Design and Develop Artificial Neural Network Model.

Task: $($Multilayer Perceptron $($MLP$)$ for Regression Problem$)($Demonstration $($D$)5\backslash \%,$ Presentation$($P$)5\backslash \%$ and Report $(\backslash (2\mathrm{.}5\backslash \%\backslash )))$: You are provided data from Metrology Station and solar Farm. The task is to develop MLP regression model that can predict solar power output based on data from the metrology station. The model will be useful for a solar power company as an insight prior to constructing a solar farm. $-$ Normalize the data accordingly so that the value will be within the same range.

$-$ Split the data into $70$:$30$ for training $\backslash$& validation.

$-$ Design MLP model that yields a smaller error rate. You can fine tune the model by increasing the hidden neuron number or selecting different types of optimizer $\backslash$& cost function. All groups are required to develop $\backslash$& evaluate minimum two different models and analyze which model that able to produce less error.

$-$ For all the constructed model, plot a graph to compare between the predicted output and the actual output.