{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:54:36Z","timestamp":1753887276793,"version":"3.41.2"},"reference-count":15,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The emergence of emergencies has impacted China\u2019s politics, economy, and other aspects to varying degrees, seriously threatening social stability, economic development, and people\u2019s happiness. The emergency management platform plays an important role in the handling of emergencies. The establishment of the emergency management platform can help leaders make correct decisions and reduce the impact of emergencies on the safety of people\u2019s lives and property. However, some problems are gradually exposed in the process of establishing the emergency management platform. How to make it play its role better has become an important goal of platform informatization. With the advent of the big data era, big data technology has become a new way of information construction of emergency management platforms. This article mainly discussed the information construction of the emergency management platform. This article proposed to use big data technology to carry out the information construction of the emergency management platform and use the time series data mining algorithm based on the Artificial Neural Network to achieve the prediction function of the platform. The experimental results in this article showed that the prediction rate was 98.0% when the emergencies of the input platform were 50 and 99.0% when the emergencies of the input platform were 300. It can be seen that the emergency management platform designed in this article has a high ability to predict emergencies, so that emergency management measures can be taken in advance to reduce the occurrence of emergencies.<\/jats:p>","DOI":"10.1515\/comp-2024-0003","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T14:20:48Z","timestamp":1720794048000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of big data technology in emergency management platform informatization construction"],"prefix":"10.1515","volume":"14","author":[{"given":"Meirong","family":"Lin","sequence":"first","affiliation":[{"name":"College of Information Engineering, Hainan Vocational University of Science and Technology , Haikou 571126, Hainan , China"}]}],"member":"374","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"key":"2024071214204265269_j_comp-2024-0003_ref_001","doi-asserted-by":"crossref","unstructured":"S. Harrison and J. 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Dagaeva, \u201cBig spatio\u2010temporal data mining for emergency management information systems,\u201d IET Intell. Transp. Syst., vol. 13, no. 11, pp. 1649\u20131657, 2019.","DOI":"10.1049\/iet-its.2019.0171"},{"key":"2024071214204265269_j_comp-2024-0003_ref_005","doi-asserted-by":"crossref","unstructured":"R. Tidhar, \u201cAirport emergency management: The art of strict rules and flexible minds,\u201d J. Bus. Continuity Emerg. Plan., vol. 13, no. 3, pp. 230\u2013239, 2020.","DOI":"10.69554\/JDVP3463"},{"key":"2024071214204265269_j_comp-2024-0003_ref_006","doi-asserted-by":"crossref","unstructured":"N. Chen, \u201cApplication of computational intelligence technologies in emergency management: a literature review,\u201d Artif. Intell. Rev., vol. 52, no. 3, pp. 2131\u20132168, 2019.","DOI":"10.1007\/s10462-017-9589-8"},{"key":"2024071214204265269_j_comp-2024-0003_ref_007","doi-asserted-by":"crossref","unstructured":"C. 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