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Applications of Evolutionary Computation

Overview of attention for book
Cover of 'Applications of Evolutionary Computation'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines
  3. Altmetric Badge
    Chapter 2 On the Use of Smelly Examples to Detect Code Smells in JavaScript
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    Chapter 3 Deep Parameter Tuning of Concurrent Divide and Conquer Algorithms in Akka
  5. Altmetric Badge
    Chapter 4 Focusing Learning-Based Testing Away from Known Weaknesses
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    Chapter 5 Polytypic Genetic Programming
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    Chapter 6 Evolving Rules for Action Selection in Automated Testing via Genetic Programming - A First Approach
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    Chapter 7 A New Multi-swarm Particle Swarm Optimization for Robust Optimization Over Time
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    Chapter 8 The Static and Stochastic VRP with Time Windows and both Random Customers and Reveal Times
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    Chapter 9 Pre-scheduled Colony Size Variation in Dynamic Environments
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    Chapter 10 An Online Packing Heuristic for the Three-Dimensional Container Loading Problem in Dynamic Environments and the Physical Internet
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    Chapter 11 Advancing Dynamic Evolutionary Optimization Using In-Memory Database Technology
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    Chapter 12 Road Traffic Rules Synthesis Using Grammatical Evolution
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    Chapter 13 Solving Dynamic Graph Coloring Problem Using Dynamic Pool Based Evolutionary Algorithm
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    Chapter 14 Meta-heuristics for Improved RF Emitter Localization
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    Chapter 15 Automated Design of Genetic Programming Classification Algorithms Using a Genetic Algorithm
Attention for Chapter 6: Evolving Rules for Action Selection in Automated Testing via Genetic Programming - A First Approach
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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5 X users

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12 Mendeley
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Chapter title
Evolving Rules for Action Selection in Automated Testing via Genetic Programming - A First Approach
Chapter number 6
Book title
Applications of Evolutionary Computation
Published in
Lecture notes in computer science, March 2017
DOI 10.1007/978-3-319-55792-2_6
Book ISBNs
978-3-31-955791-5, 978-3-31-955792-2
Authors

Anna I. Esparcia-Alcázar, Francisco Almenar, Urko Rueda, Tanja E. J. Vos

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 33%
Student > Master 3 25%
Student > Bachelor 1 8%
Student > Ph. D. Student 1 8%
Unknown 3 25%
Readers by discipline Count As %
Computer Science 8 67%
Engineering 1 8%
Unknown 3 25%
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 07 June 2017.
All research outputs
#6,461,837
of 22,963,381 outputs
Outputs from Lecture notes in computer science
#2,100
of 8,137 outputs
Outputs of similar age
#104,848
of 309,171 outputs
Outputs of similar age from Lecture notes in computer science
#14
of 100 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,137 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 309,171 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 66% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.