Name: Machine Learning Applications in Non-Conventional Machining Processes (en Inglés)
Price: 188.78 USD
Availability: InStock
Author: Bose, Goutam Kumar ; Pain, Pritam
ISBN: 9781799836254

portada Machine Learning Applications in Non-Conventional Machining Processes (en Inglés)

Machine Learning Applications in Non-Conventional Machining Processes (en Inglés)

Formato

Libro Físico

Editorial

Engineering Science Reference

Autor

Bose, Goutam Kumar ; Pain, Pritam

Idioma

Inglés

N° páginas

344

Encuadernación

Tapa Blanda

Dimensiones

27.9 x 21.6 x 1.8 cm

Peso

0.80 kg.

ISBN13

9781799836254

Categorías

Algoritmos y estructuras de datos
Teoría matemática de la computación
Aprendizaje automático («machine learning»)
Redes neuronales y sistemas difusos

Machine Learning Applications in Non-Conventional Machining Processes (en Inglés)

Bose, Goutam Kumar ; Pain, Pritam (Autor) · Engineering Science Reference · Tapa Blanda

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Reseña del libro "Machine Learning Applications in Non-Conventional Machining Processes (en Inglés)"

Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today's technology-driven market.