2021
DOI: 10.1155/2021/5517029
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Design of Minimizing Expected Energy of Multisource Wireless Cooperative Network Based on Multiobjective Optimization

Abstract: In order to solve the problems of high average power consumption, low average throughput, high average energy consumption per unit of data, and short network life cycle in traditional multisource wireless cooperation methods, this paper proposes a multisource wireless cooperative network design method based on multiple goals. We analyze the characteristics of heterogeneous deployment of multisource wireless cooperative networks and the energy consumption of nodes and control the energy consumption of network d… Show more

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Cited by 5 publications
(7 citation statements)
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References 22 publications
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“…is technology has improved the degree of reuse. Based on Wang's noncooperative game theory, the energy efficiency of a mobile communication network is maximized by appropriate power control strategies [20]. Singh et al proposed a noncooperative game power control algorithm to optimize the network energy efficiency.…”
Section: Research On Wireless Network Optimizationmentioning
confidence: 99%
See 1 more Smart Citation
“…is technology has improved the degree of reuse. Based on Wang's noncooperative game theory, the energy efficiency of a mobile communication network is maximized by appropriate power control strategies [20]. Singh et al proposed a noncooperative game power control algorithm to optimize the network energy efficiency.…”
Section: Research On Wireless Network Optimizationmentioning
confidence: 99%
“…It demonstrates that the algorithm has good algebraic connectivity and stiffness properties. E distance from relay node Our ref [18] ref [20] ref [21] Figure 9: e relationship between the distance from E relay and users' safety satisfaction.…”
Section: Computational Intelligence and Neurosciencementioning
confidence: 99%
“…e idea of multiobjective optimization originated in the field of economics is as follows. With people's continuous awareness of the limitation of means of production, how to use the least means of production to obtain the maximum benefit has become the concern of scholars [9]. Based on this idea, the multiobjective optimization process seeks how to optimize the allocation of resources under the condition of the same output, so as to minimize the consumption of means of production in the production process.…”
Section: Multiobjective Optimization Problemmentioning
confidence: 99%
“…This is beneficial as it allows for the discovery of patterns in data sets that may have otherwise been overlooked, resulting in more accurate and complete classifications. Additionally, SOMs are particularly effective in cases where the data set is large and complex [18]. By having the ability to automatically classify data sets, SOMs can help save time and resources for businesses that would otherwise have to spend a significant amount of time and effort classifying data manually [19].…”
Section: Introductionmentioning
confidence: 99%
“…Additionally, SOMs are particularly effective in cases where the data set is large and complex. 18 By having the ability to automatically classify data sets, SOMs can help save time and resources for businesses that would otherwise have to spend a significant amount of time and effort classifying data manually. 19 Competitive learning is a progression that dispenses a massive amount of information in clusters based on inherent input data.…”
mentioning
confidence: 99%