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A RFID tag detection system is proposed with two charge coupled device (CCD). This system can automatically focus on the tag according to its position, so it can obtain the image information more accurately by template matching and edge detection method. Therefore, the spatial structure of multi-tag and the corresponding reading distance can be obtained for training. Because of its excellent performance in multi-objective optimization, the PSO neural network is used to train and predict multi-tag distribution at the maximum reading distance. Compared with other neural networks, PSO is more accurate and its uptime is shorter for RFID multi-tag analysis.<\/jats:p>","DOI":"10.1177\/0142331218823864","type":"journal-article","created":{"date-parts":[[2019,2,7]],"date-time":"2019-02-07T00:37:16Z","timestamp":1549499836000},"page":"3331-3339","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["An optimal measurement method for spatial distribution of radio frequency identification multi-tag based on image analysis and PSO"],"prefix":"10.1177","volume":"41","author":[{"given":"Xiaolei","family":"Yu","sequence":"first","affiliation":[{"name":"College of Science, Nanjing University of Aeronautics and Astronautics, Republic of China"},{"name":"National Quality Supervision and Testing Center for RFID Product (Jiangsu), Republic of 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