Research Article
BibTex RIS Cite

Year 2006, , 0 - 0, 01.01.2006

Murat H. Sazlı

https://doi.org/10.1501/commua1-2_0000000026
Cited By: 10

Abstract

References

  • Communications, Series A2-A3: Physical Sciences and Engineering

A brief review of feed-forward neural networks

Year 2006, , 0 - 0, 01.01.2006

Murat H. Sazlı

https://doi.org/10.1501/commua1-2_0000000026
Cited By: 10

Abstract

Artificial neural networks, or shortly neural networks, find applications in a very wide spectrum. In this paper, following a brief presentation of the basic aspects of feed-forward neural netvvorks, their mostly used leaming/training algorithm, the so-called back-propagation algorithm, have been described.

Keywords

Artificial neural networks feed-forward neural networks back-propagation algorithm

References

  • Communications, Series A2-A3: Physical Sciences and Engineering
There are 1 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Murat H. Sazlı This is me

Publication Date January 1, 2006
Submission Date January 1, 2006
Published in Issue Year 2006

Cite

APA Sazlı, M. H. (2006). A brief review of feed-forward neural networks. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, 50(01). https://doi.org/10.1501/commua1-2_0000000026
AMA Sazlı MH. A brief review of feed-forward neural networks. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. January 2006;50(01). doi:10.1501/commua1-2_0000000026
Chicago Sazlı, Murat H. “A Brief Review of Feed-Forward Neural Networks”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 50, no. 01 (January 2006). https://doi.org/10.1501/commua1-2_0000000026.
EndNote Sazlı MH (January 1, 2006) A brief review of feed-forward neural networks. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 50 01
IEEE M. H. Sazlı, “A brief review of feed-forward neural networks”, Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng., vol. 50, no. 01, 2006, doi: 10.1501/commua1-2_0000000026.
ISNAD Sazlı, Murat H. “A Brief Review of Feed-Forward Neural Networks”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 50/01 (January 2006). https://doi.org/10.1501/commua1-2_0000000026.
JAMA Sazlı MH. A brief review of feed-forward neural networks. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2006;50. doi:10.1501/commua1-2_0000000026.
MLA Sazlı, Murat H. “A Brief Review of Feed-Forward Neural Networks”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, vol. 50, no. 01, 2006, doi:10.1501/commua1-2_0000000026.
Vancouver Sazlı MH. A brief review of feed-forward neural networks. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2006;50(01).

Cited By

A comprehensive survey on deep learning‐based intrusion detection systems in Internet of Things (IoT)
Expert Systems
https://doi.org/10.1111/exsy.13726
Strategies to Measure Soil Moisture Using Traditional Methods, Automated Sensors, Remote Sensing, and Machine Learning Techniques: Review, Bibliometric Analysis, Applications, Research Findings, and Future Directions
IEEE Access
https://doi.org/10.1109/ACCESS.2023.3243635
DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction
BMC Genomics
https://doi.org/10.1186/s12864-023-09796-2
Alternating Transfer Functions to Prevent Overfitting in Non-Linear Regression with Neural Networks
Journal of Experimental & Theoretical Artificial Intelligence
https://doi.org/10.1080/0952813X.2023.2270995
https://doi.org/
Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art review
Fuel
https://doi.org/10.1016/j.fuel.2023.129265
Fault Diagnosis in Bevel Gearbox Using Coiflet Wavelet and Fault Classification Based on ANN Including DNN
Arabian Journal for Science and Engineering
https://doi.org/10.1007/s13369-022-06767-9
Solving musculoskeletal biomechanics with machine learning
PeerJ Computer Science
https://doi.org/10.7717/peerj-cs.663
Evolutionary optimization of machine learning algorithm hyperparameters for strength prediction of high-performance concrete
Asian Journal of Civil Engineering
https://doi.org/10.1007/s42107-023-00698-y
https://doi.org/

Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.