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题名/责任者:

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

版本说明:

1st ed. 2018.

出版发行项:

Singapore : Springer Singapore : Imprint: Springer, 2018.

ISBN:

9789811084768

其它标准号:

10.1007/978-981-10-8476-8

载体形态项:

VI, 384 p. 135 illus., 88 illus. in color. online resource.

主文献:

Springer eBooks

其他载体形态:

Printed edition: 9789811084751

其他载体形态:

Printed edition: 9789811084775

其他载体形态:

Printed edition: 9789811341625

丛编说明:

Studies in Big Data, 2197-6503 ; 44

丛编统一题名:

Studies in Big Data, 44

附加个人名称:

Roy, Sanjiban Sekhar. editor.

附加个人名称:

Samui, Pijush. editor.

附加个人名称:

Deo, Ravinesh. editor.

附加个人名称:

Ntalampiras, Stavros. editor.

附加团体名称:

SpringerLink (Online service)

论题主题:

Computational intelligence.

论题主题:

Big data.

论题主题:

Computer mathematics.

论题主题:

Computational Intelligence.

论题主题:

Big Data.

论题主题:

Computational Science and Engineering.

内容附注:

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.

摘要附注:

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.

电子资源:

https://doi.org/10.1007/978-981-10-8476-8

豆瓣简介：