[email protected] +91 9840521421 Scholarly Open Access, Peer-reviewed, Refereed Journal e-ISSN 2582-8746 Since 2020
  1. Home
  2. Archives
  3. 2022
  4. Vol. 3 Issue 4
  5. Article
Research Article

Performance of Momentum Dynamics of Artificial Neural Network in Deep learning neural networks

Open Access Peer Reviewed

Authors

  • Madhav Sharma1

Research Scholar, Computer Science & Engineering Department, Jagannath University, Jaipur, India.

Article Information

DOI
No DOI
Published Online
July-August 2022
Pages
101-105
Article Type
Research Article
Check for updates
No DOI available for cross-reference

Abstract

View PDF

Abstract: The stochastic gradient descent optimization approach is used to train deep learning neural networks in this paper. Artificial neural networks are a subfield of deep learning that uses algorithms inspired by the structure and function of the brain. Deep learning systems are designed to learn feature hierarchies based on the composition of lower level characteristics at the top of the hierarchy. The various sorts of learning models are also discussed. We build a train and dataset with different samples (500, 2000, and 4000) and change the Epochs value in this research (100, 300 and 400).We also create learning curves for different momentums. In This paper we create learning curves for different momentums.

APC from ₹1200 + 18% GST

Peer-reviewed open access₹1200 Indian (₹1400 with DOI)$80 USD internationalpaid after acceptance Peer-reviewed open access₹1200 Indian$80 USD international ₹1200 Indian · $80 intl

  • CrossRef DOI
  • ISSN 2582-8746
  • Open Access
  • Peer Reviewed
  • Plagiarism Checked
  • Google Scholar
Submit Paper