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Issue title: Special Section: Intelligent & fuzzy theory in engineering and science
Guest editors: Teresa Guarda, Isabel Lopes and Álvaro Rocha
Article type: Research Article
Affiliations: Xi’an Aeronautical University, Xi’an, Shaanxi, China
Correspondence: [*] Corresponding author. Qin Peng, Xi’an Aeronautical University, Xi’an, Shaanxi 710077, E-mail: China.qinpeng2113@163.com.
Abstract: With the full spread of various IT application systems, a large number of business data are stored in the business systems of enterprises. In this paper, the author analyzes the aviation industry management mode based on big data analysis. In this paper, the author analyses aviation industry management model and exchange rate index analysis based on error correction model and fuzzy mathematics. The BP algorithm uses the error of the output layer to estimate the error of the direct predecessor layer of the output layer, and then gradually estimates the error forward, and thus, the error of all layers is obtained. The weights and thresholds of the layers are adjusted according to the error so that the modified network output can approach the expected value. The aviation industry data include both the financial and internal data of airlines, and the external data such as flight information and user data. From the ETL process, building an enterprise data warehouse is an important strategy for the development of the aviation industry. It has a positive effect on the application of automatic data mining and business intelligence in the aviation industry. On this basis, we put forward relevant suggestions for aviation industry management.
Keywords: Big data, aviation industry, operation management, error correction model, fuzzy mathematics
DOI: 10.3233/JIFS-179216
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6363-6375, 2019
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