificial intelligence 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 as well as practical knowledge about the design of modern computation techniques with advanced tools and methodologies.

Highlights the importance of using smart techniques including artificial intelligence and machine learning 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.

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