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Computational Intelligence

Overview of attention for book
Cover of 'Computational Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Niching-Based Feature Selection with Multi-tree Genetic Programming for Dynamic Flexible Job Shop Scheduling
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    Chapter 2 Building Market Timing Strategies Using Trend Representative Testing and Computational Intelligence Metaheuristics
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    Chapter 3 Hybrid Strategy Coupling EGO and CMA-ES for Structural Topology Optimization in Statics and Crashworthiness
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    Chapter 4 An Empirical Study on Insertion and Deletion Mutation in Cartesian Genetic Programming
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    Chapter 5 Handling Complexity in Some Typical Problems of Distributed Systems by Using Self-organizing Principles
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    Chapter 6 Markov Decision Processes with Fuzzy Risk-Sensitive Rewards: The Best Coherent Risk Measures Under Risk Averse Utilities
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    Chapter 7 Correlation Analysis Via Intuitionistic Fuzzy Modal and Aggregation Operators
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    Chapter 8 Fuzzy Geometric Approach to Collision Estimation Under Gaussian Noise in Human-Robot Interaction
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    Chapter 9 Predicting Cardiovascular Death with Automatically Designed Fuzzy Logic Rule-Based Models
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    Chapter 10 Neural Models to Quantify the Determinants of Truck Fuel Consumption
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    Chapter 11 Towards a Class-Aware Information Granulation for Graph Embedding and Classification
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    Chapter 12 Near Optimal Solving of the (N $$^2$$ 2 –1)-puzzle Using Heuristics Based on Artificial Neural Networks
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    Chapter 13 Deep Convolutional Neural Network Processing of Images for Obstacle Avoidance
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    Chapter 14 CVaR Q-Learning
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    Chapter 15 Rule Extraction from Neural Networks and Other Classifiers Applied to XSS Detection
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    Chapter 16 Introduction to Sequential Heteroscedastic Probabilistic Neural Networks
Attention for Chapter 4: An Empirical Study on Insertion and Deletion Mutation in Cartesian Genetic Programming
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Citations

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Chapter title
An Empirical Study on Insertion and Deletion Mutation in Cartesian Genetic Programming
Chapter number 4
Book title
Computational Intelligence
Published in
Studies in Computational Intelligence, July 2021
DOI 10.1007/978-3-030-70594-7_4
Book ISBNs
978-3-03-070593-0, 978-3-03-070594-7
Authors

Roman Kalkreuth, Kalkreuth, Roman

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 100%
Readers by discipline Count As %
Computer Science 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 July 2021.
All research outputs
#17,732,227
of 25,992,468 outputs
Outputs from Studies in Computational Intelligence
#1
of 1 outputs
Outputs of similar age
#279,484
of 456,171 outputs
Outputs of similar age from Studies in Computational Intelligence
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 1.0. 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 456,171 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
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

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