Efficiency of adaptive neuro-fuzzy inference system in estimation of Earth's velocity field
محل انتشار: فصلنامه زمین و آمار، دوره: 2، شماره: 1
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 46
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شناسه ملی سند علمی:
JR_JEAST-2-1_002
تاریخ نمایه سازی: 29 بهمن 1402
چکیده مقاله:
The purpose of this paper is estimation of earth velocity field using adaptive neuro-fuzzy inference system (ANFIS) in north-west of Iran. For this purpose, observations of ۲۲ GPS stations are selected from the Azerbaijan local network. At the first step, the velocity field of these stations is estimated with Bernese GNSS software. Then, observations of ۲۰ stations used for training of ANFIS with back-propagation (BP) algorithm. It should be note that the input vector of ANFIS is considered latitude and longitude of the GPS stations and the output is the velocity field (Ve , Vn). After the training step, estimated velocity field with ANFIS in two test stations, are compared and evaluated with the velocity field obtained from GPS. For a more accurate evaluation of the new model, all results are compared with velocity field obtained from the Kriging model. To analyze the error of the models, relative error and root mean square error (RMSE) is used. The averaged relative error of ANFIS and Kriging models obtained in the two test stations for the eastern component of the velocity field is ۸.۶۱% and ۱۸.۹۹%, respectively. Also for northern component, the averaged relative error is ۲۱.۸۴% and ۲۸.۵۱%, respectively. The results show the high accuracy of ANFIS model compared to Kriging in estimation of velocity field.
نویسندگان
Seyyed Reza Ghaffari-Razin
Department of Geoscience Engineering, Arak University of Technology, Arak, Iran
Navid Hooshangi
Department of Surveying Engineering, College of Earth Sciences Engineering, Arak University of Technology, Arak, Iran
Fateme Heydari
Department of Geoscience Engineering, Arak University of Technology, Arak, Iran
Hanie Safari
Department of Geoscience Engineering, Arak University of Technology, Arak, Iran