{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:14:41Z","timestamp":1772262881473,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T00:00:00Z","timestamp":1668038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Process","award":["2019220714SYS022CG04"],"award-info":[{"award-number":["2019220714SYS022CG04"]}]},{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Process","award":["2021ZDLGY04-04"],"award-info":[{"award-number":["2021ZDLGY04-04"]}]},{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Process","award":["CXJJDL2021014"],"award-info":[{"award-number":["CXJJDL2021014"]}]},{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Process","award":["CXJJDL2021015"],"award-info":[{"award-number":["CXJJDL2021015"]}]},{"name":"Key R&amp;D plan of Shaanxi Province","award":["2019220714SYS022CG04"],"award-info":[{"award-number":["2019220714SYS022CG04"]}]},{"name":"Key R&amp;D plan of Shaanxi Province","award":["2021ZDLGY04-04"],"award-info":[{"award-number":["2021ZDLGY04-04"]}]},{"name":"Key R&amp;D plan of Shaanxi Province","award":["CXJJDL2021014"],"award-info":[{"award-number":["CXJJDL2021014"]}]},{"name":"Key R&amp;D plan of Shaanxi Province","award":["CXJJDL2021015"],"award-info":[{"award-number":["CXJJDL2021015"]}]},{"name":"Postgraduate Innovation Fund of Xi\u2019an University of Posts and Telecommunications","award":["2019220714SYS022CG04"],"award-info":[{"award-number":["2019220714SYS022CG04"]}]},{"name":"Postgraduate Innovation Fund of Xi\u2019an University of Posts and Telecommunications","award":["2021ZDLGY04-04"],"award-info":[{"award-number":["2021ZDLGY04-04"]}]},{"name":"Postgraduate Innovation Fund of Xi\u2019an University of Posts and Telecommunications","award":["CXJJDL2021014"],"award-info":[{"award-number":["CXJJDL2021014"]}]},{"name":"Postgraduate Innovation Fund of Xi\u2019an University of Posts and Telecommunications","award":["CXJJDL2021015"],"award-info":[{"award-number":["CXJJDL2021015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Wireless sensor network deployment should be optimized to maximize network coverage. The D-S evidence theory is an effective means of information fusion that can handle not only uncertainty and inconsistency, but also ambiguity and instability. This work develops a node sensing probability model based on D-S evidence. When there are major evidence disputes, the priority factor is introduced to reassign the sensing probability, with the purpose of addressing the issue of the traditional D-S evidence theory aggregation rule not conforming to the actual scenario and producing an erroneous result. For optimizing node deployment, a virtual force-directed particle swarm optimization approach is proposed, and the optimization goal is to maximize network coverage. The approach employs the virtual force algorithm, whose virtual forces are fine-tuned by the sensing probability. The sensing probability is fused by D-S evidence to drive particle swarm evolution and accelerate convergence. The simulation results show that the virtual force-directed particle swarm optimization approach improves network coverage while taking less time.<\/jats:p>","DOI":"10.3390\/e24111637","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T19:17:34Z","timestamp":1668107854000},"page":"1637","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Node Deployment Optimization for Wireless Sensor Networks Based on Virtual Force-Directed Particle Swarm Optimization Algorithm and Evidence Theory"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6183-4680","authenticated-orcid":false,"given":"Liangshun","family":"Wu","sequence":"first","affiliation":[{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Processing, School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"},{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200241, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junsuo","family":"Qu","sequence":"additional","affiliation":[{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Processing, School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"},{"name":"Xi\u2019an Robertic Intelligent Systems International Science and Technology Cooperation Base, Xi\u2019an 710061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haonan","family":"Shi","sequence":"additional","affiliation":[{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Processing, School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengfei","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Key Laboratory of Advanced Control and Intelligent Processing, School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,10]]},"reference":[{"key":"ref_1","first-page":"39564","article-title":"Genetic algorithm based node deployment in hybrid wireless sensor networks","volume":"2013","author":"Banimelhem","year":"2013","journal-title":"Commun. 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