An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue

Rani, Shalli; Babbar, Himanshi; Kaur, Pardeep; Alshehri, Mohammad Dahman; Shah, Syed Hassan Ahmed

doi:10.1109/tits.2021.3129914

Cited by 40 publications

(16 citation statements)

References 17 publications

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“…Design and develop the real-time preprocessing and common analysis functions for mechanical vibration signal analysis and optimize the algorithm Mathematical Problems in Engineering to form a relatively complete set of high-efficiency and lowcomplexity embedded function library [14]. e structural block diagram of the embedded function library is shown in Figure 3, which includes 8 modules, including a basic mathematical function module, a statistics function module, a transformation function module, an interpolation operation function module, and a filtering function module, and the corresponding function functions of each module [15].…”

Section: Dual-core Wsns Node Designmentioning

confidence: 99%

Application of Wireless Sensor Network Data Fusion Technology in Mechanical Fault Diagnosis

Zhao¹,

Shen²,

Jing³

2022

Mathematical Problems in Engineering

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In order to solve the problem that a large number of vibration signals cannot be transmitted in real time in the application of wireless sensor networks (WSNs) in mechanical fault diagnosis, a mechanical fault diagnosis method based on multilevel and hierarchical information fusion of WSNs was proposed. In this method, the cluster tree network structure is used to expand the coverage of network monitoring, and WSNs information fusion is divided into three levels: data-level fusion, feature-level fusion, and decision-level fusion. The terminal node performs data-level fusion on the original vibration information to extract feature information; the cluster-head node performs feature-level fusion on the feature information to obtain pattern recognition results; and the gateway node performs decision-level fusion on the recognition results to evaluate the running status of mechanical equipment. The results show that the slight damage fault of the bearing inner ring can be accurately diagnosed by decision-level fusion based on four groups of probability distribution functions. According to the statistics of 30 test results, the fault recognition rate is 83.3%. The method can be applied to mechanical fault diagnosis effectively.

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Section: Dual-core Wsns Node Designmentioning

confidence: 99%

Application of Wireless Sensor Network Data Fusion Technology in Mechanical Fault Diagnosis

Zhao¹,

Shen²,

Jing³

2022

Mathematical Problems in Engineering

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“…The hybrid algorithm is far better than the standalone algorithm with respect to convergence time, reliability, and memory etc. After the extraction of both the models the Friedman ranking test [ 40 – 44 ] Table 8 and Wilcoxon’s rank sum test [ 45 – 51 ] Table 9 is performed and from this test also it is concluded that the proposed hybrid algorithm is far better than the rest of the compared standalone algorithms.…”

Section: Resultsmentioning

confidence: 99%

A modified particle swarm optimization rat search algorithm and its engineering application

Singla,

Gupta,

Alsharif

et al. 2024

PLoS ONE

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Solar energy generation requires photovoltaic (PV) systems to be optimised, regulated, and simulated with efficiency. The performance of PV systems is greatly impacted by the fluctuation and occasionally restricted accessibility of model parameters, which makes it difficult to identify these characteristics over time. To extract the features of solar modules and build highly accurate models for PV system modelling, control, and optimisation, current-voltage data collecting is essential. To overcome these difficulties, the modified particle swarm optimization rat search algorithm is presented in this manuscript. The modified rat search algorithm is incorporated to increase the PSO algorithm’s accuracy and efficiency, which leads to better outcomes. The RSA mechanism increases both the population’s diversity and the quality of exploration. For triple diode model of both monocrystalline and polycrystalline, PSORSA has showed exceptional performance in comparison to other algorithm i.e. RMSE for monocrystalline is 3.21E-11 and for polycrystalline is 1.86E-11. Similar performance can be observed from the PSORSA for four diode model i.e. RMSE for monocrystalline is 4.14E-09 and for polycrystalline is 4.72E-09. The findings show that PSORSA outperforms the most advanced techniques in terms of output, accuracy, and dependability. As a result, PSORSA proves to be a trustworthy instrument for assessing solar cell and PV module data.

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“…Compared to the PEMFC and SOFC fuel cells, the number of publications in the literature devoted to the modelling of the DMFC seems to be quite minimal. Mostly researchers estimate the unknown parameters using meta heuristic algorithm like swam based algorithms [ 22 , 23 ], genetic based algorithms [ 24 ] and currently focusing on artificial intelligence based algorithms [ 25 , 26 ]. Most of these works have had great difficulty in solving the Butler–Volmer equation.…”

Section: Introductionmentioning

confidence: 99%

Sustainable development of fuel cell using enhanced weighted mean of vectors algorithm

Singla¹,

Gupta²,

Nijhawan³

et al. 2023

Heliyon

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An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue

Cited by 40 publications

References 17 publications

Application of Wireless Sensor Network Data Fusion Technology in Mechanical Fault Diagnosis

Application of Wireless Sensor Network Data Fusion Technology in Mechanical Fault Diagnosis

A modified particle swarm optimization rat search algorithm and its engineering application

Sustainable development of fuel cell using enhanced weighted mean of vectors algorithm

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