{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:24:23Z","timestamp":1775838263071,"version":"3.50.1"},"reference-count":17,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T00:00:00Z","timestamp":1698451200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China (NSFC)","award":["U2133203"],"award-info":[{"award-number":["U2133203"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To clarify the reasons for inaccurate fire detection in aircraft cargo holds, this article depicts research from the perspective of a single type of sensor detection. In terms of fire smoke, we select dual-wavelength photoelectric smoke sensors for fire-data collection and a genetic algorithm to optimize the classification and detection of random forest fires. From the perspective of fire CO concentration, we use PSO-LSTM to train a CO concentration compensation model to reduce sensor measurement errors. Research is then conducted from the perspective of various types of sensor detection, using the improved BP-AdaBoost algorithm to train a fire-detection model and achieve the high-precision identification of complex environments and fire situations.<\/jats:p>","DOI":"10.3390\/s23218797","type":"journal-article","created":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T13:26:55Z","timestamp":1698672415000},"page":"8797","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Research on Fire-Detection Algorithm for Airplane Cargo Compartment Based on Typical Characteristic Parameters"],"prefix":"10.3390","volume":"23","author":[{"given":"Haibin","family":"Wang","sequence":"first","affiliation":[{"name":"Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"},{"name":"Civil Aviation Safety Engineering College, Civil Aviation Flight University of China, Guanghan 618307, China"}]},{"given":"Hongjuan","family":"Ge","sequence":"additional","affiliation":[{"name":"Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}]},{"given":"Zhihui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Civil Aviation Safety Engineering College, Civil Aviation Flight University of China, Guanghan 618307, China"}]},{"given":"Zonghao","family":"Bu","sequence":"additional","affiliation":[{"name":"Civil Aviation Safety Engineering College, Civil Aviation Flight University of China, Guanghan 618307, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,28]]},"reference":[{"key":"ref_1","unstructured":"Blake, D. 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Sensors, 17.","DOI":"10.3390\/s17020303"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8797\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:13:34Z","timestamp":1760130814000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8797"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,28]]},"references-count":17,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["s23218797"],"URL":"https:\/\/doi.org\/10.3390\/s23218797","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,28]]}}}