I recently realized that I may have over-trained my classification neural network and used too many parameters, so that my weight vectors are too fine-tuned to my particular data set and do not generalize well. I lowered the number of hidden neurons in the network to 15, and the number of epochs to 25000, and regularized based on the deltas (the gradient). Here is the most recent learning curve:

The old weights and code are saved in the c1pem directory in the file "classify_seismic_20neurons.c", while the current 15 neuron network is saved as "classify_seismic.c". I'll monitor the performance of this current network throughout the day, and decide which one we should keep.