I´m sort of a new to neural networks and need some help. I´m working on a project that simulates a blast furnace and forcasts the silicon content of the molten metal output. I´ve tried many different combinations, sadly i haven´t had any real breakthrough. The best combination so far, that still doesn´t return satsfying results, is a 2 layer network:
180 neurons – TANSIG
1 neuron – PURELIN
Training = LM
I have 11 vectors of 1000 elements as input, some range from 0-10 some from 1300-1500. The target vector is the same size ranging from 0-3.
Any ideas on what I should do?
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