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Issue title: Ethical Computational Intelligence for Cyber Market
Guest editors: Oscar Sanjuán Martínez, Giuseppe Fenza and Ruben Gonzalez Crespo
Article type: Research Article
Authors: Tao, Zoua; * | Si Jun, Baia | Xi Bai, Rongb
Affiliations: [a] School of Management, Northwestern Polytechnic University, Xian Shanxi, China | [b] School of Sociology, Wuhan University, Wuhan, Hubei, China
Correspondence: [*] Corresponding author. Zou Tao, School of Management, Northwestern Polytechnic University, Xian Shanxi, 71000, School of Sociology, Wuhan University, Wuhan, Hubei, 430056, China. E-mail: [email protected].
Abstract: The rapid development of cloud computing, big data, AI, BI and other information technologies has accelerated the process of enterprise modernization and informatization. The combination of computer technology and management science promoted the formation of modern enterprise management technology. Especially in today’s era of big data, in the face of massive data, how to quickly and accurately find out the required information, analyze the memory relation of data, find out the inherent business law hidden under massive information, and provide an important reference for enterprises to make business decisions and seek for market opportunities. A methodology that exhibits fuzzy TOPSIS model has been incorporated in this study. Fuzzy weights and fuzzy judgment about the management systems have employed to estimate the scores of evaluation. In order to solve this problem, this paper integrates independent ERP and BI, and studies and develops a marketing management system by using advanced technologies such as data warehouse, online analysis and data mining; The system extracts useful data from ERP data sources, and analyzes the internal rules and statistical results that can be used to guide the enterprise’s actions, so as to effectively improve the enterprise’s competitiveness.
Keywords: ERP, artificial intelligence (AI), data mining, marketing management, computer technology, fuzzy TOPSIS, fuzzy weights, fuzzy judgment
DOI: 10.3233/JIFS-189647
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8247-8255, 2021
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