Nonlinear Regression Models

These are utilized to design models where the relationship between input variables and output variable cannot be described by a simple linear model. The format of the model usually takes the form of:

Here f is a function of X and (. X represents an input matrix, ( a vector of weights and e a vector of errors or disturbances from an expected outcome.

Artificial neural network is a computational method that strives to mimic the complex interconnections between neurons in a biologic system.

When designing a neural network, the data to be analyzed in randomly distributed into three groups: a training data set, a testing data set and a validation data set.

FIGURE 1 ■ Artificial neural network model.








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