MATLAB: How can use static feedforward neural network to predict futre observation

neural networksstatic feedforward neural network

As newff the appropriate choice or we must use others functions like feedforwardnet???

Best Answer

The generic NEWFF and special cases that call it (e.g., NEWFIT(regression/curvefitting) and NEWPR(Classification/pattern-recognition) ) are obsolete.

Use the current special cases FITNET(regression/curvefitting) and PATTERNNET(Classification/pattern-recognition,...) that call the generic FEEDFORWARDNET.

In your case it looks like FITNET.

However, why don't you want to use a dynamic net?

Hope this helps.

Thank you for formally accepting my answer

Greg

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MATLAB: By including a moving window of fixed length in the input vector of MLP, is the Back-propagation ANN equivalent to NAR model

1. When you insert code try to make sure it runs.

 N= lenght(data);  % ERROR

 d=timestep ahead; % ERROR

2. Replace TRAIN with ADAPT

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: Normalize Inputs and Targets of neural network

MAPMINMAX can be inappropriate only if there are outliers.

Use MAPSTD to detect outliers that can be removed or modified.

Hope this helps.

Thank you for formally accepting my answer

Greg

Best Answer

Related Solutions

MATLAB: By including a moving window of fixed length in the input vector of MLP, is the Back-propagation ANN equivalent to NAR model

MATLAB: Normalize Inputs and Targets of neural network

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