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inventory management and demand forecasting Improvement of a forecasting Model Based on artificial neural networks

Journal of management Science & Engineering Research 2021年第2期4卷 33-39页

作者： Cisse Sory Ibrahima Jianwu Xue Thierno Gueye School of management Northwestern Polytechnical UniversityXi'an710072China School of Mechanical engineering Northwestern Polytechnical UniversityXi'an710072China

forecasting is predicting or estimating a future event or *** chains have been constantly growing in most countries ever since the industrial revolution of the 18th *** the competitiveness between supply chains intensifies day by day,companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and *** inventory(overstock)and stock outs are very significant issues for *** inventory levels can lead to loss of revenue because the company's capital is tied up in excess *** inventory can also lead to increased storage,insurance costs and labor as well as lower and degraded quality based on the nature of the *** or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the *** clients are unable to find the right products on the shelves,they may switch to another vendor or purchase alternative *** forecasting is valuable for planning,scheduling and improving the coordination of all supply chain *** paper discusses the use of neural networks for seasonal time series *** objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.

关键词： inventory management demand forecasting seasonal time series artificial neural networks transfer function inventory management demand forecasting seasonal time series artificial neural networks transfer function

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