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A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-).
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2024 (English)In: Lecture Notes in Computer Science, Springer Nature , 2024, p. 259-272Conference paper, Published paper (Refereed)
Abstract [en]

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. 

Place, publisher, year, edition, pages
Springer Nature , 2024. p. 259-272
Keywords [en]
clustering, Differential evolution, neural network training, regularisation
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:miun:diva-51134DOI: 10.1007/978-3-031-56852-7_17Scopus ID: 2-s2.0-85189627585ISBN: 9783031568510 (print)OAI: oai:DiVA.org:miun-51134DiVA, id: diva2:1852088
Conference
27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024
Available from: 2024-04-16 Created: 2024-04-16 Last updated: 2024-04-16Bibliographically approved

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Seyed Jalaleddin, Mousavirad

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CiteExportLink to record
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Citation style
  • apa
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
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