Grey Wolf Optimizer for Training Multi-Layer Perceptrons

The submission employs the recently proposed Grey Wolf Optimizer for training Multi-Layer Perceptron
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Updated 22 May 2018

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Grey Wolf Optimizer (GWO) is employed as a trainer for Multi-Layer Perceptron (MLP). The current source codes are the demonstration of the GWO trainer for solving the "Iris" classification problem.
This is the demonstration source codes of the paper:
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

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Cite As

Seyedali Mirjalili (2026). Grey Wolf Optimizer for Training Multi-Layer Perceptrons (https://se.mathworks.com/matlabcentral/fileexchange/49772-grey-wolf-optimizer-for-training-multi-layer-perceptrons), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Version Published Release Notes
1.2

Typo in the description
Links added:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF

1.1.0.0

The paper has been added to the description

1.0.0.0