There are four layers of processing unit in GRNN model [20]. Each layer of processing units is assigned with a specific computational function when non-linear regression is performed. The first layer of the network is responsible for the reception of information. There is a unique input neuron for each predictable variable in the input vector X. The input neurons feed the data to the second layer. The number of neurons in the second layer is equal to the number of cases in the training set