Introduction
Sliding window technique, artificial neural networks
Network structures
Effective parameter | Values/types |
---|---|
No. of input neurons | 1–10 |
No. of hidden layers | 1–2 |
No. of neurons in hidden layer | 1–13 |
Transfer functions | Tansigmoid, Logsigmoid |
Comparison function | MSE |
Statistical indices for performance evaluation
Statistical index | Expression |
---|---|
RMSE | |
R
2
| |
MBE |
Results and discussion
Transfer function | No. of neurons in hidden layers | MSE | RMSE |
R
2
|
---|---|---|---|---|
Logsig | 4 | 1.5303 | 1.2371 | 0.8397 |
Logsig | 5 | 1.4863 | 1.2191 | 0.8421 |
Logsig | 7 | 1.4689 | 1.2120 | 0.8442 |
Logsig | 10 | 1.4890 | 1.2203 | 0.8426 |
Logsig | 13 | 1.4854 | 1.2188 | 0.8427 |
Tansig | 4 | 1.4896 | 1.2206 | 0.8418 |
Tansig | 5 | 1.4758 | 1.2148 | 0.8433 |
Tansig | 7 | 1.4770 | 1.2153 | 0.8438 |
Tansig | 10 | 1.4749 | 1.2145 | 0.8435 |
Tansig | 13 | 1.4796 | 1.2164 | 0.8434 |
Tansig–Logsig | 7–7 | 1.4742 | 1.2142 | 0.8436 |
Tansig–Logsig
|
7–13
|
1.4430
|
1.2012
|
0.8472
|
Tansig–Logsig | 10–7 | 1.4586 | 1.2077 | 0.8454 |
Tansig–Logsig | 10–13 | 1.4697 | 1.2123 | 0.8442 |
Logsig–Tansig | 13–7 | 1.4544 | 1.206 | 0.8458 |
Logsig–Tansig | 7–13 | 1.6862 | 1.2985 | 0.8221 |
Network | Best structure |
R
2
| RMSE | MSE |
---|---|---|---|---|
MLP | 4-7-13-1 | 0.85 | 1.19 | 1.43 |
RBF | 4-25-1 | 0.83 | 1.36 | 1.84 |