سلگی ع، بیگ محمدی ف، احمدوند ر، باصر س.1403. ارزیابی ریسک نیترات در آب آشامیدنی مناطق مختلف شهر ملایر. رویکردهای نوین در مهندسی آب و محیطزیست، دوره 3 شماره 2: 101-117
قره محمودلو م، شیرزادنیا ج. 1402. ارزیابی و مقایسه کیفیت منابع آبی چشمه و چاه از نظر قابلیت شرب و آبیاری (مطالعه موردی: شرق دشت گرگان). رویکردهای نوین در مهندسی آب و محیطزیست، دوره 2 شماره 1: 47-66
Baki, A.M., Ghavami, SM. A. 2023. modified DRASTIC model for groundwater vulnerability assessment using connecting path and analytic hierarchy process methods. Environmental Science and Pollution Research: 1-14.
Brown, RM., McClelland, NI, Deininger RA, Tozer RG. 1970. A water quality index-do we dare. Water and sewage works, 117.
Chicco D, Warrens MJ, Jurman G. 2021.The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. Peerj computer science, 7: e623.
Fausett LV. 2006. Fundamentals of neural networks: architectures, algorithms and applications: Pearson Education India.
Ghaffari, M., Chavoshbashi, AA, Eslami, A., Hatami, H., Pourakbar, M., Hashemi, M. 2021. Spatial and temporal variation of groundwater quality around a volcanic mountain in northwest of Iran. Groundwater for Sustainable Development, 14: 100627.
Gharemahmoodlu, M., Shirzadnia, J. 2023. Assessment and comparison of the spring and well water resources quality for Drinking and Irrigation Purposes (Case study: East of Gorgan plain). Journal of New Approaches in Water and Environmental Engineering, 2(1). 44-67.
Goodarzi MR, Abedi MJ, Niknam ARR, Heydaripour M. 2022. Groundwater quality status based on a modification of water quality index in an arid area, Iran. Water Supply, 22: 6245-6261.
Haykin S. Neural networks and learning machines, 3/E: Pearson Education India, 2009.
Kashaninejad M, Dehghani A, Kashiri M. 2009. Modeling of wheat soaking using two artificial neural networks (MLP and RBF). Journal of food engineering, 91: 602-607.
Kouadri S, Kateb S, Zegait R. 2021. Spatial and temporal model for WQI prediction based on back-propagation neural network, application on EL MERK region (Algerian Southeast). Journal of the Saudi Society of Agricultural Sciences, 20: 324-336.
Khoi, Dao Nguyen, et al. 2022. Using machine learning models for predicting the water quality index in the La Buong River, Vietnam. Water 14.10: 1552.
Kulisz, M, Kujawska, J. 2021. Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland. Journal of Physics: conference series. 2130. IOP Publishing, 012028.
Lahari, K., Supriya, M. 2020. Parallelized Heat Map Algorithm Using Multiple Cores. ICDSMLA 2019: Proceedings of the 1st International Conference on Data Science, Machine Learning and Applications. Springer, 602-610.
Machiwal, D., Cloutier, V., Guler, C., Kazakis, N. 2018. A review of GIS-integrated statistical techniques for groundwater quality evaluation and protection. Environmental Earth Sciences; 77: 1-30.
Organization, W.H. 2008. Guidelines for drinking-water quality: second addendum. Vol. 1, Recommendations.
Sivakumar, M., Parthasarathy, S., Padmapriya, T. 2024.Trade-off between training and testing ratio in machine learning for medical image processing. PeerJ Computer Science; 10: e2245.
Solgi, E. 2024. Beigmohammadi F, Ahmadvand R, Baser S. Nitrate risk assessment in drinking water in different areas of Malayer city. Journal of New Approaches in Water and Environmental Engineering; 3(2). 101-117.
Yousefi, H., Zahedi, S., Niksokhan, MH. 2018. Modifying the analysis made by water quality index using multi-criteria decision making methods. Journal of African Earth Sciences, 138: 309-318.
Zahedi, S., Azarnivand, A., Chitsaz, N. Groundwater quality classification derivation using multi-criteria-decision-making techniques. Ecological Indicators78(7):201-243.
Zhang, B., Hu, X., Li, B., Wu, P., Cai, X., Luo, Y.A. 2024. Groundwater Quality Assessment Model for Water Quality Index: Combining Principal Component Analysis, Entropy Weight Method, and Coefficient of Variation Method for Dimensionality Reduction and Weight Optimization, and Its Application. Water Environment Research, 96: 11155.
