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Big Data and Differential Privacy (Analysis Strategies for Railway Track Engineering) by Attoh-Okine, Nii O. is a scholarly article available to read on EtoBox.

What is Big Data and Differential Privacy (Analysis Strategies for Railway Track Engineering) about?

A comprehensive introduction to the theory and practice of contemporary data science analysis for railway track engineering Featuring a practical introduction to state-of-the-art data analysis for railway track engineering, Big Data and Differential Privacy: Analysis Strategies for Railway Track Engineering addresses common issues with the implementation of big data applications while exploring the limitations, advantages, and disadvantages of more conventional methods. In addition, the book provides a unifying approach to analyzing large volumes of data in railway track engineering using an array of proven methods and software technologies. Dr. Attoh-Okine considers some of today's most notable applications and implementations and highlights when a particular method or algorithm is most appropriate. Throughout, the book presents numerous real-world examples to illustrate the latest railway engineering big data applications of predictive analytics, such as the Union Pacific Railroad's use of big data to reduce train derailments, increase the velocity of shipments, and reduce emissions. In addition to providing an overview of the latest software tools used to analyze the large amoun

Author

Attoh-Okine, Nii O.

Publisher

John Wiley & Sons, Incorporated

Published

2017

Language

EN

ISBN

9781119229049