ANN weight optimization using Cat Swarm Optimization

This toolbox updates the weights of ANN using CSO method.
700 Downloads
Updated 4 May 2018

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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 Linux
Version Published Release Notes
1.0.0.0