قیاس روش‌های شبکه عصبی مصنوعی و ماشین بردار پشتیبان در پیش‌بینی پارامترهای کیفیت آب رودخانه دیناچال

Abbasi, A., Khalili, K., Bahmanesh, J & Shirzad, A. (2020). Application of Support Vector Machine and Bayesian Network for Agricultural Drought Prediction. Journal of Watershed Engineering and Management, 107-124 and (1)12. (In Persian)

Abobakr Yahya, A. S. Ahmed, A. N. Binti Othman, F. Ibrahim, R. K. Afan, H. A. El-Shafie, A. & Elshafie, A. (2019). Water Quality Prediction Model-Based Support Vector Machine Model for ungauged River Catchment under Dual Scenarios. Water, 11(6), 1231.‏

Ahmadi, F., Radmanesh, F & Mirabbasi Najaf Abadi, R. (2015). Comparison between Genetic Programming and Support Vector Machine Methods for Daily River Flow Forecasting (Case Study: Barandoozchay River). Journal of Water and Soil, 1162-1171 and 28 (6). (In Persian)

Amini, A., Nouri, HA & Aslani Sangdeh, B. (2015). Evaluation of Rice Production Sustainability Using Multi-Criteria Decision-Making Methods: The Case of Razvanshahr County. Agricultural Education and Extension Sciences of Iran, 126-101(1)11. (In Persian)

Banejad, H. and E. Olyaie (2011). "Application of an Artificial Neural Network Model to Rivers Water Quality Indexes Prediction–A Case Study." Journal of American Science Journal of American Science, 77: 60-65.

Chia, S. L. Chia, M. Y. Koo, C. H. & Huang, Y. F. (2022). Integration of Advanced Optimization Algorithms into Least-Square Support Vector Machine (LSSVM) for Water Quality Index Prediction. Water Supply, 22(2), 1951-1963.

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Gorashi, F. & Abdullah, A. (2012). Prediction of Water Quality Index Using Back Propagation Network Algorithm Case Study: Gombak River. Journal of Engineering Science and Technology, 7(4), 447-461.‏

Hosseinpanahi, B., Nikmehr, S & Ebrahimi, K. (2021). Comparison of the Support Vector Machine Models and Radial Function Neural Network in Predicting SiminehRood River Water Quality Iran. Water and Irrigation Management, 409-419 and (3)11. (In Persian)

Huang, M. Tian, D. Liu, H. Zhang, C. Yi, X. Cai, J., & Ying, G. (2018). A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers. Complexity, 2018, 1-11.‏

Iraji, M., Movahedi Naeini, SA., Komaki, CB., Ebrahimi, S & Yaghmaei, B. (2023). Evaluation of the Effective Parameters for Predicting the Potassium Grade of Saline Water by Using Support Vector Machine and Random Forest Algorithms (Case Study: Playa of Khoor and Biabank Area City, Isfahan Province). Iran water and soil research. (In Persian)

Jamali, B & Ebrahimi, K. (2011). Time Series Forecasting of Sefidrood River Water Quality Using Linear Stochastic Models. Journal of Agricultural Engineering Research, 31-44 and (3)12. (In Persian)

Li, Q., Yang, Y., Yang, L., & Wang, Y. (2023). Comparative Analysis of Water Quality Prediction Performance Based on LSTM in the Haihe River Basin, China. Environmental Science and Pollution Research, 30(3), 7498-7509.‏

Mahapatra, S. S., Nanda, S. K., & Panigrahy, B. K. (2011). A Cascaded Fuzzy Inference System for Indian River Water Quality Prediction. Advances in Engineering Software, 42(10), 787-796.‏

Mohammadi Ghaleni, M., Ebrahimi, K & Omid, MH. (2015). Estimation of Rearation Rate Coefficient on Dinachal River Numerical Methods in Water Quality Management. Water and Irrigation Management, 79-69(1)5. (In Persian)

Najwa Mohd Rizal, N., Hayder, G., Mnzool, M., Elnaim, B. M., Mohammed, A. O. Y., & Khayyat, M. M. (2022). Comparison between Regression Models, Support Vector Machine (SVM), and Artificial Neural Network (ANN) in River Water Quality Prediction. Processes, 10(8), 1652.‏

Pedregosa, F., et al. (2012). "Scikit-learn: Machine Learning in Python." Journal of Machine Learning Research 12.

Rohmah, M. F., et al. (2021). "Comparison Four Kernels of SVR to Predict Consumer Price Index." Journal of Physics: Conference Series 1737(1): 012018.

Roshangar, K & Davoudi, S. (2022). Comparing the Performance of Deep Learning and Machine Learning Methods in Predicting Dissolved Oxygen Content. Iran soil and water research, 1885-1900(8)53. (In Persian)

Sakaa, B., Elbeltagi, A., Boudibi, S., Chaffaï, H., Islam, A. R. M. T., Kulimushi, L. C., & Wong, Y. J. (2022). Water Quality Index Modeling Using Random Forest and Improved SMO Algorithm for Support Vector Machine in Saf-Saf River Basin. Environmental Science and Pollution Research, 29(32), 48491-48508.‏‏

Sattari, M., Abbasgoli Naebzad, M & Mirabbasi Najafabadi. (2014). Surface Water Quality Prediction Using Decision Tree Method. Iranian Journal of Irrigation and Water Engineering, 88-86(3)4. (In Persian)

Shahinejad, B., Izadi, Z & Javadi, B (2021). Evaluation of Qual2Kw Model in Qualitative Simulation of Khorramabad River. Hydrogeomorphology. Volume 8, Number 26. (In Persian)

Sillberg, C.V., Kullavanijaya, P., & Chavalparit, O. (2021). Water Quality Classification by Integration of Attribute-Realization and Support Vector Machine for the Chao Phraya River. Journal of Ecological Engineering, 22 (9), 70-86

Veisi, M & Mohammadi Rouzbahani, M. (2021). Survey on Shavoor River Using Water Quality Indexes (Hamzeh village to Shavoor dam). Environmental Science and Technology Quarterly, 23-81(5)-93. (In Persian)

Yan, J., Liu, J., Yu, Y., & Xu, H. (2021). Water Quality Prediction in the Luan River based on 1-drcnn and bigru Hybrid Neural Network Model. Water,13 (9), 1273.‏