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Deep Learning Applications and Intelligent Decision Making in Engineering

Deep Learning Applications and Intelligent Decision Making in Engineering

Copyright: © 2021 |Pages: 332
ISBN13: 9781799821083|ISBN10: 1799821080|ISBN13 Softcover: 9781799821090|EISBN13: 9781799821106
DOI: 10.4018/978-1-7998-2108-3
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MLA

Senthilnathan, Karthikrajan, et al., editors. Deep Learning Applications and Intelligent Decision Making in Engineering. IGI Global, 2021. https://doi.org/10.4018/978-1-7998-2108-3

APA

Senthilnathan, K., Shanmugam, B., Goyal, D., Annapoorani, I., & Samikannu, R. (Eds.). (2021). Deep Learning Applications and Intelligent Decision Making in Engineering. IGI Global. https://doi.org/10.4018/978-1-7998-2108-3

Chicago

Senthilnathan, Karthikrajan, et al., eds. Deep Learning Applications and Intelligent Decision Making in Engineering. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-2108-3

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Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process.

Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Advances in Computational Intelligence and Robotics (ACIR) Book Series
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Preface
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Chapters
Back Materials
Compilation of References
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About the Contributors
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Index
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