Design of global positioning system (GPS) networks using different artificial intelligence techniques

  • Doaa. S. Odam Civil Department, Higher Institute of Engineering and Technology, Kafr El-Sheikh, Egypt
  • Mohamed. I. Doma Civil Department, Faculty of Engineering, Menoufia University, Egypt
  • Hossam. I. Fawzy Civil Department, Faculty of Engineering, Kafr El-Sheikh University, Egypt
  • Ahmed A. Sedeek Civil Department, Faculty of Engineering, Kafr El-Sheikh University, Egypt
  • Magda. H. Farhan Civil Department, EL Behira Higher Institute of Engineering and Technology, El Behira, Egypt
DOI: https://doi.org/10.36909/jer.10587

Abstract

The selection of optimal GPS baselines can be realized by solving the geodetic second-order design (SOD) problem. Basically, there are two techniques to be used for selecting optimal baselines in GPS network, namely traditional techniques and artificial techniques. Traditional techniques include the method of trial and error and the analytical method, while artificial methods include both local and global optimization techniques. The global optimization techniques, such as Genetic Algorithms (GAs), Simulated Annealing (SA) method, Particle Swarm Optimization (PSO) Algorithm, and Butterfly Optimization Algorithm (BOA) have been recently used in geodesy. In the current study, (BOA) has been used for the selection of the optimal GPS baselines to be measured in the field that will meet the postulated criterion matrix, at a reasonable cost. The work has been executed on a pre-designed GPS network, where the number of baselines, to be observed to attain high accuracy, has been already determined. The results of this paper were more efficient than the results of the traditional methods by 19.2% where it was better than the artificial methods in terms of length, whereas it enhanced (SA) method by 21.7% and (PSO) method by 4.6% . Consequently, the use of the BOA is effective and applicable.

 

 

Author Biographies

Doaa. S. Odam, Civil Department, Higher Institute of Engineering and Technology, Kafr El-Sheikh, Egypt

 

 

Mohamed. I. Doma, Civil Department, Faculty of Engineering, Menoufia University, Egypt

 

 

Hossam. I. Fawzy, Civil Department, Faculty of Engineering, Kafr El-Sheikh University, Egypt

 

 

Ahmed A. Sedeek, Civil Department, Faculty of Engineering, Kafr El-Sheikh University, Egypt

 

 

Magda. H. Farhan, Civil Department, EL Behira Higher Institute of Engineering and Technology, El Behira, Egypt

The selection of optimal GPS baselines can be realized by solving the geodetic second-order design (SOD)
problem. Basically, there are two techniques to be used for selecting optimal baselines in GPS network, namely,
traditional techniques and artificial techniques. Traditional techniques include the method of trial and error and
the analytical method, while artificial methods include both local and global optimization techniques. The global
optimization techniques, such as Genetic Algorithms (GAs), Simulated Annealing (SA) method, Particle Swarm
Optimization (PSO) Algorithm, and Butterfly Optimization Algorithm (BOA), have been used recently in
geodesy. In the current study, BOA has been used for the selection of the optimal GPS baselines to be measured in the field that will meet the postulated criterion matrix, at a reasonable cost. It has been tested on a GPS network. The BOA is already designed, and it determined the number of baselines that would be observed because of obtaining high accuracy. The results showed that the BOA method was more efficient than the traditional ones by 19.2%. It was better than the artificial methods in terms of length as it enhanced SA method by 21.7% and PSO method by 4.6%. Consequently, the use of the BOA is proven to be more effective and applicable.

 

Published
2021-10-13
Issue
Vol 11 No 1B (2023): Journal of Engineering Research
Section
Civil Engineering