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Neural network based efficient knowledge discovery in hospital databases using RFID technology

机译:使用RFID技术的医院数据库中神经网络的高效知识发现

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In a smart hospital that uses RFID technology the location and status of the entities inside the hospital are continuously tracked and are captured into the hospital database. Such a database stores enormous amount of spatial as well as temporal data. Transforming this huge data into actionable information is highly complex. Knowledge discovery in such databases is highly desirable and can be applied to various security aspects such as trait and trend analysis. In this paper, the process of data mining in hospital databases is discussed using both BPN and ART and their performance comparison is established. The technique that suits this application more effectively is analyzed and suggested.
机译:在使用RFID技术的智能医院中,医院内部的实体的位置和状态被持续跟踪并被捕获到医院数据库中。这种数据库存储巨大的空间和时间数据。将此巨大数据转换为可操作的信息非常复杂。在此类数据库中的知识发现是非常需要的,并且可以应用于各种安全方面,例如特征和趋势分析。在本文中,使用BPN和艺术讨论了医院数据库中的数据挖掘过程,并建立了它们的性能比较。分析并建议更有效地适用于该应用的技术。

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