Descriptive statistics of fitness function results through the 30 executions by each approach optimizing the hyperparameters of the FCNN, GRNN and RBF by data set

Descriptive statistics of fitness function results through the 30 executions by each approach optimizing thehyperparameters of the FCNN by data set

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-28
DOI
https://doi.org/10.5281/zenodo.14736075
Primary Topic
Evolutionary Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Descriptive statistics of fitness function results through the 30 executions by each approach optimizing the hyperparameters of the FCNN, GRNN and RBF by data set

Zenodo (CERN European Organization for Nuclear Research)
Evolutionary Algorithms and Applications
article

Descriptive statistics of fitness function results through the 30 executions by each approach optimizing the hyperparameters of the FCNN, GRNN and RBF by data set

article en

Abstract

Descriptive statistics of fitness function results through the 30 executions by each approach optimizing thehyperparameters of the FCNN by data set

Zenodo (CERN European Organization for Nuclear Research)
Universidad Veracruzana (MX)
Openalex Percentile: Top 76%
Evolutionary Algorithms and Applications
DOIOpen Access PDFOpenAlex
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Descriptive statistics of fitness function results through the 30 executions by each approach optimizing the hyperparameters of the FCNN, GRNN and RBF by data set · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS