Question 5: (20 Marks) Assuming that you were asked to apply the genetic algorithm to train the model in Question 1. Explain how you would do it. Throw an example in your elaboration using diagrams and mathematics. Design a neural network of three layers, the first layer has two neuronn nt and ne (200) Marks) inputs 1=3.2 and 2=2.8, the hidden layer has two neurons n3 and m, and and na recancing has two neurons n5 and n6 with desired outputs d1=0.81 and d2=0.11 renpectively in the output layer. The hidden weights are w13=0.85, w 14=0.9,w23=0.77, w24 =0.9, w 03=0.6, w04 =0.62. And the hidden to output weights are w35=0.70,w36=0.70,w45=0.60,w46=0.60,w05=0.50,w06=0.40 Find and compare the error of the network in the following cases: a) All hidden and output neurons employ Binary Sigmoid Functions. b) All hidden and output neurons employ Hyperbolic Tangent Activation Functions