Big Data in Engineering Applications

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Roy, Sanjiban Sekhar (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Samui, Pijush (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Deo, Ravinesh (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Ntalampiras, Stavros (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Studies in Big Data, 44
• Θέματα: Computational intelligence.; Big data.; Computer mathematics.; Computational Intelligence.; Big Data.; Computational Science and Engineering.
• Φυσική περιγραφή: VI, 384 p. 135 illus., 88 illus. in color. online resource.
• ISBN: 9789811084768
• ISSN: 2197-6503 ;
• DOI: 10.1007/978-981-10-8476-8

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.