Lightweight Neural Networks-Based Safety Evaluation for Smart Construction Devices

Table 2

Multiple neural network simulations at the end of training.

Multiple neural network case	Test training simulations
Kinds = data.iloc[:, 0]	Of hidden layer nodes in
Labels = data.iloc[:, 2:].columns	Increasing the number of hidden layer
Centers = pd.concat([data.iloc[:, 2:], data.iloc[], axis = 1)	The first column of
Plt.figure(figsize = (6, 4))	The second column is
Plt.contourf(x, y, z)	The last are those to
Ax.plot(angles, centers[i], lw = 2, label = kinds[i])	Of each cluster
Ax.fill(angles, centers[i])	Describe the center
X = np.arange(1, st.tot_det-1, st.step)	The number x, y, z = x_list, y_list, z_list
Y = np.arange(1, st.tot_det-1, st.step)	Management system
X, Y = np.meshgrid(x, y)	Consider increasing the number
Z = np.mat(an)	This error is unacceptable