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- W4287883618 abstract "This paper presents a sales forecasting model of e-commerce products based on hybrid neural network. Firstly, we screen the factors that have great influence on sales volume to establish the sales volume prediction index system, and then the fusion value of each level index in the sales volume prediction index system is obtained by combining entropy weighting and hierarchical analysis methods as the three inputs of the sales volume prediction model. Then, a hybrid neural network model based on voting-ensemble method is established, and the performance of the model is evaluated. The experimental results show that the ensemble model has higher accuracy in the sales forecast of e-commerce. At the same time, the model in this paper is also practical, which can promote B2C e-commerce enterprises to optimize inventory management, improve the overall efficiency of logistics, and then improve the overall customer satisfaction and improve the competitiveness of enterprises." @default.
- W4287883618 created "2022-07-26" @default.
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- W4287883618 date "2022-05-27" @default.
- W4287883618 modified "2023-09-28" @default.
- W4287883618 title "Research on E-commerce Mathematical Forecasting Model based on Hybrid Neural Network" @default.
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- W4287883618 doi "https://doi.org/10.1109/icetci55101.2022.9832316" @default.
- W4287883618 hasPublicationYear "2022" @default.
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