Abstract
The price of fish product is changing daily based on the market demand and the supply from feeding and fishing at any moment. We find that the production and demand of fish product are different in different seasons based on the investigation and analysis on the fish product market. Therefore it will be much advantageous for the operating personnel if the short-term demand of customer in the future can be forecasted. This research makes use of the back propagation neural network algorithm to forecast the fish product demand, so that the order demand in the future can be forecasted on the base of the existing order data. The object is to improve the competitive force of industry and maximize the profit.
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Lo, CY. (2011). Back Propagation Neural Network on the Forecasting System of Sea Food Material Demand. In: Zhou, M., Tan, H. (eds) Advances in Computer Science and Education Applications. Communications in Computer and Information Science, vol 202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22456-0_22
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DOI: https://doi.org/10.1007/978-3-642-22456-0_22
Publisher Name: Springer, Berlin, Heidelberg
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