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RFID-bad multi-attribute logistics information processing and anomaly mining in production
虎年福字logistics大象的鼻子像什么
期刊名称： International Journal of Production Rearch
关晓智扮演者作者： Cao, Xiaohua,Li, Tiffany,Wang, Qiang
豆腐制作年份： 2019年
攻的反义词关键词： production logistics;anomaly mining;RFID;similarity model;clustering
摘要：Timely collecting logistics information and finding anomalies of material supply plays a critical role in modern manufacturing systems. The problem is how to obtain multi-attribute logistics information of production logistics and build an effective approach for mining anomalies from the huge number of RFID data. The multi-attribute, randomness and various measure units of logistics states further aggravate the problem. In this paper, a novel RFID-bad logistics information processing approach is propod. Firstly, the state features of production logistics is discusd from multi-attribute
perspectives including time, location, quantities, quence and path, and a t of calculating models is t up to process RFID data for getting multi-attribute state data. Furthermore, in ca of the randomness and various measure units
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