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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: Wang, Xiaodong | Wang, Xiaoming | Wu, Junfeng | Zheng, Kai | Pang, Yanhong | Gang, Song; *
Affiliations: China Tobacco Henan Industrial Co., Ltd, Zhengzhou, China
Correspondence: [*] Corresponding author. Song Gang, China Tobacco Henan Industrial Co., Ltd, Zhengzhou, China, 450000. E-mail: [email protected].
Abstract: For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.
Keywords: Information strategy, Artificial Intelligence (AI), PDCA quality cycle, cigarette logistics, quality traceability, fuzzy, artificial neural network
DOI: 10.3233/JIFS-189644
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8217-8226, 2021
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