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A peer-reviewed article of this preprint also exists.
This version is not peer-reviewed
Submitted:
30 December 2023
Posted:
03 January 2024
You are already at the latest version
ACO | Ant colony optimization |
ANFIS | Adaptive neuro-fuzzy inference system |
ANN | Artificial neural network |
ANSE | Arithmetic mean |
ARIMA | Autoregressive integrated moving average |
ARMA | Auto-regressive moving averageo-regressive m |
BA | Bat algorithm |
BFGS | Broyden-fletcher-goldfarb-shanno |
BSA | Backtracking search algorithm |
BT | Bagged tree |
CC | Coefficient of correlation |
CE | Coefficient of efficiency |
CFBNN | Cascade forward backpropagation neural network |
CNN | Convolutional neural network |
C-QPSO | Cuckoo quantum-behaviour particle swarm optimization |
CSA | Clonal selection algorithm |
DE | Differential evolution |
DE | Differential evolution |
DLCM | Discrete linear cascade model |
DP | Difference in peak |
DPF | Difference in peak flow |
EA | Evolutionary algorithm |
EEMD | Ensemble empirical mode decomposition |
EMD | Empirical model decomposition |
EQp | Error of peak discharge |
ETp | Error of time to peak |
FFBNN | Feed-forward backpropagation neural network |
FMLP | Feed forward multilayer percetptron |
GA | Genetic algorithm |
GBM | Gradient-boosted machine |
GEP | Gene expression programming |
GMC | Gaussian mixture copula |
GP | Genetic programming |
GPR | Gaussian process regression |
GRG | Generalized reduced gradient |
GRP | Gaussian process regression |
GRU | Gated recurrent unit |
GWO | Grey wolf optimizer |
HBSA | Hybrid bat-swarm algorithm |
HPSO | Hybrid particle swarm optimization |
HS | Harmony search |
ICA | Imperialist competitive algorithm |
ICSA | Immune clonal selectio algorithm |
IOA | Index of agreement |
KF | Kalman filter |
KGE | Kling-Gupta efficiency |
KN2K | KNN-KF |
KNN | K-nearest neighbor |
LM | Levenberg-Marquardt |
LMM | Lagrange multiplier |
LSSVM | Least squares support vector machine |
LSTM | Long short-term memory |
MAE | Mean absolute error |
MAPE | Mean absolute percentage error |
MBE | Mean bias error |
MHBMO | Modified honey bee mating optimization |
ML | Mahine Learning |
MLFN | Multilayer-feedforward network |
MLP | Multilayer perceptron |
MRE | Mean relative error |
MSE | Mean square error |
MWLP | MLP-based water level prediction |
NMM | Nonlinear Muskingum model |
NMS | Nelder-mead simplex |
NSE | Nash-Sutcliffe Coefficient |
PCC | Pearson correlation coefficient |
PI | Persistence index |
PSF-HS | Parameter setting free-harmony search |
PSO | Particle swarm optimization |
PWRMSE | Peak-weighted root mean square error |
R2 | Coefficient of determination |
RAPID | Routing application for parallel computation of discharge |
RCM | Rating curve method |
RF | Random forest |
RFR | Random forest regression |
RMSE | Root mean square error |
RNN | Recurrent neural network |
RWLP | RNN-based water level prediction |
SA | Shark algorithm |
SBA | Social-based algorithm |
SDE | Standard deviation of the NSE |
SFLA | Shuffled frog leaping algorithm |
SI | Scatter index |
S-LSM | segmented least square method |
SSE | Sum of squared error |
SSQ | Sum of the square of the deviations between the observed and routed outflows |
SVM | Support vector machine |
SVR | Support vector regression |
TDNN | Time delay neural network |
TDRNN | Time delay recurrent neural network |
TSS | Taylor skill score |
VMD | Variational model decomposition |
WI | Willmott’s index of agreement |
WOA | Weed optimizatio algorithm |
WPANFIS | Wavelet packet-based adaptive neuro-fuzzy inference system |
WPANN | Wavelet packet-based artificial neural network |
XGBoost | Extream gradient boosting |
Paper | No. of citations | Journal | Impact factor | Studied river | Adopted method | Compared models | Modeling performance criteria |
---|---|---|---|---|---|---|---|
[19] | 73 | Hydrological Processes | 3.2 | Walla Walla River, USA | GP | NMM | RMSE, CC |
[15] | 125 | Computers & Geosciences | 8.1 | Kushabhadra River, India | ANN | MIKE 11 HD | RMSE, R2, NSE, IOA, DP |
[16] | 164 | Alexandria Engineering Journal | 6.8 | River Nile, Sudan | ANN | R2, RMSE | |
[13] | 7 | Journal of Applied Mathematics | - | River Wyre, UK | SVM | Muskingum model | SSE |
[20] | 19 | Water Resources Management | 4.2 | Chindwin River, Myanmar | ANN | CE, MRE, EQp, ETp | |
