Skip to Main Content
Table 3

Averaged modeling results for surface water levels for five different prediction horizons (from 1 to 5 days ahead)

1 day ahead
2 days ahead
3 days ahead
4 days ahead
5 days ahead
MethodR2σR2σR2σR2σR2σtt (ms)tp (ms)
LinearRegression 0.553 0.069 0.499 0.071 0.487 0.081 0.484 0.081 0.489 0.078 3.7 0.3 
DecisionTreeR 0.350 0.172 0.325 0.161 0.287 0.202 0.294 0.195 0.267 0.302 3.8 0.1 
RandomForestR 0.571 0.106 0.514 0.109 0.492 0.109 0.501 0.111 0.502 0.1 1,194 6.4 
GradientBoostingR 0.572 0.106 0.500 0.088 0.480 0.108 0.480 0.113 0.482 0.109 399.0 0.4 
PLSRegression 0.502 0.065 0.457 0.068 0.450 0.072 0.450 0.071 0.449 0.07 3.0 0.4 
ExtraTreeR 0.350 0.172 0.325 0.161 0.287 0.202 0.294 0.195 0.267 0.302 3.7 0.1 
SVR 0.154 0.059 0.155 0.059 0.156 0.058 0.156 0.058 0.156 0.058 158.6 18.2 
MLP-R 0.538 0.078 0.512 0.077 0.511 0.083 0.511 0.082 0.509 0.082 3,014 1.5 
KNeighborsR 0.507 0.092 0.458 0.095 0.439 0.111 0.435 0.109 0.436 0.103 8.6 12.7 
HoeffdingTreeR 0.312 0.212 0.246 0.203 0.279 0.178 0.284 0.181 0.282 0.18 3,748 39.8 
HAT-R 0.312 0.213 0.218 0.28 0.276 0.183 0.281 0.186 0.279 0.184 4,140 40.1 
LogisticRegression 0.205 0.162 0.212 0.158 0.207 0.167 0.200 0.159 0.206 0.169 110.6 0.2 
DecisionTreeC − 0.066 0.301 − 0.108 0.353 − 0.096 0.35 − 0.09 0.383 − 0.104 0.35 6.3 0.1 
ExtraTreeC − 0.189 0.447 − 0.181 0.403 − 0.163 0.371 − 0.252 0.479 − 0.192 0.455 2.1 0.1 
RandomForestC 0.081 0.241 0.065 0.254 0.069 0.221 0.08 0.224 0.058 0.248 264.5 8.5 
SVC 0.083 0.174 0.130 0.178 0.126 0.173 0.124 0.178 0.135 0.172 167.9 20.1 
KNeighborsC 0.06 0.18 0.047 0.206 0.029 0.206 0.039 0.207 0.037 0.209 8.8 17.6 
Perceptron − 0.121 0.739 − 0.224 0.732 − 0.279 0.964 − 0.14 0.736 − 0.088 0.622 14.0 0.2 
GaussianNB 0.127 0.225 0.143 0.217 0.143 0.219 0.142 0.22 0.139 0.218 1.3 0.4 
HoeffdingTreeC 0.097 0.221 0.111 0.216 0.111 0.218 0.109 0.218 0.111 0.216 1,592 154.7 
HAT-C 0.099 0.218 0.115 0.209 0.108 0.207 0.108 0.206 0.108 0.208 2,694 161.8 
1 day ahead
2 days ahead
3 days ahead
4 days ahead
5 days ahead
MethodR2σR2σR2σR2σR2σtt (ms)tp (ms)
LinearRegression 0.553 0.069 0.499 0.071 0.487 0.081 0.484 0.081 0.489 0.078 3.7 0.3 
DecisionTreeR 0.350 0.172 0.325 0.161 0.287 0.202 0.294 0.195 0.267 0.302 3.8 0.1 
RandomForestR 0.571 0.106 0.514 0.109 0.492 0.109 0.501 0.111 0.502 0.1 1,194 6.4 
GradientBoostingR 0.572 0.106 0.500 0.088 0.480 0.108 0.480 0.113 0.482 0.109 399.0 0.4 
PLSRegression 0.502 0.065 0.457 0.068 0.450 0.072 0.450 0.071 0.449 0.07 3.0 0.4 
ExtraTreeR 0.350 0.172 0.325 0.161 0.287 0.202 0.294 0.195 0.267 0.302 3.7 0.1 
SVR 0.154 0.059 0.155 0.059 0.156 0.058 0.156 0.058 0.156 0.058 158.6 18.2 
MLP-R 0.538 0.078 0.512 0.077 0.511 0.083 0.511 0.082 0.509 0.082 3,014 1.5 
KNeighborsR 0.507 0.092 0.458 0.095 0.439 0.111 0.435 0.109 0.436 0.103 8.6 12.7 
HoeffdingTreeR 0.312 0.212 0.246 0.203 0.279 0.178 0.284 0.181 0.282 0.18 3,748 39.8 
HAT-R 0.312 0.213 0.218 0.28 0.276 0.183 0.281 0.186 0.279 0.184 4,140 40.1 
LogisticRegression 0.205 0.162 0.212 0.158 0.207 0.167 0.200 0.159 0.206 0.169 110.6 0.2 
DecisionTreeC − 0.066 0.301 − 0.108 0.353 − 0.096 0.35 − 0.09 0.383 − 0.104 0.35 6.3 0.1 
ExtraTreeC − 0.189 0.447 − 0.181 0.403 − 0.163 0.371 − 0.252 0.479 − 0.192 0.455 2.1 0.1 
RandomForestC 0.081 0.241 0.065 0.254 0.069 0.221 0.08 0.224 0.058 0.248 264.5 8.5 
SVC 0.083 0.174 0.130 0.178 0.126 0.173 0.124 0.178 0.135 0.172 167.9 20.1 
KNeighborsC 0.06 0.18 0.047 0.206 0.029 0.206 0.039 0.207 0.037 0.209 8.8 17.6 
Perceptron − 0.121 0.739 − 0.224 0.732 − 0.279 0.964 − 0.14 0.736 − 0.088 0.622 14.0 0.2 
GaussianNB 0.127 0.225 0.143 0.217 0.143 0.219 0.142 0.22 0.139 0.218 1.3 0.4 
HoeffdingTreeC 0.097 0.221 0.111 0.216 0.111 0.218 0.109 0.218 0.111 0.216 1,592 154.7 
HAT-C 0.099 0.218 0.115 0.209 0.108 0.207 0.108 0.206 0.108 0.208 2,694 161.8 

Best results by prediction horizon are bolded. Best classification-based results are underlined.

Close Modal

or Create an Account

Close Modal
Close Modal