A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks

Seyed Jalaleddin Mousavirad, Diego Oliva, Gerald Schaefer, Mahshid Helali Moghadam, Mohammed El-Abd

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Determining appropriate weights and biases for feed-forward neural networks is a critical task. Despite the prevalence of gradient-based methods for training, these approaches suffer from sensitivity to initial values and susceptibility to local optima. To address these challenges, we introduce a novel two-level clustering-based differential evolution approach, C2L-DE, to identify the initial seed for a gradient-based algorithm. In the initial phase, clustering is employed to detect some regions in the search space. Population updates are then executed based on the information available within each region. A new central point is proposed in the subsequent phase, leveraging cluster centres for incorporation into the population. Our C2L-DE algorithm is compared against several recent DE-based neural network training algorithms, and is shown to yield favourable performance.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Proceedings
EditorsStephen Smith, João Correia, Christian Cintrano
PublisherSpringer Science and Business Media Deutschland GmbH
Pages259-272
Number of pages14
ISBN (Print)9783031568510
DOIs
StatePublished - 21 Mar 2024
Event27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024 - Aberystwyth, United Kingdom
Duration: 3 Apr 20245 Apr 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14634 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024
Country/TerritoryUnited Kingdom
CityAberystwyth
Period3/04/245/04/24

Keywords

  • clustering
  • Differential evolution
  • neural network training
  • regularisation

Fingerprint

Dive into the research topics of 'A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks'. Together they form a unique fingerprint.

Cite this