Multi step ahead forecasting with Radial basis function neural network

I want to forecast multi step (k=6) ahead with Radial basis function neural network (RBFNN) with time series data. I have one output and 2 input variables. The code is given below:
net = newrb(p, t, 0.5)
outputs = net(p)
perf = perform(net, outputs, t)
I am stuck with what to do after this to make multi step ahead prediction?
Please help and thanks in advance.

4 Comments

anurag kulshrestha commented:
The input and output, both are time-series. Input is 90*2 and output is 90*1 time series data.
Save the net..and give the input, you shall get the predicted value.
I want to do multi step forecatsing recursively.

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