An efficient cluster-based routing using Sparrow Search Algorithm for heterogeneous nodes in Wireless Sensor Networks

Kathiroli, Panimalar; Kanmani, S.

doi:10.1109/iccict50803.2021.9510032

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…Gai et al proposed a parameter-optimized deep belief network (DBN) based on SSA for gear fault severity detection [ 11 ]. Kathiroli et al presented an efficient cluster-based routing model using Sparrow search algorithm derives a fitness function to perform clustering process [ 19 ]. Tuerxun et al used the SSA to optimize the penalty factor and kernel function parameter of SVM and constructed the SSA-SVM wind turbine fault diagnosis model [ 52 ].…”

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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“…Next, to reflect the high efficiency of the improved SSA, we select two algorithms for comparison, i.e., standard SSA and particle swarm optimization (PSO), which are used to solve optimization problems in reference [28] and [29] separately. The simulation results are taken average value through multiple experiments.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

A Random Access Scheme for Aggregate Traffic Based on Deep Fusion of Supermartingale and Improved SSA

Sun,

Liao,

Shen

2023

RADIOENGINEERING

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The network services present diversity as the continuous evolution of communication scenarios, which brings a great challenge to the efficient utilization of resources. The ALOHA access mechanism is considered as an effective solution to deal with multi services for its feature of shared bandwidth. However, the collision problem of ALOHA degrades the quality of service (QoS) seriously. The multi packet reception (MPR) technology could mitigate collision and improve network performance. Considering ALOHA mechanism with MPR capability, we propose a novel random access scheme for aggregate traffic based on deep fusion of supermartingale and improved sparrow search algorithm (SSA) to provide delay QoS guarantee. Firstly, we construct a complicated queuing model with heterogeneous arrivals and ALOHA-type service. Secondly, we derive the tighter delay-violation probability bound relying on supermartingale theory, and the optimization problem is constructed with the goal of minimizing the service rate and the constraint of supermartingale bound. Finally, we improve the SSA by combining Circle chaotic map, nonlinear inertia weight and Lévy flight strategy, then the scheme is designed by applying the improved SSA and supermartingale constraint. Simulation results show that the proposed algorithm has faster convergence speed and the scheme is more bandwidth-saving.

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“…Sparrow Search Algorithm (SSA) is a new type of swarm intelligence optimisation algorithm proposed by sparrow foraging and anti-predator behaviour, the sparrow foraging process consists of three parts: the discoverer, the joiner, and the warning [10]. In SSA, the finder with higher fitness will guide the population to search and forage for food, the joiner will follow the finder to forage for food in order to obtain higher fitness, and the anti-predator behaviour will occur when the sparrow population is aware of the danger [11].…”

Section: Sparrow Search Algorithmmentioning

confidence: 99%

“…In order to improve the parameter optimization effect of the RBF neural network model, this paper adopts an improved method based on the Sparrow Search Algorithm. The Sparrow Search Algorithm simulates the collective intelligent behavior of sparrows when foraging, with the characteristics of strong global search capability and fast convergence speed [7]. Therefore, applying the Sparrow Search Algorithm to parameter optimization of the RBF model is expected to improve the predictive performance and generalization ability of the model.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Water Quality Prediction in the Yellow River Basin: Application of the SSA-RBF Model

Wu,

Blancaflor

2024

E3S Web Conf.

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Watershed water quality monitoring is of great significance in water environment protection and management, and this paper proposes a water quality prediction model based on RBF neural network. Aiming at the parameter optimisation of RBF water quality prediction model, we propose to apply the sparrow search algorithm to optimise the parameters of the RBF model, aiming to improve the global search ability and convergence speed of the model. The characteristics of water quality parameters in the Shaanxi section of the Yellow River Basin were analysed using the model. Comparison with the RBF prediction algorithm is made, and the SSA-RBF prediction algorithm can significantly improve the prediction performance of the RBF model.

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An efficient cluster-based routing using Sparrow Search Algorithm for heterogeneous nodes in Wireless Sensor Networks

Cited by 10 publications

References 27 publications

Threshold image segmentation based on improved sparrow search algorithm

Threshold image segmentation based on improved sparrow search algorithm

A Random Access Scheme for Aggregate Traffic Based on Deep Fusion of Supermartingale and Improved SSA

Enhanced Water Quality Prediction in the Yellow River Basin: Application of the SSA-RBF Model

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