ANN weight optimization using Cat Swarm Optimization
Version 1.0.0.0 (7.79 KB) by
Kalpesh Patil
This toolbox updates the weights of ANN using CSO method.
ANN weights optimization using CSO has better ability to reach global minima than gradient descent method. This package was developed to predict Sea Surface Temperature anomaly (SSTA) time series for specific lead times. Results of prediction of SSTA with CSO and gradient descent was compared and found that CSO gives 20 to 40% improvement in root mean square error.
Cite As
Kalpesh Patil (2026). ANN weight optimization using Cat Swarm Optimization (https://www.mathworks.com/matlabcentral/fileexchange/67211-ann-weight-optimization-using-cat-swarm-optimization), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Created with
R2016a
Compatible with any release
Platform Compatibility
Windows macOS LinuxCategories
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| Version | Published | Release Notes | |
|---|---|---|---|
| 1.0.0.0 |
