Page 94 - AJWEP-22-6

Heidarnejad, et al.

40. Emiroglu ME, Kisi O. Prediction of discharge coefficient
for trapezoidal labyrinth side weir using a neuro-fuzzy 47. Lukas P, Melesse AM, Kenea TT. Predicting reservoir
approach. Water Resour Manag. 2013;27:1473-1488. sedimentation using multilayer perceptron - artificial
doi: 10.1007/s11269-012-0249-0 neural network model with measured and forecasted
41. Cortes C, Vapnik V. Support-vector networks. Mach hydrometeorological data in gibe-III reservoir, omo-gibe
Learn. 1995;20:273-297. river basin, Ethiopia. J Environ Manag. 2024;359:121018.
doi: 10.1007/BF00994018 doi: 10.1016/j.jenvman.2024.121018
42. Sandamal K, Shashiprabha S, Muttil N, Rathnayake U. 48. Friedman JH. Multivariate adaptive regression splines.
Pavement roughness prediction using explainable and Ann Statis. 1991;19:1-67.
supervised machine learning technique for long-term doi: 10.1214/aos/1176347963
performance. Sustainability. 2023;15(12):9617. 49. Garai S, Paul RK, Yeasin M, Paul AK. CEEMDAN-
doi: 10.3390/su15129617 based hybrid machine learning models for time
43. Ferreira C. Gene expression programming: A new series forecasting using MARS algorithm and PSO-
adaptive algorithm for solving problems. Complex Syst. optimization. Neural Process Lett. 2024;56(2):92.
2001;13:87-129. doi: 10.1007/s11063-024-11552-w
doi: 10.48550/arXiv.cs/0102027 50. Fuladipanah M, Azamathulla HM, Kisi O, Kouhdaragh M,
44. Fuladipanah M, Shahhosseini A, Rathnayake N, et al. Mandala V. Quantitative forecasting of bed sediment
In-depth simulation of rainfall-runoff relationships load in river engineering: An investigation into machine
using machine learning methods. Water Pract Technol. learning methodologies for complex phenomena. Water
2024;19(6):2442-2459. Supply. 2024;24(2):585-600.
doi: 10.2166/wpt.2024.147 doi: 10.2166/ws.2024.017
45. Perera A, Hazi MD, Upaka R. Comparison of different 51. Noori R, Khakpour A, Omidvar B, Farokhnia A.
artificial neural network (ANN) training algorithms to Comparison of ANN and principal component analysis-
predict the atmospheric temperature in Tabuk, Saudi multivariate linear regression models for predicting the
Arabia. MAUSAM. 2021;71(2):233-244. river flow based on developed discrepancy ratio statistic.
doi: 10.54302/mausam.v71i2.22 Expert Syst Appl. 2010;37(8):5856-5862.
46. Agbasi JC, Egbueri JC. Prediction of potentially toxic doi: 10.1016/j.eswa.2010.02.020
elements in water resources using MLP-NN, RBF-NN, 52. Koskinas A, Tegos A, Tsira P, et al. Insights into the
and ANFIS: A comprehensive review. Environ Sci Pollut Oroville dam 2017 spillway incident. Geosciences.
Res Int. 2024;31:30370-30398. 2019;9(1):37.
doi: 10.1007/s11356-024-33350-6 doi: 10.3390/geosciences9010037

Volume 22 Issue 6 (2025) 88 doi: 10.36922/AJWEP025120081