ARTIFICIAL NEURAL NETWORKS APPLIED TO POWER SYSTEMS

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Q4 A neurons have an inputs given by P=[1 0.2 0.4 0.6], and weights W= (-0.4 1 -1 1]t with a sigmoid activation function, 1- Determine the output. 2- It will be desired to use a back-propagation algorithm by adding a hidden layer with three neurons to get the same output in step 1, a- Draw the NNs with one hidden neuron has a bias of 0.3, (show all connection weight assumed values on the graph). b- If all hidden neurons have a threshold of 0.1, find the actual output. C- Find the new adjustment weights for any two hidden neurons with the output neuron. Q4 A neurons have an inputs given by P=[1 0.2 0.4 0.6], and weights W= (-0.4 1 -1 1]t with a sigmoid activation function, 1- Determine the output. 2- It will be desired to use a back-propagation algorithm by adding a hidden layer with three neurons to get the same output in step 1, a- Draw the NNs with one hidden neuron has a bias of 0.3, (show all connection weight assumed values on the graph). b- If all hidden neurons have a threshold of 0.1, find the actual output. C- Find the new adjustment weights for any two hidden neurons with the output neuron