Week Four

Week 4

In week Four, most of the programming and plotting was made:

1) Comparison of pre_exp:
The predicted data generated by the trained Neural Network programme are compared with the experimental data. In the graph, predicted data are on y-axis.


scatter (exp_conversion, pre_conversion)



scatter (exp_efficiency, pre_efficiency)

2) Effect of parameters:
The experimental data and simulated data are combined together to investigate the effect of the 4 parameters on convesion rate and energy efficiency respectively.




3) Importance of parameters:
The 4 parameters are constrained in the same range and see the change of conversion and energy efficiency within that range caused by the increment of different parameters are shown on the graph. From the trend of the lines on the graph, the importance of parameters can be observed.


4) Neuron number:
The Neural Network for this programme has 2 layers. In order to find the best fit of neuron number for each layer, the effect of different neuron number combinations is compared by the 3-D graph.