Application of Optimization Algorithms for Identification of Reference Points in a Monitoring Network

Area of Science:

• Geodesy and Geomatics
• Geophysical Sciences
• Computational Science

Background:

• Geodetic measurements are crucial for displacement analysis, requiring stable reference points.
• Identifying stable reference points becomes complex due to network size, measurement duration, and geological factors.
• Ambiguous results can arise when selecting reference point subgroups over extended periods.

Purpose of the Study:

• To develop and evaluate an optimization-based method for identifying stable reference systems in geodetic networks.
• To compare the efficacy of simulated annealing (SA) and Hooke-Jeeves (HJ) algorithms for this task.
• To provide a computational tool to aid analysts in selecting reliable reference points.

Main Methods:

• Utilized optimization algorithms, specifically simulated annealing (SA) and Hooke-Jeeves (HJ) method.
• Applied the proposed reference system identification method to two numerical examples.
• Assessed the performance and reliability of the algorithms in identifying mutually stable reference points.

Main Results:

• Both SA and HJ methods yielded positive results in the first numerical example.
• The simulated annealing (SA) method demonstrated superior performance compared to the Hooke-Jeeves (HJ) method in the second, more complex example.
• The study confirms the potential for alternative stable reference point subgroups, highlighting the need for robust identification methods.

Conclusions:

• The proposed optimization-based method effectively supports the identification of stable reference systems for geodetic displacement analysis.
• Simulated annealing is a more robust algorithm for reference system identification in challenging geodetic scenarios.
• This approach enhances the reliability of displacement analysis by providing a systematic tool for reference point selection.