這是一篇印度那邊學(xué)生的畢業(yè)論文，唯一要記錄的是里面提到了一個(gè)特征構(gòu)造的思想，記錄如下：
論文思想：
特征選用速度、電流、電壓、溫度、平均電壓、平均電流、平均速度，模型用cnn+lstm+lr+lr
平均特征計(jì)算方式：近50個(gè)時(shí)刻的取值求平均。
模型參數(shù)：

# 建立網(wǎng)絡(luò)結(jié)構(gòu)
input_size = 7
hidden_size = 48
output_size = 1
num_layers = 1
rate = 5e-3
epochs = 1500class LSTM_CONV(nn.Module):def __init__(self, input_size = input_size, hidden_size = hidden_size, output_size = output_size,num_layers = num_layers):super(LSTM_CONV, self).__init__()self.conv = nn.Conv1d(in_channels = 1, out_channels = 6, kernel_size = 3, stride = 1)self.rnn = nn.LSTM(5, hidden_size, num_layers)self.reg_1 = nn.Linear(hidden_size, output_size)self.reg_2 = nn.Linear(6, output_size)def forward(self, x):x = self.conv(x)  x, _ = self.rnn(x)  s, b, h = x.shapex = x.view(s * b, h)  x = self.reg_1(x)  x = x.view(s, -1) x = self.reg_2(x) x = x.view(s, 1, 1)  return xnet = LSTM_CONV()
criterion = nn.MSELoss()
optimizer = torch.optim.Adam(net.parameters(), lr = rate, betas = (0.9, 0.999), eps = 1e-08)