Altmetric – Genetic Programming
↓ Skip to main content
What is this page? Embed badge

Genetic Programming

Overview of attention for book
Cover of 'Genetic Programming'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Genetic Programming
  3. Altmetric Badge
    Chapter 2 Learning Text Patterns Using Separate-and-Conquer Genetic Programming
  4. Altmetric Badge
    Chapter 3 Improving Geometric Semantic Genetic Programming with Safe Tree Initialisation
  5. Altmetric Badge
    Chapter 4 On the Generalization Ability of Geometric Semantic Genetic Programming
  6. Altmetric Badge
    Chapter 5 Automatic Derivation of Search Objectives for Test-Based Genetic Programming
  7. Altmetric Badge
    Chapter 6 Evolutionary Design of Transistor Level Digital Circuits Using Discrete Simulation
  8. Altmetric Badge
    Chapter 7 M3GP – Multiclass Classification with GP
  9. Altmetric Badge
    Chapter 8 Evolving Ensembles of Dispatching Rules Using Genetic Programming for Job Shop Scheduling
  10. Altmetric Badge
    Chapter 9 Attributed Grammatical Evolution Using Shared Memory Spaces and Dynamically Typed Semantic Function Specification
  11. Altmetric Badge
    Chapter 10 Indirectly Encoded Fitness Predictors Coevolved with Cartesian Programs
  12. Altmetric Badge
    Chapter 11 Tapped Delay Lines for GP Streaming Data Classification with Label Budgets
  13. Altmetric Badge
    Chapter 12 Cartesian GP in Optimization of Combinational Circuits with Hundreds of Inputs and Thousands of Gates
  14. Altmetric Badge
    Chapter 13 Genetic Programming for Feature Selection and Question-Answer Ranking in IBM Watson
  15. Altmetric Badge
    Chapter 14 Automatic Evolution of Parallel Recursive Programs
  16. Altmetric Badge
    Chapter 15 Proposal and Preliminary Investigation of a Fitness Function for Partial Differential Models
  17. Altmetric Badge
    Chapter 16 Evolutionary Methods for the Construction of Cryptographic Boolean Functions
  18. Altmetric Badge
    Chapter 17 Templar – A Framework for Template-Method Hyper-Heuristics
  19. Altmetric Badge
    Chapter 18 Circuit Approximation Using Single- and Multi-objective Cartesian GP
Overall attention for this book and its chapters
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
17 Mendeley
Summary Wikipedia Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genetic Programming
Published by
Lecture notes in computer science, March 2015
DOI 10.1007/978-3-319-16501-1
ISBNs
978-3-31-916500-4, 978-3-31-916501-1
Authors

Penousal Machado, Malcolm I. Heywood, James McDermott, Mauro Castelli, Pablo García-Sánchez, Paolo Burelli, Sebastian Risi, Kevin Sim, Park, John, Nguyen, Su, Zhang, Mengjie, Johnston, Mark

Editors

Machado, Penousal, Sim, Kevin, Risi, Sebastian, Burelli, Paolo, García Sánchez, Pablo, Castelli, Mauro, McDermott, James, Heywood, Malcolm I.

View on publisher site
Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 24%
Student > Doctoral Student 3 18%
Student > Ph. D. Student 3 18%
Other 2 12%
Lecturer 2 12%
Other 2 12%
Unknown 1 6%
Readers by discipline Count As %
Computer Science 9 53%
Engineering 5 29%
Decision Sciences 1 6%
Unknown 2 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 September 2024.
All research outputs
#9,008,083
of 26,563,746 outputs
Outputs from Lecture notes in computer science
#2,587
of 8,208 outputs
Outputs of similar age
#97,999
of 277,772 outputs
Outputs of similar age from Lecture notes in computer science
#37
of 95 outputs
Altmetric has tracked 26,563,746 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,208 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 53% 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 277,772 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 53% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.

This page is provided by Altmetric.