The simulation parameters.
<div><p>With the continuous advancement of network transmission technology, more and more applications are being applied in wireless network environments, especially in places that require high coverage, such as oceans and mountainous areas. However, wireless data transmission has the di...
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2025
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| _version_ | 1849927626492215296 |
|---|---|
| author | Ziyang Xing (22683634) |
| author_facet | Ziyang Xing (22683634) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ziyang Xing (22683634) |
| dc.date.none.fl_str_mv | 2025-11-25T18:39:34Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0333372.t001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/The_simulation_parameters_/30714766 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified require high coverage experimental verification shows achieve retrieval enhancement wireless network status wireless network environments network transmission technology wireless data transmission data transmission system wireless network data transmission unstable transmission mechanical system xlink "> strong generalizability reward functions mountainous areas continuous advancement |
| dc.title.none.fl_str_mv | The simulation parameters. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <div><p>With the continuous advancement of network transmission technology, more and more applications are being applied in wireless network environments, especially in places that require high coverage, such as oceans and mountainous areas. However, wireless data transmission has the disadvantages of unstable transmission and easy interruption using traditional methods. Based on this, we propose a data transmission system that uses a micro-electron-mechanical system (MEMS) sensor to obtain the wireless network status and applies expert library reinforcement learning that does not rely on reward functions to achieve retrieval enhancement of data transmission. Experimental verification shows that the proposed expert library reinforcement learning has strong generalizability and fast convergence.</p><p>Expert library reinforcement learning, wireless network, MEMS, integrated network.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_6cafcaeccabf77221f70fdf9f963bb8b |
| identifier_str_mv | 10.1371/journal.pone.0333372.t001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30714766 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The simulation parameters.Ziyang Xing (22683634)BiotechnologyCancerScience PolicyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedrequire high coverageexperimental verification showsachieve retrieval enhancementwireless network statuswireless network environmentsnetwork transmission technologywireless data transmissiondata transmission systemwireless networkdata transmissionunstable transmissionmechanical systemxlink ">strong generalizabilityreward functionsmountainous areascontinuous advancement<div><p>With the continuous advancement of network transmission technology, more and more applications are being applied in wireless network environments, especially in places that require high coverage, such as oceans and mountainous areas. However, wireless data transmission has the disadvantages of unstable transmission and easy interruption using traditional methods. Based on this, we propose a data transmission system that uses a micro-electron-mechanical system (MEMS) sensor to obtain the wireless network status and applies expert library reinforcement learning that does not rely on reward functions to achieve retrieval enhancement of data transmission. Experimental verification shows that the proposed expert library reinforcement learning has strong generalizability and fast convergence.</p><p>Expert library reinforcement learning, wireless network, MEMS, integrated network.</p></div>2025-11-25T18:39:34ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0333372.t001https://figshare.com/articles/dataset/The_simulation_parameters_/30714766CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307147662025-11-25T18:39:34Z |
| spellingShingle | The simulation parameters. Ziyang Xing (22683634) Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified require high coverage experimental verification shows achieve retrieval enhancement wireless network status wireless network environments network transmission technology wireless data transmission data transmission system wireless network data transmission unstable transmission mechanical system xlink "> strong generalizability reward functions mountainous areas continuous advancement |
| status_str | publishedVersion |
| title | The simulation parameters. |
| title_full | The simulation parameters. |
| title_fullStr | The simulation parameters. |
| title_full_unstemmed | The simulation parameters. |
| title_short | The simulation parameters. |
| title_sort | The simulation parameters. |
| topic | Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified require high coverage experimental verification shows achieve retrieval enhancement wireless network status wireless network environments network transmission technology wireless data transmission data transmission system wireless network data transmission unstable transmission mechanical system xlink "> strong generalizability reward functions mountainous areas continuous advancement |