Correction of Radio Wave Propagation Prediction Model Based on Improved Seagull Algorithm in Tunnel Environment

Zheng, Yunshui; Yan, Rui; Liu, Yang

doi:10.1109/access.2021.3122300

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…In this technique [93] the standard propagation models (SPM) are enhanced by deploying the ISOA algorithm. RT propagation mechanisms were used to develop the basis of this technique.…”

Section: D: Improved Seagull Optimization Algorithm (Isoa)mentioning

confidence: 99%

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

et al. 2023

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The prediction of radio signal transmission in tunnels is important for wireless communication link design as it enables the delivery of optimum power to the intended receiver inside the tunnel. Several techniques have been proposed to estimate path loss for wireless communication inside tunnels. The radio coverage range and where base stations need to be installed can be figured out with the help of propagation models. At the time of developing these models, modeling complexity and environmental attributes, such as the tunnel geometry and the electrical and magnetic properties of its walls and interior materials are considered. A limited amount of literature currently overviews how waves transmits through tunnels and how electromagnetic wave transmission has recently changed. This survey, which examines current advancements in the propagation of waves in tunnels, aims to address this gap. In this review, thirty wave propagation models were analyzed and grouped into distinct categories for the first time. The detailed specifications of each model were omitted to make the survey easy to comprehend. This comparative research will help service providers adopt an appropriate propagation model and plan efficient transmitter and receiver placement and link management for a specific tunnel environment.INDEX TERMS Artificial neural network, radio wave propagation, ray tracing, scaling, tunnel.

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“…In this technique [93] the standard propagation models (SPM) are enhanced by deploying the ISOA algorithm. RT propagation mechanisms were used to develop the basis of this technique.…”

Section: D: Improved Seagull Optimization Algorithm (Isoa)mentioning

confidence: 99%

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

et al. 2023

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Multi-strategy Improved Seagull Optimization Algorithm

Li,

Yuan

et al. 2023

Int J Comput Intell Syst

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Aiming at the shortcomings of seagull optimization algorithm in the process of searching for optimization, such as slow convergence speed, low precision, easy falling into local optimal, and performance dependent on the selection of parameters, this paper proposes an improved gull optimization algorithm based on multi-strategy fusion based on the analysis of gull population characteristics. Firstly, L–C cascade chaotic mapping is used to initialize the population so that seagulls are more evenly distributed in the initial solution space. Secondly, to improve the algorithm’s global exploration ability in the early stage, the nonlinear convergence factor is incorporated to adjust the position of seagulls in the migration stage. At the same time, the group learning strategy was introduced after the population position update to improve the population quality and optimization accuracy further. Finally, in the late stage of the algorithm, the golden sine strategy of the Levy flight guidance mechanism is used to update the population position to improve the population’s diversity and enhance the local development ability of the algorithm in the late stage. To verify the optimization performance of the improved algorithm, CEC2017 and CEC2022 test suites are selected for simulation experiments, and box graphs are drawn. The test results show that the proposed algorithm has apparent convergence speed, accuracy, and stability advantages. The engineering case results demonstrate the proposed algorithm’s advantages in solving complex problems with unknown search spaces.

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Key technologies for wireless network digital twin towards smart railways

Guan,

Guo,

et al. 2024

High-speed Railway

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Correction of Radio Wave Propagation Prediction Model Based on Improved Seagull Algorithm in Tunnel Environment

Cited by 7 publications

References 16 publications

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

Multi-strategy Improved Seagull Optimization Algorithm

Key technologies for wireless network digital twin towards smart railways

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