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Erschienen in:
Introduction to Emergency Management Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Learning Algorithms for Emergency Management

verfasst von : Minsung Hong, Rajendra Akerkar

Erschienen in: Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data

Verlag: Springer International Publishing

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Abstract

Machine learning techniques can help authorities and decision makers more accurately answer urgent questions. Machine learning can be used to refine strategies over time, getting smarter about planning and response. This chapter discusses the application of fundamental learning techniques to support the decision making processes for emergency management. The chapter also presents exercises based on the learning techniques using emergency relevant tweeter datasets.

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Vorheriges Kapitel Big Data
Nächstes Kapitel Knowledge Graphs and Natural-Language Processing
Fußnoten
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Wards distance between clusters C i and C j is the difference between the total within cluster sum of squares for the two clusters separately, and the within cluster sum of squares resulting from merging the two clusters in cluster C ij.
 
4
In Computer Vision, a Fisher Vector is used to describe an entire image for image classification [43].
 
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Metadaten
Titel
Learning Algorithms for Emergency Management
verfasst von
Minsung Hong
Rajendra Akerkar
Copyright-Jahr
2020
Buch
Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data

Print ISBN: 978-3-030-48098-1

Electronic ISBN: 978-3-030-48099-8

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-48099-8_3

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