Big data in engineering applications
Author(s)
Bibliographic Information
Big data in engineering applications
(Studies in big data, v. 44)
Springer, c2018
Available at 3 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
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  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
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  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
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  France
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Note
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
Big Data Applications in Education and Health Care.- Analysis of Compressive strength of alkali activated cement using Big data analysis.- Application of cluster based AI methods on daily streamflows.- Bigdata applications to smart power systems.- Big Data in e-commerce.- Interaction of Independent Component Analysis (ICA) and Support Vector Machine (SVM) in exploration of Greenfield areas.- Big Data Analysis of decay Coefficient of Naval Propulsion Plant.- Information Extraction and Text Summarization in documents using Apache Spark.- Detecting Outliers from Big Data Streams.- Machine Learning in Big Data Applications.
by "Nielsen BookData"