Positioning algorithm based on improved dragonfly optimization

Authors

  • Yue Zhang
  • Hongping Pu
  • Wei Chen

DOI:

https://doi.org/10.62051/ijcsit.v1n1.08

Keywords:

Dragonfly algorithm, Positional accuracy, Cauchy disturbance

Abstract

Aiming at solving the nonlinear equation of indoor arrival time difference positioning, a multi-strategy improved dragonfly optimization algorithm is proposed. The initial population is improved by chaotic mapping, and then nonlinear factors and Cauchy mutation operators are introduced to rapidly converge the balanced global search and local search. At the same time, simulation and comparison experiments with other algorithms show that the algorithm has a higher positioning effect.

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References

Mirjalili S. Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems[J]. Neural Computing and Applications, 2016, 27(4): 1053-1073.

Yi S. Exploring and evaluating the key technologies in TDOA-Based indoor positioning[J]. Highlights in Science, Engineering and Technology, 2023, 68: 108-114.

Dong J, Lian Z, Xu J, Yue Z. An improved adaptive sparrow search algorithm for TDOA-Based localization[J]. ISPRS International Journal of Geo-Information, 2023, 12(8): 334.

Liu H, Chen D, Lin F, et al. Wind Power Short-Term Forecasting Based on LSTM Neural Network with Dragonfly Algorithm[J]. Journal of Physics Conference Series, 2021,1748(3):032015.

Dongsheng Y, Mingling W, et al. Dynamic opposite learning enhanced dragonfly algorithm for solving large-scale flexible job shop scheduling problem[J]. Knowledge-Based Systems, 2022,238(28):107815.

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Published

30-12-2023

Issue

Section

Articles

How to Cite

Zhang, Y., Pu, H., & Chen, W. (2023). Positioning algorithm based on improved dragonfly optimization. International Journal of Computer Science and Information Technology, 1(1), 54-59. https://doi.org/10.62051/ijcsit.v1n1.08