Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Website thesai.org
Follow Us
Contact Info
Follow Us
Research Article | Open Access |

Visualization of Learning Processes for Back Propagation Neural Network Clustering

Author 1: Kohei Arai
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 4, No. 2 · Published 2013

DOI: https://doi.org/10.14569/IJACSA.2013.040235

Abstract

Method for visualization of learning processes for back propagation neural network is proposed. The proposed method allows monitor spatial correlations among the nodes as an image and also check a convergence status. The proposed method is attempted to monitor the correlation and check the status for spatially correlated satellite imagery data of AVHRR derived sea surface temperature data. It is found that the proposed method is useful to check the convergence status and also effective to monitor the spatial correlations among the nodes in hidden layer.

Keywords

How to Cite this Article

Arai, K. (2013). Visualization of Learning Processes for Back Propagation Neural Network Clustering. International Journal of Advanced Computer Science and Applications, 4(2). https://doi.org/10.14569/IJACSA.2013.040235

Arai, Kohei. "Visualization of Learning Processes for Back Propagation Neural Network Clustering." International Journal of Advanced Computer Science and Applications, vol. 4, no. 2, 2013, https://doi.org/10.14569/IJACSA.2013.040235.

@article{Arai2013,
  title     = {Visualization of Learning Processes for Back Propagation Neural Network Clustering},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {4},
  number    = {2},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJACSA.2013.040235},
  url       = {https://doi.org/10.14569/IJACSA.2013.040235}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.