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Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights

Overview of attention for book
Cover of 'Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 An Assessment of the Impact of Natural and Technological Disasters Using a DEA Approach
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    Chapter 2 Selective Routing for Post-disaster Needs Assessments
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    Chapter 3 Bridging the Gap
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    Chapter 4 Multi-Hazard Scenarios and Impact Mapping for a Protected Built Area in Bucharest, as a Base for Emergency Planning
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    Chapter 5 Lean Thinking and UN Field Operations: A Successful Co-existence?
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    Chapter 6 Collaborative Incident Planning and the Common Operational Picture
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    Chapter 7 Metaheuristic Optimization for Logistics in Natural Disasters
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    Chapter 8 Tsunami of the Meteoric Origin
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    Chapter 9 The Donation Collections Routing Problem
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    Chapter 10 Network Criticality and Network Complexity Indicators for the Assessment of Critical Infrastructures During Disasters
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    Chapter 11 Freight Service Provision for Disaster Relief: A Competitive Network Model with Computations
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    Chapter 12 A Mean-Variance Disaster Relief Supply Chain Network Model for Risk Reduction with Stochastic Link Costs, Time Targets, and Demand Uncertainty
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    Chapter 13 A Review of Current Earthquake and Fire Preparedness Campaigns: What Works?
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    Chapter 14 The Impact of the Syria Crisis on Lebanon
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    Chapter 15 Absenteeism Impact on Local Economy During a Pandemic via Hybrid SIR Dynamics
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    Chapter 16 Tornado Detection with Kernel-Based Classifiers from WSR-88D Radar Data
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    Chapter 17 Evacuation Modeling and Betweenness Centrality
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    Chapter 18 Ode to the Humanitarian Logistician: Humanistic Logistics Through a Nurse’s Eye
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

twitter
6 X users

Readers on

mendeley
21 Mendeley
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Title
Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights
Published by
Springer Proceedings in Mathematics & Statistics, January 2016
DOI 10.1007/978-3-319-43709-5
ISBNs
978-3-31-943709-5, 978-3-31-943707-1
Editors

Ilias S. Kotsireas, Anna Nagurney, Panos M. Pardalos

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 19%
Student > Ph. D. Student 4 19%
Student > Doctoral Student 1 5%
Student > Bachelor 1 5%
Researcher 1 5%
Other 1 5%
Unknown 9 43%
Readers by discipline Count As %
Engineering 3 14%
Business, Management and Accounting 2 10%
Mathematics 1 5%
Environmental Science 1 5%
Computer Science 1 5%
Other 3 14%
Unknown 10 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 February 2023.
All research outputs
#7,556,603
of 25,992,468 outputs
Outputs from Springer Proceedings in Mathematics & Statistics
#1
of 1 outputs
Outputs of similar age
#109,026
of 402,374 outputs
Outputs of similar age from Springer Proceedings in Mathematics & Statistics
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 4.0. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,374 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them