Solving the local positioning problem using a four-layer artificial neural network

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Kaveh Mehrdad; MESGARI MOHAMMAD SAADI; KHOSRAVI ALI

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Journal: ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY Year:2020 | Volume:7 | Issue:4 Page(s): 21-40

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Title

Solving the local positioning problem using a four-layer artificial neural network

Author(s)

Kaveh Mehrdad | MESGARI MOHAMMAD SAADI | KHOSRAVI ALI | Issue Writer Certificate

Keywords

Local positioning system (LPS)Q1

artificial neural network based on nonlinear system solver (NLANN)Q1

gauss-newton (GN)Q1

genetic algorithm (GA)Q1

hybrid particle swarm optimization (HPSO)Q1

Abstract

Today, the global positioning systems (GPS) do not work well in buildings and in dense urban areas when there is no lines of sight between the user and their satellites. Hence, the local positioning system (LPS) has been considerably used in recent years. The main purpose of this research is to provide a four-layer artificial neural network based on nonlinear system solver (NLANN) for local positioning problem. To evaluate the performance of artificial neural network, three methods of gauss-newton (GN), genetic algorithm (GA) and hybrid particle swarm optimization (HPSO) have been used. The results indicate that the proposed model has high accuracy. The accuracy of the artificial neural network on the simulated data is 0. 05 m, while the best accuracy in other algorithms is about 0. 45 meters. In the data of Italy's GPS network, the artificial neural network has been reached to accuracy below 10 cm in one minute. Also, artificial neural network has better accuracy in different dimensions of study area and different signal to noise ratio (SNR), and by increasing the number of stations, it has achieved good results in less time. Whereas other algorithms have not get well accuracy. However, the HPSO has better results related to GA and GN algorithms.

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APA: Copy

Kaveh, Mehrdad, MESGARI, MOHAMMAD SAADI, & KHOSRAVI, ALI. (2020). Solving the local positioning problem using a four-layer artificial neural network. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, 7(4 ), 21-40. SID. https://sid.ir/paper/230160/en

Vancouver: Copy

Kaveh Mehrdad, MESGARI MOHAMMAD SAADI, KHOSRAVI ALI. Solving the local positioning problem using a four-layer artificial neural network. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY[Internet]. 2020;7(4 ):21-40. Available from: https://sid.ir/paper/230160/en

IEEE: Copy

Mehrdad Kaveh, MOHAMMAD SAADI MESGARI, and ALI KHOSRAVI, “Solving the local positioning problem using a four-layer artificial neural network,” ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, vol. 7, no. 4 , pp. 21–40, 2020, [Online]. Available: https://sid.ir/paper/230160/en

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