This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

Big Data in Engineering Applications / [a cura di] S. Sekhar Roy, P. Samui, R. Deo, S. Ntalampiras. - [s.l] : Springer, 2018. - ISBN 9789811084751. (STUDIES IN BIG DATA) [10.1007/978-981-10-8476-8]

Big Data in Engineering Applications

S. Ntalampiras
2018

Abstract

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.
2018
Deep Learning; Machine Learning; Deep Neutral Network; Data Analytics; Predictive Modeling; Predictive Analysis; Data Visualization; Data Mining; Internet of Things; Decision-Making Process
Settore INF/01 - Informatica
Big Data in Engineering Applications / [a cura di] S. Sekhar Roy, P. Samui, R. Deo, S. Ntalampiras. - [s.l] : Springer, 2018. - ISBN 9789811084751. (STUDIES IN BIG DATA) [10.1007/978-981-10-8476-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/784350
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