传感器融合
计算机科学
大数据
融合
卡尔曼滤波器
数据集成
过程(计算)
能源消耗
电子商务
数据挖掘
工程类
人工智能
电气工程
万维网
哲学
操作系统
语言学
标识
DOI:10.1109/icsess.2018.8663755
摘要
The traditional method of massive e-commerce data fusion based on the integrated averaging method is featured by high energy consumption and high total cost. Therefore, a distributed optimization technology based on distributed e-commerce data fusion is proposed in this paper. Innovating the concept of e-commerce data fusion under big data, implementing the data fusion algorithm based on the Kalman filtering method of data fusion, the massive e-commerce data fusion strategy was effectively improved by this algorithm. The effectiveness of massive e-commerce data fusion technology was verified through experimental demonstration. In the process of data fusion, it can reduce the energy consumption of the e-commerce system, save the total cost in the integration process, and improve the economic benefits of e-commerce.
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