Research Article
Application of Extreme Learning Machine for Predicting Chlorophyll-a Concentration Inartificial Upwelling Processes
Table 1
Error comparison between different models.
| ā | R-square | RMSE | ME |
| MLR | 0.4528 | 0.2116 | -0.0676 | MLR-updated | 0.4494 | 0.2101 | -0.0619 | MQR | 0.6966 | 0.1951 | 0.1275 | MQR-updated | 0.7084 | 0.1892 | 0.1226 | BP-NN | 0.7060 | 0.1270 | 0.0186 | ELM | 0.5212 | 0.1251 | 0.0193 | GA-ELM | 0.5437 | 0.1241 | 0.0262 | PSO-ELM | 0.6557 | 0.1156 | 0.0357 | ACO-ELM | 0.6913 | 0.1195 | 0.0119 |
|
|