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• W2183628734 abstract "In recent years, there has been a strong tendency by companies to use centralized management systems like Enterprise resource planning (ERP). ERP systems offer a comprehensive and simplified process managements and extensive functional coverage. Sales management module is an important element business management of ERP. T his paper describes an intelligent hybrid sales forecasting system ERP-FCBPN sales forecast based on architecture of ERP through Delphi, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate (FCBPN). The proposed approach is composed of three stages: (1) Stage of data collection: Data collection will be implemented from the fields (attributes) existing at the interfaces (Tables the database) of the ERP. Collection of Key factors that influence sales be made using the Delphi method; (2) Stage of Data preprocessing: Winter’s Exponential Smoothing method will be utilized to take the trend effect into consideration. (3) Stage of learning by FCBPN: We use hybrid sales forecasting system based on Delphi, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate (FCBPN). The data for this study come from an industrial company that manufactures packaging. Experimental results show that the proposed model outperforms the previous and traditional approaches. Therefore, it is a very promising solution for industrial forecasting." @default.
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• W2183628734 date "2012-01-01" @default.
• W2183628734 modified "2023-09-27" @default.
• W2183628734 title "Sales Forecasting Based on ERP System through Delphi, fuzzy Clustering and Back-Propagation Neural Networks with adaptive learning rate" @default.
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