Effect of fitness function on localization performance in range-free localization algorithm

The problem of solving the nonlinear equations in the range-free localization algorithm has been transformed into an optimal solution problem. Meta-heuristic optimization method has been widely adopted to tackle above issues. How to choose the best localization fitness function for a specific target...

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Bibliographic Details
Main Authors: Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue
Format: Article
Language:English
English
Published: Springer US 2024
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/42167/1/Effect%20of%20fitness%20function%20on%20localization%20performance_ABST.pdf
http://umpir.ump.edu.my/id/eprint/42167/2/Effect%20of%20fitness%20function%20on%20localization%20performance%20in%20range-free%20localization%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/42167/
https://doi.org/10.1007/s11042-023-16030-4
https://doi.org/10.1007/s11042-023-16030-4
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Institution: Universiti Malaysia Pahang Al-Sultan Abdullah
Language: English
English
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Summary:The problem of solving the nonlinear equations in the range-free localization algorithm has been transformed into an optimal solution problem. Meta-heuristic optimization method has been widely adopted to tackle above issues. How to choose the best localization fitness function for a specific target is a key factor in determining whether the localization algorithm is accurate or not. However, so far there is no literature to investigate the effect of fitness function on rang-free localization algorithm. Firstly, this study comprehensively reviews and classifies the frequently-used localization fitness function in range-free localization scheme. Next, multiple experiments are carried out for each typical localization fitness function. The experimental results are analyzed in terms of accuracy and stability. Besides, the advantage and disadvantage of each localization fitness function are also given. Finally, an advanced localization fitness function is proposed based on the above experimental results, which will provide a guide and reference for selection and improvement of the fitness function in range-free localization algorithm.