A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array

Liang, Qiankun; Bin, Chen; Wu, Huaning; Ma, Chaoyi; Li, Senyou

doi:10.1155/2021/9915420

Cited by 26 publications

(23 citation statements)

References 40 publications

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“…This algorithm has higher convergence rate than the original SSA. Liang et al modified SSA with combining a homogeneous chaotic system, adaptive inertia weight, and improved boundary constraint [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Threshold image segmentation based on improved sparrow search algorithm

Yuan

2022

Multimed Tools Appl

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Threshold segmentation based on swarm intelligence optimization algorithm is a research hotspot in image processing, because of its good segmentation effect and easy implementation. This paper proposes an image threshold segmentation method based on an improved sparrow search algorithm and 2-D maximum entropy method. In the proposed algorithm, the nonlinear inertia weight is introduced into the entrants’ update formula to improve the local exploration ability of the algorithm, and Levy flight is introduced into the vigilant sparrows’ update formula to prevent the algorithm from falling into the local optimal solution in the later stage of iteration. In addition, improved sparrow search algorithm is tested on fifteen benchmark functions. The results represent the merit of the proposed algorithm with respect to other algorithms. Finally, the proposed algorithm is applied to entropy based image segmentation. Experiment results on classical images and medical images show that the proposed method improves the segmentation effect in terms of peak signal-to-noise ratio and feature similarity.

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Section: Introductionmentioning

confidence: 99%

Threshold image segmentation based on improved sparrow search algorithm

Yuan

2022

Multimed Tools Appl

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“…Liang et al [ 18 ] introduced another modified version of SSA (MSSA) for sidelobe level reduction of the linear antenna array. The homogeneous chaotic system was used to construct the initial population to enhance the population diversity.…”

Section: Recent Variants Of Ssamentioning

confidence: 99%

Recent Versions and Applications of Sparrow Search Algorithm

Awadallah

Al-Betar

Doush

et al. 2023

Arch Computat Methods Eng

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This paper reviews the latest versions and applications of sparrow search algorithm (SSA). It is a recent swarm-based algorithm proposed in 2020 rapidly grew due to its simple and optimistic features. SSA is inspired by the sparrow living style of foraging and the anti-predation behavior of sparrows. Since its establishment, it has been utilized for a plethora of optimization problems in different research topics, such as mechanical engineering, electrical engineering, civil engineering, power systems, industrial engineering, image processing, networking, environment, robotics, planing and scheduling, and healthcare. Initially, the growth of SSA and its theoretical features are highlighted in terms of the number of published articles, citations, topics covered, etc. After that, the different extended versions of SSA are reviewed, where the main variations of SSA are produced to avoid premature convergence and to boost the diversity aspects. These extended versions are modifications and hybridization summarized with more focus on the motivations behind establishing these versions. Multi-objective SSA is also presented as another version to deal with Multi-objective optimization problems. The critical analysis of the main research gaps in the convergence behaviour of SSA is discussed. Finally, the conclusion and the possible future expansions are recommended based on the research works accomplished in the literature.

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“…It can be seen from Table 1 that although the improved strategy reduces the number of individuals beyond the boundary, some individuals still exceed the boundary and gather at the boundary. Literature [ 38 ] adopts the strategy of the current optimal solution for individuals beyond the boundary, which will be difficult to get rid of the local optimization. Therefore, this paper proposes a simple boundary treatment method, namely,

…”

Section: Sparrow Search Algorithm Based On Iterative Local Search (Issa)mentioning

confidence: 99%

Improved Sparrow Search Algorithm Based on Iterative Local Search

Yan

Yang

Zhu

et al. 2021

Computational Intelligence and Neuroscience

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This paper solves the shortcomings of sparrow search algorithm in poor utilization to the current individual and lack of effective search, improves its search performance, achieves good results on 23 basic benchmark functions and CEC 2017, and effectively improves the problem that the algorithm falls into local optimal solution and has low search accuracy. This paper proposes an improved sparrow search algorithm based on iterative local search (ISSA). In the global search phase of the followers, the variable helix factor is introduced, which makes full use of the individual’s opposite solution about the origin, reduces the number of individuals beyond the boundary, and ensures the algorithm has a detailed and flexible search ability. In the local search phase of the followers, an improved iterative local search strategy is adopted to increase the search accuracy and prevent the omission of the optimal solution. By adding the dimension by dimension lens learning strategy to scouters, the search range is more flexible and helps jump out of the local optimal solution by changing the focusing ability of the lens and the dynamic boundary of each dimension. Finally, the boundary control is improved to effectively utilize the individuals beyond the boundary while retaining the randomness of the individuals. The ISSA is compared with PSO, SCA, GWO, WOA, MWOA, SSA, BSSA, CSSA, and LSSA on 23 basic functions to verify the optimization performance of the algorithm. In addition, in order to further verify the optimization performance of the algorithm when the optimal solution is not 0, the above algorithms are compared in CEC 2017 test function. The simulation results show that the ISSA has good universality. Finally, this paper applies ISSA to PID parameter tuning and robot path planning, and the results show that the algorithm has good practicability and effect.

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A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array

Cited by 26 publications

References 40 publications

Threshold image segmentation based on improved sparrow search algorithm

Threshold image segmentation based on improved sparrow search algorithm

Recent Versions and Applications of Sparrow Search Algorithm

Improved Sparrow Search Algorithm Based on Iterative Local Search

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