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The Analysis of Seasonal Fish Quantity with Artifical Intelligent Theory

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Fish products have been important food in most areas of the world. The fish demand is expected to rise sharply by 2020. Fish prices have traditionally been the main cause of arguments between fishermen and fish wholesalers. The proprietors need to spend much capital on the stocks in the traditional fish industry. However, the price of fish products are changing daily based on the supply and demand in the market. Therefore, a fish demand forecast system is necessary for the proprietors. This research used the back propagation neural network algorithm to develop and construct the FDFS (fish demand forecast system), so that the future fish order demand can be forecasted on the base of the existing order data. The studying results will make sure that the proprietors can buy at low price and achieve the aim of short-term stocks according to the short-term demand by adopting the FDFS to assist them in forecasting the future demand. Accordingly, the proprietors can not only increase the profit by reducing the material cost, but also enable the customers get fresh fish products with low price.
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Document Type: Research Article

Publication date: September 1, 2013

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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