Specific activities and the corresponding degree of failure

Open MATLAB and double click .mat file will load the data set. DataSet4.mat is the data set with input of 4 specific activities. DataSet6.mat is the data set with input of 6 specific activities. DataSet23.mat is the data set with input of 23 specific activities. After opening the file, input_norm is the normalized specific activities, input_max is the maximum specific activities, input_min is the minium specific activies, and the target is the corresponding one-hot encoding degree of failure. For example, {1,0,0,0,0,0} is failure of degree 1, {0,0,1,0,0,0} is failure of degree 3. Input of the function TrainN is number of neurons in the hidden layer1. For example, running TrainN(10) will train the neural network with 10 neurons in the hidden layer 1.打开MATLAB软件后，双击.mat格式文件即可加载对应数据集。 DataSet4.mat为包含4种特定活动输入的数据集；DataSet6.mat为包含6种特定活动输入的数据集；DataSet23.mat为包含23种特定活动输入的数据集。 加载该数据集后，其中input_norm为归一化后的特定活动数据，input_max为特定活动数据的最大值，input_min为特定活动数据的最小值，target为对应的故障程度独热编码（one-hot encoding）。例如，{1,0,0,0,0,0}代表故障等级1，{0,0,1,0,0,0}代表故障等级3。 TrainN函数的输入参数为隐藏层1的神经元数量。例如，执行TrainN(10)即可训练隐藏层1包含10个神经元的神经网络。