Applications of evolutionary computation : 25th European Conference, EvoApplications 2022, held as part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, proceedings

Responsibility
Juan Luis Jiménez Laredo, J. Ignacio Hidalgo Perez, Kehinde Oluwatoyin Babaagba (Eds.).
Publication
Cham, Switzerland : Springer, 2022.
Physical description
1 online resource (1 volume) : illustrations (black and white).
Series
Lecture notes in computer science ; 13224.

Online

Available online

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Description

Contents/Summary

Bibliography
Includes bibliographical references and author index.
Contents
  • Intro
  • Preface
  • Organization
  • Contents
  • Applications of Evolutionary Computation
  • An Enhanced Opposition-Based Evolutionary Feature Selection Approach
  • 1 Introduction
  • 2 Moth Flame Optimization
  • 2.1 Binary Moth Flame Optimization
  • 2.2 Binary Moth Flame Optimization for Feature Selection
  • 3 The Proposed Approach
  • 3.1 Initialization Using Opposition-Based Method
  • 3.2 Retiring Flame
  • 4 Experimental Setup and Results
  • 5 Conclusions
  • References
  • A Methodology for Determining Ion Channels from Membrane Potential Neuronal Recordings
  • 1 Introduction
  • 2 Conductance-Based Model Description
  • 3 Defining a Benchmark with Known Types of Ion Channels
  • 4 Methodology and Experimental Setup
  • 5 Experimental Results
  • 6 Conclusions
  • A Mathematical Description of the Models
  • B Experimental Setup and Parameter Ranges
  • References
  • Swarm Optimised Few-View Binary Tomography
  • 1 Introduction
  • 2 Binary Tomographic Reconstruction
  • 3 Swarm Optimisation
  • 4 Constrained Search in High Dimensions
  • 5 Reconstructions
  • 6 Results
  • 7 Discussion
  • 8 Conclusions
  • References
  • Comparing Basin Hopping with Differential Evolution and Particle Swarm Optimization
  • 1 Introduction
  • 2 The Metaheuristics Studied
  • 2.1 Basin Hopping
  • 2.2 Differential Evolution
  • 2.3 Particle Swarm Optimization
  • 3 The Benchmarking Environment
  • 4 Experimental Setup
  • 5 Experimental Results
  • 6 Conclusions
  • References
  • Combining the Properties of Random Forest with Grammatical Evolution to Construct Ensemble Models
  • 1 Introduction
  • 2 Methodology
  • 2.1 Structured Grammatical Evolution
  • 2.2 Random Structured Grammatical Evolution for Symbolic Regression Problems
  • 3 Experimental Setup
  • 3.1 Study Problems
  • 3.2 Configuration of the Algorithms
  • 4 Results
  • 5 Conclusions
  • References
  • EvoCC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in Python
  • 1 Introduction
  • 2 Related Works
  • 3 Methodology
  • 4 Framework Overview
  • 4.1 Parameters
  • 4.2 Datasets
  • 4.3 Clustering with EvoCluster
  • 4.4 Classification
  • 4.5 Evaluation Measures
  • 4.6 Results Management
  • 5 Experiments and Visualizations
  • 6 Conclusion and Future Works
  • References
  • Evolution of Acoustic Logic Gates in Granular Metamaterials
  • 1 Introduction
  • 2 Problem Statement
  • 3 Simulation Setup
  • 3.1 2D Granular Simulator
  • 3.2 Optimization Method
  • 4 Results and Discussion
  • 4.1 Evolution of an Acoustic Band Gap
  • 4.2 Evolving an AND Gate
  • 4.3 Evolving an XOR Gate
  • 5 Conclusion and Future Work
  • References
  • Public-Private Partnership: Evolutionary Algorithms as a Solution to Information Asymmetry
  • 1 Introduction
  • 2 The Problem
  • 3 Proposed Approach
  • 3.1 The Model
  • 3.2 Data
  • 3.3 Adversarial Optimization
  • 3.4 Operator (EA1)
  • 3.5 Public Administration (EA2)
  • 4 Experimental Evaluation
Publisher's summary
This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2022, held as part of Evo*2022, in April 2022, co-located with the Evo*2022 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented in this book were carefully reviewed and selected from 67 submissions. .
(source: Nielsen Book Data)

Bibliographic information

Publication date
2022
Series
Lecture notes in computer science ; 13224
ISBN
9783031024627 (electronic bk.)
3031024621 (electronic bk.)
9783031024610
3031024613
DOI
10.1007/978-3-031-02462-7
Librarian view | Catkey: 14273795