{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:46:32Z","timestamp":1760985992610,"version":"3.41.2"},"reference-count":26,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T00:00:00Z","timestamp":1611792000000},"content-version":"vor","delay-in-days":27,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin Municipality","doi-asserted-by":"publisher","award":["18JCYBJC42300"],"award-info":[{"award-number":["18JCYBJC42300"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Aiming at the high false alarm rate when using single sensor to detect fire in aircraft cabin, a multisensor data fusion method is proposed to detect fire. First, the weights of multiple factors, that is, temperature, smoke concentration, CO concentration, and infrared ray intensity in the event of fire, were calculated by using the improved analytic hierarchy process (AHP) method on each sensor node of wireless sensor network, and the probability of fire event in the cabin was evaluated by multivariable\u2010weighted fusion method. Second, based on the mutual support among the evaluation data of fire probabilities of each node, the adaptive weight coefficient is assigned to each evaluation value, and the weighted fusion of all evaluation values of each node is conducted to obtain the fire probability. In the end, compared to the threshold of probability, the fire alarm is determined. Comparing the proposed algorithm to the grey fuzzy neural network fusion algorithm and fuzzy logic fusion algorithm in terms of the time consumption for fire detection and sending alarm and the accuracy of fire alarm perspectives, the experiments demonstrate that the proposed fire detection algorithm can detect the fire within 10<jats:italic>s<\/jats:italic> and reduce the false alarm rate to less than 0.5%, which verifies the superiority of the algorithm in promptness and accuracy. In the meanwhile, the fault tolerance of the algorithm is proved as well.<\/jats:p>","DOI":"10.1155\/2021\/8704924","type":"journal-article","created":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T03:35:08Z","timestamp":1611891308000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multisensor\u2010Weighted Fusion Algorithm Based on Improved AHP for Aircraft Fire Detection"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4452-6795","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9337-6319","authenticated-orcid":false,"given":"Yahui","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7199-9059","authenticated-orcid":false,"given":"Hui","family":"Sun","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3984-4190","authenticated-orcid":false,"given":"Kaixin","family":"Yang","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,1,28]]},"reference":[{"key":"e_1_2_9_1_2","article-title":"Target tracking of a linear time invariant system under irregular sampling","volume":"9","author":"Jin X.","year":"2012","journal-title":"International Journal of Advanced Robotic Systems"},{"key":"e_1_2_9_2_2","first-page":"1","article-title":"Closed-Loop estimation for randomly sampled measurements in target tracking system","volume":"2014","author":"Jin X.","year":"2014","journal-title":"Mathematical Problems in Engineering"},{"key":"e_1_2_9_3_2","first-page":"1","article-title":"Parallel irregular fusion estimation based on nonlinear filter for indoor RFID tracking system","volume":"2016","author":"Jin X.","year":"2016","journal-title":"International Journal of Distributed Sensor Networks"},{"key":"e_1_2_9_4_2","doi-asserted-by":"crossref","unstructured":"LiangY.andTianW. 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