آشوری، رضا.، امامقلی زاده، صمد.، حاجی کندی، هومن.، و جمالی، سعید. (1402). بررسی تغییرات مکانی فرونشست دشت دامغان و پیش‌بینی آن با استفاده مدل شبکه عصبی مصنوعی. فناوری های پیشرفته در بهره وری آب، 3(3)، 87-68. https://doi.org/10.22126/atwe.2023.9801.1065
الصریفی، رسول جواد.، عباس.، شیرین آبادی، رضا.، ربیعی فر، حمید رضا.، و نجارچی، محسن. (1402). پیش بینی نوسانات تراز آب زیرزمینی دشت سنقر با استفاده از روشهای یادگیری ماشین. فناوری های پیشرفته در بهره وری آب، 4(1)، 118-99. https://doi.org/10.22126/atwe.2024.10418.1117
حسنی، قاسم.، محوی، امیرحسین.، ناصری، سیمین.، عرب علی بیک، حسین.، یونسیان، مسعود.، و قریبی، حامد. (1390). طراحی شاخص کیفی آب های زیرزمینی با استفاده از منطق فازی. http://healthjournal.arums.ac.ir/article-1-79-fa.html
سازمان شیلات ایران. (1397). دستورالعمل اجرایی نظارت و کنترل بر کیفیت آب در مراکز تکثیر. معاونت توسعه آبزی پروری: معاونت توسعه آبزی پروری. https://www.fisheries.ir/Articlefile/.docx
شاهینی، شبنم.، فرج پهلو، عبدالحسین.، خادمی زاده، شهناز.، و نادران طحان، مرجان. (1402). ارائه معماری پیشنهادی به کارگیری اینترنت اشیاء در کتابخانه‌ها‌‌ی دانشگاهی ایران. پژوهشنامه پردازش و مدیریت اطلاعات، 38(4)، 1498-1457. https://doi.org/10.22034/jipm.2023.701680
صفائیان توپکانلو، الهه.، مظاهری، سید احمد.، و ملکزاده شفارودی، آزاده. (1395). بررسی کیفیت آب با استفاده از شاخصهای کیفی منابع آب معدن فیروزه نیشابور (شمال غرب شهرستان نیشابور، خراسان رضوی). هفتمین همایش انجمن زمین شناسی اقتصادی ایران، مشهد، ایران. https://profdoc.um.ac.ir/paper-abstract-1049398.html
قمرنیا، هوشنگ.، پالاش، زلیخا.، و پالاش، میثم. (1402، الف). ارزیابی کیفیت آب رودخانه گلین در استان کرمانشاه با استفاده از شاخص NSFWQI. فناوری های پیشرفته در بهره وری آب، 3(2)، 67-51. https://doi.org/10.22126/atwe.2023.9040.1048
قمرنیا، هوشنگ.، پالاش، زلیخا.، و پالاش، میثم. (1402، ب). بررسی کیفی آب رودخانه گلین در استان کرمانشاه با استفاده از شاخص کیفیت آب کانادا (CWQI) جهت احداث مراکز پرورش ماهی. محیط زیست و مهندسی آب، 3(3)، 334-320. https://doi.org/10.22034/ewe.2022.339853.1771
معاونت برنامه ریزی و نظارت راهبردی رییس جمهور. (1388). دستورالعمل پایش کیفیت آب های سطحی (جاری) (نشریه شماره 522). معاونت نظارت راهبردی دفتر فنی و اجرایی: وزارت نیرو، دفتر مهندسی و معیارهای فنی آب و آبفا. https://waterstandard.wrm.ir/uploaded_files/DCMS/WRMResearch_files/522-s.pdf
معاونت محیط زیست انسانی. (1392). شاخص کیفیت آب کشور و طبقه بندی آن. بهمن 1392. دفتر آب و خاک: سازمان حفاظت محیط زیست. https://dl.hsenk.ir/uploads/2023/06/HSEnk-2154.pdf
میربهاری، سید هاشم.، شاه بهرامی، اسدالله،. و پورذاکر عربانی، سودابه. (1402). شناسایی چالشهای پایش کیفیت آب و ارائه راهکاری فناورانه مبتنی بر اینترنت اشیا، نخستین کنفرانس ملی اینترنت اشیا با تمرکز بر صنعت کشاورزی، اهواز، ایران. https://civilica.com/doc/1905139
Al-Sarifi, A. R. J., Shirinabadi, R., Rabieifar, H. R., & Najarchi, M. (2024). Prediction of groundwater level fluctuations in Songhor plain using machine learning methods. Advanced Technologies in Water Productivity, 4(1), 99-118. https://doi.org/10.22126/atwe.2024.10418.1117 [In Persian]
American Public Health Association. (2023), American Water Works Association, Water Environment Federation. Lipps WC, Braun-Howland EB, Baxter TE, eds. Standard Methods for the Examination of Water and Wastewater. 24th ed. Washington DC: APHA Press. https://www.standardmethods.org/doi/10.2105/SMWW.2882.219
Ashoori, R., Imamgholizadeh, S., Hajikandi, H., & Jamali, S. (2023). Investigation of spatial changes in the subsidence of Damghan plain and its prediction using artificial neural network model. Advanced Technologies in Water Productivity, 3(3), 68-87. https://doi.org/10.22126/atwe.2023.9801.1065 [In Persian]
Deputy of Human Environment. (2014). Environmental quality index of the country and its classification. Water and Soil Office: Environmental Protection Organization. https://dl.hsenk.ir/uploads/2023/06/HSEnk-2154.pdf [In Persian]
Deputy of Planning and Strategic Supervision of the President. (2009). Guidelines for monitoring the quality of surface waters (Publication No. 522). Strategic Supervision Deputy, Office of Technical and Executive: Ministry of Energy, Office of Water and Wastewater Engineering Standards. https://waterstandard.wrm.ir/uploaded_files/DCMS/WRMResearch_files/522-s.pdf [In Persian]
Dhok, R. P. (2020). Water Quality Index of Groundwater of Karha River Basin Area, Baramati, India. Journal of Emerging Technologies and Innovation Research, 7, 280-289.
