Safety Stock Prediction System And Its Application In Chemical Fiber Enterprises
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 5
Abstract
Accurate and timely prediction of the safety stock of enterprises is of great significance for reducing the cost and improving the economic benefit, which is the urgent problem to be solved in the current manufacturing industry. Because of the complex nonlinear relationship between factors which affecting safety stock, it is difficult to get better decision results by traditional methods. This project first studies the intelligent prediction system of safety stock based on synergetic neural network, and applies it to inventory management of Quanzhou chemical fiber enterprise. The research is of great theoretical and practical significance for chemical fiber enterprises and even for private enterprises.
Authors and Affiliations
Zhehuang Huang
Keywords
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- EP ID EP397073
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