Table 1 CNN-LSTM information fusion technique using entropy identity attributes metrics values.
Epoch | P | B | D | Target | Output | Error |
|---|---|---|---|---|---|---|
\(\:930\) | \(\:1.2\) | \(\:0.8\) | \(\:0.5\) | \(\:0.90\) | \(\:0.88\) | \(\:0.02\) |
\(\:940\) | \(\:1.1\) | \(\:0.7\) | \(\:0.4\) | \(\:0.85\) | \(\:0.82\) | \(\:0.03\) |
\(\:950\) | \(\:1.3\) | \(\:0.9\) | \(\:0.6\) | \(\:0.95\) | \(\:0.92\) | \(\:0.03\) |
\(\:960\) | \(\:1.0\) | \(\:0.6\) | \(\:0.3\) | \(\:0.80\) | \(\:0.77\) | \(\:0.03\) |
\(\:970\) | \(\:1.4\) | \(\:1.0\) | \(\:0.7\) | \(\:1.00\) | \(\:0.98\) | \(\:0.02\) |
\(\:980\) | \(\:1.2\) | \(\:0.8\) | \(\:0.5\) | \(\:0.90\) | \(\:0.87\) | \(\:0.03\) |
\(\:990\) | \(\:1.1\) | \(\:0.7\) | \(\:0.4\) | \(\:0.85\) | \(\:0.83\) | \(\:0.02\) |
\(\:1000\) | \(\:1.3\) | \(\:0.9\) | \(\:0.6\) | \(\:0.95\) | \(\:0.93\) | \(\:0.02\) |
\(\:1010\) | \(\:1.0\) | \(\:0.6\) | \(\:0.3\) | \(\:0.80\) | \(\:0.78\) | \(\:0.02\) |
\(\:1020\) | \(\:1.4\) | \(\:1.0\) | \(\:0.7\) | \(\:1.00\) | \(\:0.99\) | \(\:0.01\) |
\(\:1030\) | \(\:1.2\) | \(\:0.8\) | \(\:0.5\) | \(\:0.90\) | \(\:0.89\) | \(\:0.01\) |
