A decomposition-based multi-objective optimization approach for balancing the energy consumption of wireless sensor networks

Tam, Nguyen Thi; Hung, Tran Quang; Bình, Huỳnh Thị Thanh; Vĩnh, Lê Trọng

doi:10.1016/j.asoc.2021.107365

Cited by 32 publications

(8 citation statements)

References 31 publications

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“…They have a strong understanding of meaning and syntactic structure and have good memory and recall. They tend to learn knowledge through reading, reading, writing, discussion, or debate [13]. In high English teaching, every teaching is closely related to this intelligent development, that is, to effectively improve students' comprehensive English language skills such as written expression, oral expression, and translation [14].…”

Section: Related Workmentioning

confidence: 99%

Advanced Intelligent English Translation Based on Multisensor Data Fusion Optimization

Wang

2022

Journal of Sensors

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English translation activity course is of great significance to cultivate students’ English translation level. In the context of multisensor data fusion, how to effectively carry out English translation activity course in colleges and universities has become an important topic. The educational value and intellectual property of advanced Intelligent English translation activity course are analyzed. From multisensor data fusion and the improvement of translation, translators psychological changes of the boot and prominent features, English translation activity and translation, the generality of the multisensor data fusion of multisensor data fusion personalization features this four aspects, which is under the background of the sensor data fusion of the practice for college English translation activity. Firstly, the theory of data fusion estimation is elaborated, and various data fusion structures in multisensor systems are summarized. Then, the data fusion estimation model based on Kalman filter is established, and the Kalman filtering algorithms of centralized, sequential, parallel, and joint structures are given, respectively. Simulation experiments are carried out on the algorithms. Experimental results show that the estimation accuracy of the system can be improved by multisensor data fusion. Then a rule-based lexical analyzer is designed. Combined with the system model, a rule-based lexical analyzer and a comprehensive dictionary, the linguistic knowledge source throughout the whole machine translation process, are researched and designed. A hashing algorithm for lexical retrieval is designed, and various rules and data structures related to the lexical analyzer are described in formal language. The analysis algorithms of morphological preprocessing, morphological analysis, unincluded word processing, phrase analysis, and part of speech tagging are introduced.

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Section: Related Workmentioning

confidence: 99%

Advanced Intelligent English Translation Based on Multisensor Data Fusion Optimization

Wang

2022

Journal of Sensors

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“…These collected information will be sent out wirelessly and will be sent to the terminal in a self-grouping multi-hop way, so as to realize the physical world, the computing world and human society of the ternary world of mutual connectivity. Wireless sensor networks unite the world of valuable information with a global mission, changing the way people interact with nature [1].…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption and QoS Optimization Coverage Mechanism in Wireless Sensor Networks Based on Swarm Sensing Algorithm

Wang

Feng

et al. 2022

Journal of Sensors

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Objective. To study energy consumption and QoS optimization coverage mechanism in wireless sensor networks based on swarm sensing algorithm. Methods. The swarm sensor algorithm is reported to optimize the configuration of wireless sensor nodes, improve network service performance, and provide feedback on effective sensor placement. Results. Two WSN coverage optimization schemes were proposed in this essay. The first scheme applied drosophila intelligent algorithm to WSN coverage optimization, and the second scheme integrated particle swarm optimization algorithm and improved firefly algorithm to complement each other. Both schemes can achieve good results in practical application. Scheme one can increase the coverage rate by 6.36% compared with previous schemes, while scheme two can increase it by 6.48%. Both schemes are basically the same, so they can be applied in the optimization of WSN node deployment. Conclusion. As an optimization method, group perception algorithm is inspired by biology. Through the continuous enrichment and development of this algorithm, it has been effectively used in the coverage optimization of the wireless sensor networks.

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“…To explore the business objectives of SWSN applications, it offers sale data access, marketing automation, targeted customer services, reduces the cost of delivery, and improves the supply chain processes [32]. Smart-SWSN applications create a knowledge base framework for the customers such as the buying pattern, order records, payment records, supply chain, and preferences, etc [33]. Despite this, it also allows the business stakeholders to find out the customer needs in real-time and they also make a prediction of the future demands of the customers based on recorded data.…”

Section: Targeted Customersmentioning

confidence: 99%

Survey: Self-Empowered Wireless Sensor Networks Security Taxonomy, Challenges, and Future Research Directions

Adil

Menon²,

Balasubramanian

et al. 2023

IEEE Sensors J.

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A decomposition-based multi-objective optimization approach for balancing the energy consumption of wireless sensor networks

Cited by 32 publications

References 31 publications

Advanced Intelligent English Translation Based on Multisensor Data Fusion Optimization

Advanced Intelligent English Translation Based on Multisensor Data Fusion Optimization

Energy Consumption and QoS Optimization Coverage Mechanism in Wireless Sensor Networks Based on Swarm Sensing Algorithm

Survey: Self-Empowered Wireless Sensor Networks Security Taxonomy, Challenges, and Future Research Directions

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