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Big Data in Engineering Applications at Meripustak

Big Data in Engineering Applications by Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras , Springer

Books from same Author: Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras

Books from same Publisher: Springer

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  • General Information  
    Author(s)Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras
    PublisherSpringer
    ISBN9789811341625
    Pages384
    BindingPaperback
    LanguageEnglish
    Publish YearDecember 2018

    Description

    Springer Big Data in Engineering Applications by Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras

    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._x000D_ Table of contents : - _x000D_ 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._x000D_



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