[21] | 46 | Natural Hazards | 3.7 | Kheir Abad River, Iran | ANN (FF-SBA) | FF-GA, FF-PSO, Linear regression, Non-linear regression | R2, MSE |
[22] | 18 | Natural Hazards | 3.7 | Maryam Negar River, Iran | ANN, ANFIS | MAE, RMSE, Bias, SI, SSQ | |
[23] | 40 | Water | 3.4 | Tiber River, Italy | ANN | RCM, GA_RCM, PSO_RCM, ACO_RCM, Saint-Venant, PSO_NMM, ACO_NMM, GA_NMM | EQp, ETp, MAE, RMSE |
[24] | 10 | Theoretical and Applied Climatology | 3.4 | Gharesoo River, Iran | GEP, ANN | Muskingum model | R2, RMSE |
[17] | 53 | Journal of Hydrology | 6.4 | South-to-North water Diversion Project channel, China | MWLP, RWLP, LSTM, GRU | SVM, ANN | RMSE, MAE, NSE, PCC, PI |
[25] | 3 | Hydrology | 3.2 | Tanshui River, Taiwan | EEMD and stepwise regression | CC, RMSE | |
[26] | 4 | Environmental Science and Pollution Research | 5.8 | Turnasuyu Stream, Turkey | LSSVM, PSO-LSSVM, EMD-LSSVM, Wavelet-LSSVM, VMD-LSSVM | MAPE, NSE, MBE, R2 | |
[27] | 1 | Stochastic Environmental Research and Risk Assessment | 4.2 | Mera Stream, Sarisu Stream, Kizilirmak River, Turkey | BT, GBM, KNN, RF, SVM, XGBoost | R2, RMSE, MAE | |
[28] | 0 | Water Supply | 1.7 | Mera River, Turkey | EMD-CFBNN, EME-FFBNN | CFBNN, FFBNN | CC |
[18] | 0 | Environmental Sciences Europe | 5.9 | Tisza River, Central Europe | LSTM | DLCM, MLP, Linear model, | MAE, RMSE, R2, WI |
[14] | 2 | Water | 3.4 | Yangtze River, China | SVR, GPR, RFR, MLP, LSTM, GRU | MAPE, RMSE, NSE, TSS, KGE |
Paper | No. of citations | Journal | Impact factor | Adopted method |
---|---|---|---|---|
[37] | 261 | Journal of Hydraulic Engineering | 2.4 | GA |
[48] | 278 | Journal of the American Water Resources Association | 2.4 | HS |
[39] | 95 | Journal of Irrigation and Drainage Engineering | 2.6 | BFGS |
[19] | 73 | Hydrological Processes | 3.2 | GP |
[43] | 87 | Journal of Hydrologic Engineering | 2.4 | PSO |
[49] | 55 | Journal of Hydrologic Engineering | 2.4 | ICSA |
[38] | 218 | Journal of Hydrologic Engineering | 2.4 | NMS algorithm |
[50] | 65 | Journal of Hydrologic Engineering | 2.4 | Parameter-setting-free HS |
[51] | 55 | Journal of Hydrologic Engineering | 2.4 | DE |
[52] | 157 | Journal of Hydrologic Engineering | 2.4 | BFGS-HS |
[53] | 55 | Neural Computing and Application | 6 | HPSO |
[54] | 15 | Journal of Irrigation and Drainage Engineering | 2.6 | SFLA-NMS |
[55] | 65 | Journal of Hydrologic Engineering | 2.4 | MHBMO algorithm |
[56] | 23 | Journal of Irrigation and Drainage Engineering | 2.6 | WOA |
[57] | 42 | Water Resources Management | 4.3 | PSO |
[58] | 37 | Water Resources Management | 4.3 | MHBMO-GRG |
[1] | 33 | Water Resources Management | 4.3 | BSA evolutionary algorithm |
[59] | 39 | Water | 3.4 | HBSA |
[23] | 40 | Water | 3.4 | PSO, ACO, GA |
[60] | 11 | Water Resources Management | 4.3 | SA |
[61] | 13 | Water Resources Management | 4.3 | PSO-GA |
[62] | 9 | Water & Climate Change | 2.8 | PSO |
[63] | 13 | Water & Climate Change | 2.8 | PSO-LM |
[47] | 4 | MethodsX | 1.9 | GWO algorithm |
[64] | 0 | Neural Processing Letters | 3.1 | C-QPSO |
[65] | 0 | Hydroinformatics | 2.7 | GPR, GMC, RF, XGBoost |
Paper | No. of citations | Journal | Impact factor | Studied river | Adopted method | Compared model | Modeling performance criteria |
---|---|---|---|---|---|---|---|
[67] | 88 | Hydrology and Earth System Science | 6.3 | Neckar River, Germany | ANN & a one-dimensional hydrodynamic numerical model | - | CE, R2, RMSE, DPF |
[66] | 40 | Advances in Geosciences | 1.6 | Freiberger Mulde River, Germany | HEC-RAS & ANN | HEC-RAS | R2 |
[68] | 14 | Water International | 2.6 | Karoon River, Iran | HEC-RAS & adaptive ANNs | HEC-RAS, Muskingum routing method | CE, PWRMSE, mean error of time to peak, volume error of highest peaks |
[69] | 36 | Water and Environment Journal | 2 | Doogh River, Iran | HEC-RAS & ANN; HEC-RAS & ANFIS | HEC-RAS | NSE, MRE, RMSE |
[70] | 64 | International Journal of Sediment Research | 3.6 | Huai River, China | KN2K & one-dimensional hydraulic model | KF & one-dimensional hydraulic model | NSE, ANSE, SDE |
[71] | 101 | Journal of Hydrology | 6.4 | Eden Catchment, UK | LISFLOOD-FP & CNN | LISFLOOD-FP, SVR | NSE, RMSE |
[10] | 0 | Water | 3.4 | Han River, South Korea | HM-ANN | HM, ANN | RMSE, NSE |
[72] | 2 | Ain Shams Engineering Journal | 6 | HEC-RAS & ANN | HEC-RAS, Muskingum method | Standard error, etc. |
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