FDO-MLP

Version 1.0.0 (19.1 KB) by Tarik Rashid
FDO-MLP is developed by Dosti K Abbas and Tarik A. Rashid
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Updated 17 May 2022
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This data is a matlab coding. It is an implementation of a research work using Fitness Dependent Optimizer (FDO) algorithm for training a Multilayer Perceptron Neural Network (MLP), which is in the process of submitting to a journal.

Cite As

Cite the following articles: J. M. Abdullah and T. A. Rashid (2019). Fitness Dependent Optimizer: Inspired by the Bee Swarming Reproductive Process," in IEEE Access, vol. 7, pp. 43473-43486. DOI:https://doi.org/10.1109/ACCESS.2019.2907012 Rashid TA, Abbas DK, Turel YK (2019) A multi hidden recurrent neural network with a modified grey wolf optimizer. PLoS ONE 14(3): e0213237. https://doi.org/10.1371/journal.pone.0213237 Tarik A. Rashid and Nian Kh. Aziz (2016) Student Academic Performance Using Artificial Intelligence. ZANCO Journal of Pure and Applied Sciences, The official scientific journal of Salahaddin University-Erbil, ZJPAS, 28 (2); 56-69.https://doi.org/10.21271/zjpas.v28i2.544 Tarik A. Rashid (2015). Improvement on Classification Models of Multiple Classes through Effectual Processes. International Journal of Advanced Computer Science and Applications(IJACSA), 6(7). http://dx.doi.org/10.14569/IJACSA.2015.060709 S. Mirjalili, How effective is the GreyWolf optimizer in training multi-layer perceptrons, Applied Intelligence, In press, 2015, DOI: http://dx.doi.org/10.1007/s10489-014-0645-7

MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.