%% PSO Neural Network Classification % So, there was no proper evolutionary classification Matlab code in the web, % Which decided to make one with PSO. % This code gets data input for classification which contains data and % labels and stores it into 'netdata'. data consists of 300 samples for 6 % classes which includes 40 features. You can extract your features and % label it as it is a supervised model. These features are extracted SURF % features out of small objects images. Now, System is combination of PSO % and typical shallow neural network. Neural network itself makes the % initial structure or body of the system but PSO has duty of weighting the % neurons in training, which true power of evolutionary algorithms present % here. Finally, result compared with SVM, KNN, and TREE classification % algorithms as confusion matrix and final recognition accuracy. % There are three important parameters of 'NH' (number of hidden layers), % 'SwarmSize' and 'MaxIteration' which effect the performance of thee % system significantly. So, in order to get desired result, you should play % with these parameters based on your data. The only drawback here is that % labeling is done manually, which you can fix it yourself easily, but it % is after main stage of training. This code could be expanded to be % trained with other evolutionary algorithms such as GA or DE. If you find % any problem, please contact me as below:
% Email: mosavi.a.i.buali@gmail.com % Author: Seyed Muhammad Hossein Mousavi
% Also this code is part of the following project, so please cite below % after using the code:
% Mousavi, Seyed Muhammad Hossein, et al. "A PSO fuzzy-expert system: As an % assistant for specifying the acceptance by NOET measures, at PH. D % level." 2017 Artificial Intelligence and Signal Processing Conference % (AISP). IEEE, 2017.
% Thank you for citing the paper and enjoy the code (hope it help you (Be happy :)
