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Springer Big Data Analytics for Time-Critical Mobility Forecasting

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Description

Master the complexities of large-scale movement data with this comprehensive guide from Springer. Big Data Analytics for Time-Critical Mobility Forecasting provides technical depth for understanding how to process and manage massive volumes of moving entity data across wide geographical areas. This book covers state-of-the-art methods for detecting and predicting trajectories and significant events. It is designed for those working with heterogeneous, voluminous, and noisy data streams that fluctuate constantly. By learning to correlate real-time streams with archived data sources, such as entity characteristics and geographic information, you can build more accurate forecasting models. Specifically tailored to the aviation and maritime domains, this text explores advanced visual analytics to make sense of complex data. Whether you are managing moving entities or developing new predictive algorithms, this resource offers the methodologies needed to transform raw data into actionable trajectory-oriented mobility analytics.

Key Features

Covers big data solutions for activity detection and forecasting of large numbers of moving entities across wide areas.

Provides state-of-the-art methods for processing, managing, and predicting trajectories and important events.

Addresses challenges in handling heterogeneous, voluminous, fluctuating, and noisy data streams.

Includes advanced visual analytics methods to interpret complex mobility data sets.

Focuses on practical applications within the aviation and maritime domains.

Explains how to correlate real-time data streams with archived sources like entity characteristics and geographic data.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
24 June 2021
Listed Since
28 May 2021

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