Information Acquisition Incentive Mechanism Based on Evolutionary Game Theory
Based on evolutionary game theory, this paper proposes a new information acquisition mechanism for intelligent mine construction, which solves the problem of incomplete information acquisition in the construction of new intelligent mining area and reduces the difficulty of information acquisition, w...
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description | Based on evolutionary game theory, this paper proposes a new information acquisition mechanism for intelligent mine construction, which solves the problem of incomplete information acquisition in the construction of new intelligent mining area and reduces the difficulty of information acquisition, which solves the problem of the imperfect mine information acquisition in the construction of a new smart mine regions and decreases the difficulty of a mine information acquisition. Based on the evolutionary game model, the perceptual incentive model based on group is established. The reliability of information collection is ensured by sharing and modifying the information collector. Through the analysis of the simulation results, it is found that the regional coverage model based on the cooperation in game theory and evolutionary game theory has a good effect on solving the bottleneck problem of the current intelligent mining area. This paper has an enlightening effect on the optimization of the mine information acquisition system. Through the improvement of the mine information acquisition system, the working efficiency of the information acquisition terminal can be effectively increased by 6%. |
doi_str_mv | 10.1155/2021/5525791 |
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Based on the evolutionary game model, the perceptual incentive model based on group is established. The reliability of information collection is ensured by sharing and modifying the information collector. Through the analysis of the simulation results, it is found that the regional coverage model based on the cooperation in game theory and evolutionary game theory has a good effect on solving the bottleneck problem of the current intelligent mining area. This paper has an enlightening effect on the optimization of the mine information acquisition system. Through the improvement of the mine information acquisition system, the working efficiency of the information acquisition terminal can be effectively increased by 6%.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2021/5525791</identifier><language>eng</language><publisher>Oxford: Hindawi</publisher><subject>Communication ; Crowdsourcing ; Data processing ; Equilibrium ; Evolution ; Game theory ; Incentives ; Internet of Things ; Lagrange multiplier ; Mining ; Monetary incentives ; Ontology ; Optimization ; Publishing ; Semantics ; Sensors</subject><ispartof>Wireless communications and mobile computing, 2021, Vol.2021 (1)</ispartof><rights>Copyright © 2021 Lihong Dong et al.</rights><rights>Copyright © 2021 Lihong Dong et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-20a513bf3f0ecc919b543fe3c729d65d2a6b9451c9fa466bbf9ba4172353a3eb3</citedby><cites>FETCH-LOGICAL-c337t-20a513bf3f0ecc919b543fe3c729d65d2a6b9451c9fa466bbf9ba4172353a3eb3</cites><orcidid>0000-0002-4753-3619 ; 0000-0001-7043-5657 ; 0000-0001-6253-9237</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4021,27921,27922,27923</link.rule.ids></links><search><contributor>Zhang, Yin</contributor><contributor>Yin Zhang</contributor><creatorcontrib>Dong, Lihong</creatorcontrib><creatorcontrib>Wang, Xirong</creatorcontrib><creatorcontrib>Liu, Beizhan</creatorcontrib><creatorcontrib>Zheng, Tianwei</creatorcontrib><creatorcontrib>Wang, Zheng</creatorcontrib><title>Information Acquisition Incentive Mechanism Based on Evolutionary Game Theory</title><title>Wireless communications and mobile computing</title><description>Based on evolutionary game theory, this paper proposes a new information acquisition mechanism for intelligent mine construction, which solves the problem of incomplete information acquisition in the construction of new intelligent mining area and reduces the difficulty of information acquisition, which solves the problem of the imperfect mine information acquisition in the construction of a new smart mine regions and decreases the difficulty of a mine information acquisition. Based on the evolutionary game model, the perceptual incentive model based on group is established. The reliability of information collection is ensured by sharing and modifying the information collector. Through the analysis of the simulation results, it is found that the regional coverage model based on the cooperation in game theory and evolutionary game theory has a good effect on solving the bottleneck problem of the current intelligent mining area. This paper has an enlightening effect on the optimization of the mine information acquisition system. Through the improvement of the mine information acquisition system, the working efficiency of the information acquisition terminal can be effectively increased by 6%.</description><subject>Communication</subject><subject>Crowdsourcing</subject><subject>Data processing</subject><subject>Equilibrium</subject><subject>Evolution</subject><subject>Game theory</subject><subject>Incentives</subject><subject>Internet of Things</subject><subject>Lagrange multiplier</subject><subject>Mining</subject><subject>Monetary incentives</subject><subject>Ontology</subject><subject>Optimization</subject><subject>Publishing</subject><subject>Semantics</subject><subject>Sensors</subject><issn>1530-8669</issn><issn>1530-8677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp90E1PAjEQBuDGaCKiN3_AJh51pR87XXtEg0gC8YLnpu22oYTtQruL4d-7CPHoaSaZJzOTF6F7gp8JARhRTMkIgEIpyAUaEGA4f-FlefnXc3GNblJaY4xZjwdoMQuuibVqfROysdl1PvnffhaMDa3f22xhzUoFn-rsVSVbZf1wsm823ZGpeMimqrbZcmWbeLhFV05tkr071yH6ep8s3z7y-ed09jae54axss0pVkCYdsxha4wgQkPBnGWmpKLiUFHFtSiAGOFUwbnWTmhVkJIyYIpZzYbo4bR3G5tdZ1Mr100XQ39SUuAgKBDOe_V0UiY2KUXr5Db6un9ZEiyPgcljYPIcWM8fT3zlQ6W-_f_6B8ZOamk</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Dong, Lihong</creator><creator>Wang, Xirong</creator><creator>Liu, Beizhan</creator><creator>Zheng, Tianwei</creator><creator>Wang, Zheng</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-4753-3619</orcidid><orcidid>https://orcid.org/0000-0001-7043-5657</orcidid><orcidid>https://orcid.org/0000-0001-6253-9237</orcidid></search><sort><creationdate>2021</creationdate><title>Information Acquisition Incentive Mechanism Based on Evolutionary Game Theory</title><author>Dong, Lihong ; 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Based on the evolutionary game model, the perceptual incentive model based on group is established. The reliability of information collection is ensured by sharing and modifying the information collector. Through the analysis of the simulation results, it is found that the regional coverage model based on the cooperation in game theory and evolutionary game theory has a good effect on solving the bottleneck problem of the current intelligent mining area. This paper has an enlightening effect on the optimization of the mine information acquisition system. 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subjects | Communication Crowdsourcing Data processing Equilibrium Evolution Game theory Incentives Internet of Things Lagrange multiplier Mining Monetary incentives Ontology Optimization Publishing Semantics Sensors |
title | Information Acquisition Incentive Mechanism Based on Evolutionary Game Theory |
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