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Springer Time Series Analysis, Modeling and Applications Book

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Description

In a world driven by constant data streams, understanding temporal and spatiotemporal patterns is essential. This volume from the Intelligent Systems Reference Library (Volume 47) addresses the ongoing challenge of analyzing, interpreting, and predicting time series data. As we face massive amounts of information from sensors, financial markets, Internet activities, and environmental data, there is a growing need for models that provide both accuracy and interpretability. This book explores the conceptual and algorithmic frameworks necessary to handle physical and human-generated phenomena. It is designed to help researchers and professionals navigate the complex landscape of data feeds and recordings. By focusing on a computational intelligence perspective, the text provides a foundation for developing user-friendly models that can make sense of the vast streams of data defining our modern society.

Key Features

Explores temporal and spatiotemporal data analysis to help interpret complex data streams from numerous sensors and feeds.

Addresses the need for models that balance high accuracy with user-friendly interpretability for practical applications.

Covers diverse data sources including environmental data, financial markets, and Internet activities.

Part of the Intelligent Systems Reference Library, providing a deep computational intelligence perspective.

Provides a framework for modeling and predicting both physical and human-generated phenomena.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
06 November 2012
Listed Since
16 August 2012

Barcode

No barcode data available

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