Ghamarnia, H., Palash, Z., & Palash, M. (2023a). Evaluation of water quality of Golin River in Kermanshah Province using NSFWQI index. Advanced Technologies in Water Productivity, 3(2), 51-67. https://doi.org/10.22126/atwe.2023.9040.1048 [In Persian]
Ghamarnia, H., Palash, Z., & Palash, M. (2023b). Evaluation of the water quality of Golin River in Kermanshah Province using the Canadian Water Quality Index for establishing fish farming centers. Environmental and Water Engineering, 9(3), 320-334. https://doi.org/10.22034/ewe.2022.339853.1771 [In Persian]
Haq, K. R. A., & Harigovindan, V. P. (2022). Water quality prediction for smart aquaculture using hybrid deep learning models. Ieee Access, 10, 60078-60098.
Hassani, Q., Mahvi, A., Naseri, S., Arabalibeyk, H., Younesian, M., & Gharibi, H. (2012). Designing a groundwater quality index using fuzzy logic. Retrieved from http://healthjournal.arums.ac.ir/article-1-79-fa.html [In Persian]
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=3bb3f82ffeef4525885c362144343119be5040ab
https://doi.org/10.1109/ACCESS.2022.3180482
https://eprints.glos.ac.uk/id/eprint/6781
https://www.researchgate.net/profile/Rajaram-Dhok/publication/358659911_water_quality_index_of_groundwater_of_karha_river_basin_area_baramati_india/links/620dfaeef02286737ca4ce35/water-quality-index-of-groundwater-of-karha-river-basin-area-baramati-india.pdf
Im, Y., Song, G., Lee, J., & Cho, M. (2022). Deep learning methods for predicting tap-water quality time series in South Korea. Water, 14(22), 3766. https://doi.org/10.3390/w14223766
Iran Fisheries Organization. (2019). Executive guidelines for monitoring and controlling water quality at reproduction centers (Version 1, Document Code: MT/02/031). Aquaculture Development Deputy: Iran Fisheries Organization. https://www.fisheries.ir/Articlefile/.docx [In Persian]
Kachroud, M., Trolard, F., Kefi, M., Jebari, S., & Bourrié, G. (2019). Water quality indices: Challenges and application limits in the literature. Water, 11(2), 361. https://doi.org/10.3390/w11020361
Kumar, S., Tiwari, P., & Zymbler, M. (2019). Internet of Things is a revolutionary approach for future technology enhancement: a review. Journal of Big data, 6(1), 1-21. https://doi.org/10.1186/s40537-019-0268-2
McCabe، M. F., Rodell, M., Alsdorf, D. E., Miralles, D. G., Uijlenhoet, R., Wagner, W., & Wood, E. F. (2017). The future of Earth observation in hydrology. Hydrology and earth system sciences, 21(7), 3879-3914. https://doi.org/10.5194/hess-2017-54
Mirbahari, S. H., Shahbahrami, A., & Arabani, S. P. (2023). Identification of challenges in water quality monitoring and presentation of a technological solution based on the Internet of Things. First National Conference on Internet of Things with a focus on agriculture industry, Ahvaz, Iran. https://civilica.com/doc/1905139 [In Persian]
Nandi, B. P., Singh, G., Jain, A., & Tayal, D. K. (2024). Evolution of neural network to deep learning in prediction of air, water pollution and its Indian context. International Journal of Environmental Science and Technology, 21(1), 1021-1036. https://doi.org/10.1007/s13762-023-04911-y
Nasir, N., Kansal, A., Alshaltone, O., Barneih, F., Sameer, M., Shanableh, A., & Al-Shamma'a, A. (2022). Water quality classification using machine learning algorithms. Journal of Water Process Engineering, 48, 102920. https://doi.org/10.1016/j.jwpe.2022.102920
Nechibvute, A., & Mudzingwa, C. (2013). Wireless sensor networks for scada and industrial control systems. International Journal of Engineering and Technology, 3(12), 1025-1035.
