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- W2745834080 abstract "Sales forecasting refers to an assessment of the future sales volume and sales amount of a certain product. It combines the current sales condition of an enterprise and adopts analytical methods to propose a feasible sales target considering all possible future factors. This study combines an artificial neural network and a genetic algorithm to forecast the sales of a small restaurant. Firstly, this study applies the artificial neural network to select the relevant parameters of the current sales condition as the input data. Then it uses a genetic algorithm to optimize the default weights and thresholds of the artificial neural network, in order to compensate for the inadequate traditional artificial neural network algorithm. This study focuses on a small restaurant, by combining historical data of the current sales conditions with an artificial neural network and a genetic algorithm to design and construct a forecasting model. Simulation verifications are conducted using empirical analysis to examine the effectiveness and feasibility of the sales forecasting model proposed in this study. The results of this study indicate that the sales forecasting model developed with a combination of an artificial neural network and a genetic algorithm is a scientifically practical and effective sales forecasting method that can achieve rapid and accurate forecasting outcomes." @default.
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- W2745834080 date "2011-01-01" @default.
- W2745834080 modified "2023-09-26" @default.
- W2745834080 title "A Study of Applying Artificial Neural Network and Genetic Algorithm in Sales Forecasting Model" @default.
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