نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه مهندسی عمران، واحد اراک، دانشگاه آزاد اسلامی ، اراک ، ایران
2 گروه مهندسی شیمی، واحد اراک، دانشگاه آزاد اسلامی ، اراک ، ایران
3 گروه مهندسی آب، واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه،ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The purpose of this research is to predict fluctuations of the equivalent thickness of underground water using GRACE satellite data and modeling it using a combination of optimization algorithm and artificial intelligence.The study area of this research is the catchment area of Lake Urmia located in the northwest of Iran. For this purpose, 180 GRACE satellite data were used between April 2002 and March 2017. The output of the satellites includes 6 pixels located on the selected watershed, of which 2 points that overlapped the most with the watershed area were selected for modeling with artificial intelligence tools. GA-ANN, ICA-ANN and PSO-ANN hybrid models were used for this purpose. The results showed that the output of the ICA-ANN model had the best fit with the observational data with a correlation coefficient equal to 0.915 and 0.942 in the two selected pixels 2 and 5 in the test phase. Therefore, to predict fluctuations of the equivalent thickness of underground water in the study area, instead of using complex models with a large amount of data, the ICA-ANN model can be used with confidence.This approach helps a lot to the researchers of the underground water sector, without using numerical models with a complex and time-consuming structure, by using satellite information and artificial intelligence tools with high accuracy, the changes in the equivalent thickness of underground water in each month based on Predict the data of the equivalent thickness of underground water in the GRACE satellite for the previous months
کلیدواژه‌ها [English]
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