Niknam, A. R. R., Sabaghzadeh, M., Barzkar, A., & Shishebori, D. (2024). Comparing ARIMA and various deep learning models for long-term water quality index forecasting in Dez River, Iran. Environmental Science and Pollution Research, 1-17. https://doi.org/10.1007/s11356-024-32228-x
Nimodiya, A. R., & Ajankar, S. S. (2022). A Review on Internet of Things. International Journal of Advanced Research in Science, Communication and Technology, 113(1), 135-144. https://www.researchgate.net/profile/Aditi-Nimodiya/publication/357783537_A_Review_on_Internet_of_Things/links/649ba1b095bbbe0c6ef8f8cb/A-Review-on-Internet-of-Things.pdf
Noori, A., Bonakdari, H., Morovati, K., & Gharabaghi, B. (2020). Development of optimal water supply plan using integrated fuzzy Delphi and fuzzy electre III methods—Case study of the Gamasiab basin. Expert Systems, 37(5), e12568. https://doi.org/10.1111/exsy.12568
Parker, C., Scott, S., & Geddes, A. (2019). Snowball sampling. SAGE research methods foundations.
Rangzan, K., Kabolizadeh, M., & Karimi, D. (2020). Evaluation of Sentinel-2 and Landsat-8 Satellite images capability and evaluation of image fusion capability in seasonal zoning of NSFWQI and IRWQIsc qualitative indices in surface water. Geography and Environmental Planning, 31(1), 73-102. https://doi.org/10.22108/gep.2020.123228.1309
Saeed, A., Alsini, A., & Amin, D. (2024). Water quality multivariate forecasting using deep learning in a West Australian estuary. Environmental Modelling & Software, 171, 105884. https://doi.org/10.1016/j.envsoft.2023.105884
Safaian Toopkanloo, E., Mozaheri, S. A., & Malekzadeh Shafaroudi, A. (2015). Assessment of water quality using quality indices of Firouzeh mineral water resources in Nishapur (northwest of Nishapur city, Razavi Khorasan). Seventh Symposium of the Iranian Economic Geology Association, Mashhad, Iran. https://profdoc.um.ac.ir/paper-abstract-1049398.html [In Persian]
Shahini, S., Farajpahlou, A., Khadami Zadeh, S., & Naderan Tahan, M. (2023). Presenting a proposed architecture for employing the Internet of Things in Iranian academic libraries. Journal of Information Processing and Management, 38(4), 1457-1498. https://doi.org/10.22034/jipm.2023.701680 [In Persian]
Shamsuddin, I. I. S., Othman, Z., & Sani, N. S. (2022). Water quality index classification based on machine learning: A case from the Langat River Basin model. Water, 14(19), 2939. https://doi.org/10.3390/w14192939
Shokoohi, A. R., & Modaberi, H. (2019). Evaluating and comparing the sensitivity of NSFWQI and IRWQISC models to water quality parameters. Iran-Water Resources Research, 14(5), 118-132. https://www.iwrr.ir/article_65746_en.html?lang=fa
Vellingiri, J., Kalaivanan, K., Gopinath, M. P., Gobinath, C., Subramaniam, P. R., & Rangarajan, S. (2023). Strategies for classifying water quality in the Cauvery River using a federated learning technique. International Journal of Cognitive Computing in Engineering, 4, 187-193. https://doi.org/10.1016/j.ijcce.2023.04.004
Vo, D. T., Nguyen, X. P., Nguyen, T. D., Hidayat, R., Huynh, T. T., & Nguyen, D. T. (2021). A review on the internet of thing (IoT) technologies in controlling ocean environment. Energy sources, Part A: Recovery, utilization, and environmental effects, 1-19. https://doi.org/10.1080/15567036.2021.1960932
Wang, Y., Zhou, J., Chen, K., Wang, Y., & Liu, L. (2017). Water quality prediction method based on LSTM neural network. In 2017 12th international conference on intelligent systems and knowledge engineering (pp. 1-5). IEEE. https://doi.org/10.1109/ISKE.2017.8258814
William, P., Oyebode, O. J., Ramu, G., Gupta, M., Bordoloi, D., & Shrivastava, A. (2023). Artificial intelligence-based models to support water quality prediction using machine learning approach. In 2023 International Conference on Circuit Power and Computing Technologies, 1495-1501. IEEE. https://doi.org/10.1109/ICCPCT58313.2023.10245020
Yadegari, F., & Asoosheh, A. (2023). Presenting a smart hospital services model based on the Internet of Things. Journal of Health and Biomedical Informatics, 9(4), 267-276. http://dx.doi.org/10.34172/jhbmi.2023.06 [In Persian]
Zainurin, S. N., Wan Ismail, W. Z., Mahamud, S. N. I., Ismail, I., Jamaludin, J., Ariffin, K. N. Z., & Wan Ahmad Kamil, W. M. (2022). Advancements in monitoring water quality based on various sensing methods: a systematic review. International Journal of Environmental Research and Public Health, 19(21), 14080. https://doi.org/10.3390/ijerph192114080
Zhi, W., Appling, A. P., Golden, H. E., Podgorski, J., & Li, L. (2024). Deep learning for water quality. Nature Water, 1-14. https://doi.org/10.1038/s44221-024-00202-z
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