Grey Wolf Optimizer for Training Multi-Layer Perceptrons (ALL CLASSIFICATION AND FUNCTION DATASETS)

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 for Training Multi-Layer Perceptrons (all datasets: XOR, Baloon, Iris, Cancer, Heat, Sigmoid, Sine, Cosine, and Sphere): Updated
This is the new version of the following submission:
http://au.mathworks.com/matlabcentral/fileexchange/49772-grey-wolf-optimizer-for-training-multi-layer-perceptrons
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

More information can be found in my personal web page: http://www.alimirjalili.com

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Cite As

Seyedali Mirjalili (2024). Grey Wolf Optimizer for Training Multi-Layer Perceptrons (ALL CLASSIFICATION AND FUNCTION DATASETS) (https://www.mathworks.com/matlabcentral/fileexchange/52273-grey-wolf-optimizer-for-training-multi-layer-perceptrons-all-classification-and-function-datasets), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
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