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
I have a number of relevant courses in this area. You can enrol via the following links with 95% discount:
*******************************************************************************************************************************************
A course on “Optimization Problems and Algorithms: how to understand, formulation, and solve optimization problems”:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
A course on “Introduction to Genetic Algorithms: Theory and Applications”
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF
*******************************************************************************************************************************************
引用
Seyedali Mirjalili (2024). Grey Wolf Optimizer for Training Multi-Layer Perceptrons (https://www.mathworks.com/matlabcentral/fileexchange/49772-grey-wolf-optimizer-for-training-multi-layer-perceptrons), MATLAB Central File Exchange. 取得済み .
MATLAB リリースの互換性
プラットフォームの互換性
Windows macOS Linuxカテゴリ
- AI, Data Science, and Statistics > Deep Learning Toolbox > Function Approximation, Clustering, and Control > Function Approximation and Clustering >
- AI, Data Science, and Statistics > Deep Learning Toolbox > Function Approximation, Clustering, and Control > Function Approximation and Clustering > Define Shallow Neural Network Architectures >
タグ
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!NNGWO/
バージョン | 公開済み | リリース ノート | |
---|---|---|---|
1.2 | Typo in the description
|
|
|
1.1.0.0 | The paper has been added to the description |
|
|
1.0.0.0 |
|