Table 3.
Essential parameters used in model training.
| Name of parameter | Essential parameters |
|---|---|
| Q-learning | |
| Maximum iteration | 50 |
| Learning rate | 0.95 |
| Discount parameter | 0.5 |
| GRU | |
| Size of input units | 3/5/7/9 |
| Size of hidden units | 100 |
| Size of output units | 1 |
| Number of the Hidden layers | 16 |
| Optimizer | Adam |
| Learning rate | 0.01 |
| Training epochs | 200 |
| DBN | |
| Size of input units | 3/5/7/9 |
| Size of hidden units | 20 |
| Size of output units | 1 |
| number of the Hidden layer | 1 |
| Momentum factor | 0 |
| Optimizer | Adam |
| Learning rate | 0.01 |
| Training epochs | 200 |
| TCN | |
| Size of input units | 3/5/7/9 |
| Size of hidden units | 60 |
| Size of output units | 1 |
| number of the Hidden layer | 6 |
| Learning rate | 0.01 |
| Optimizer | Adam |
| Filter size | 2 |
| Training epochs | 100 |
| Dropout | 0.05 |
| SVM | |
| Size of input units | 3/5/7/9 |
| Size of output units | 1 |
| Kernel function | RBF |
| Gamma | 10 |
| σ2 | 20 |