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MULTIMODAL DATA GUIDED SPATIAL FEATURE FUSION AND GROUPING STRATEGY FOR E-COMMERCE COMMODITY DEMAND FORECASTING

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成果类型:
期刊论文
作者:
Cai, Weiwei;Song, Yaping;Wei, Zhanguo
作者机构:
[Wei, Zhanguo; Song, Yaping; Cai, Weiwei] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha 410004, Peoples R China.
语种:
英文
期刊:
Mobile Information Systems
ISSN:
1574-017X
年:
2021
卷:
2021
页码:
5568208:1-5568208:14
机构署名:
本校为第一机构
院系归属:
交通运输与物流学院
摘要:
E-commerce offers various merchandise for selling and purchasing with frequent transactions and commodity flows. An accurate prediction of customer needs and optimized allocation of goods is required for cost reduction. The existing solutions have significant errors and are unsuitable for addressing warehouse needs and allocation. That is why businesses cannot respond to customer demands promptly, as they need accurate and reliable demand forecasting. Therefore, this paper proposes spatial feature fusion and grouping strategies based on multimodal data and builds a neural network prediction mo...

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