How to optimize neural network by using genetic algorithm?

Question

I'm quite new with this topic so any help would be great. What I need is to optimize a neural network in MATLAB by using GA. My network has [2x98] input and [1x98] target, I've tried consulting MATLAB help but I'm still kind of clueless about what to do :( so, any help would be appreciated. Thanks in advance.

Edit: I guess I didn't say what is there to be optimized as Dan said in the 1st answer. I guess most important thing is number of hidden neurons. And maybe number of hidden layers and training parameters like number of epochs or so. Sorry for not providing enough info, I'm still learning about this.

Answer 1

If this is a homework assignment, do whatever you were taught in class.

Otherwise, ditch the MLP entirely. Support vector regression ( http://www.csie.ntu.edu.tw/~cjlin/libsvm/ ) is much more reliably trainable across a broad swath of problems, and pretty much never runs into the stuck-in-a-local-minima problem often hit with back-propagation trained MLP which forces you to solve a network topography optimization problem just to find a network which will actually train.