.png){kind=icon}
返回
Transformative computing for products sales forecast based on SCIM
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2021.107520.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Online agricultural product trading has the characteristics of rapid and diversified transaction data; there is a fuzzy correspondence between sales volume influencing factors and sales volume levels. Based on this, this paper combines the data preprocessing technology of fuzzy membership and optimized deep learning algorithm, adding a self-encoding method with sparseness restriction, and proposes a deep learning sales forecasting model based on transformative computing with fuzzy membership-the super crown model (Super Imperial Crown Model, referred to as SICM). The model uses fuzzy membership to process the weighted relationship between sales influencing factors and sales rank, and uses a sparse autoencoder network to adaptively extract sample features; sales rank classification prediction uses Softmax classifier; BP fine-tuning is used to Achieve parameter optimization. Finally, use the collected transaction data to apply R software to simulate the optimized model and compare and analyze the comprehensive prediction performance. The results show that the super crown model can realize real-time and accurate dynamic sales classification prediction according to the characteristics of current online agricultural product transaction data, effectively overcome the imbalance of supply and demand caused by information imbalance, and promote the study of deep learning in the field of e-commerce transactions effect. Presented algorithm based on transformative computing techniques can be used in optimization of sales processes, management and analysis of sales markets. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Transformative computing
SICM
Fuzzy theory
Deep learning
Sales forecast
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
分享收藏分享收藏Drug response prediction by ensemble learning and drug-induced gene expression signatures.png)
GENOMICS
OAAI
GENOMICSIF3
OAAI分享收藏
查看更多内容