{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:43:12Z","timestamp":1777704192859,"version":"3.51.4"},"reference-count":10,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T00:00:00Z","timestamp":1530835200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>The construction of long-span spatial structure is an important measure of the science and technology level of a country\u2019s architecture and is widely used in various landmark buildings. Therefore, it is of great significance to adopt effective methods to monitor the health of long-span space structures and ensure the safety of structures during construction and use. Based on the improved particle swarm optimization algorithm, different fitness functions were selected for the health monitoring project of the gymnasium in Hai Lake New District of Xining according to the structural characteristics. The location of strain sensors and acceleration transducer was optimized to provide a reference for the establishment of a long-span spatial structure health monitoring system. The validity of the method was verified through experiments, so as to provide important practical significance and theoretical support for the study of spatial structure detection.<\/jats:p>","DOI":"10.3233\/jifs-169634","type":"journal-article","created":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T12:03:32Z","timestamp":1530878612000},"page":"2813-2819","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimal layout of health monitoring sensor in gymnasium based on improved particle swarm optimization algorithm"],"prefix":"10.1177","volume":"35","author":[{"given":"Zhang","family":"Zhen","sequence":"first","affiliation":[{"name":"University of Electronic and Technology of China, Zhongshan Institute, Guangdong Zhongshan, China"}]}],"member":"179","published-online":{"date-parts":[[2018,7,6]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13296-015-1206-6"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.paerosci.2010.05.001"},{"key":"e_1_3_2_4_2","article-title":"Optimal layout of sensors for a bridge structure based on energy coefficient-effective independence method","author":"Yang Y.X.","year":"2010","unstructured":"Y.X.Yang, X.W.Hao and S.Lei, Optimal layout of sensors for a bridge structure based on energy coefficient-effective independence method, Journal of Vibration&Shock (2010).","journal-title":"Journal of Vibration&Shock"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2010.5669608"},{"issue":"8","key":"e_1_3_2_6_2","first-page":"129","article-title":"Particle swarm optimization","volume":"41","author":"Venter G.","year":"2013","unstructured":"G.Venter and J.Sobieszczanskisobieski, Particle swarm optimization, Aiaa Journal41(8) (2013), 129\u2013132.","journal-title":"Aiaa Journal"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2012.05.019"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPEL.2012.2185713"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2009.2030331"},{"issue":"3","key":"e_1_3_2_10_2","first-page":"1","article-title":"Convergence analysis of standard parti-cle swarm optimization algorithm and its improvement","author":"Qian W.","year":"2011","unstructured":"W.Qian and M.Li, Convergence analysis of standard parti-cle swarm optimization algorithm and its improvement, Soft Computing (3) (2011) 1\u201324.","journal-title":"Soft Computing"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00049"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-169634","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-169634","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-169634","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:40:40Z","timestamp":1777455640000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-169634"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,6]]},"references-count":10,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,10]]}},"alternative-id":["10.3233\/JIFS-169634"],"URL":"https:\/\/doi.org\/10.3233\/jifs-169634","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,6]]}}}