基于多维关联规则的无线传感器网络牛群健康监测数据挖掘技术

Ankit R. Bhavsar, Harshal A. Arolkar
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引用次数: 8

摘要

无线传感器网络在其使用寿命期间会产生大量的数据。有时这些数据格式未知,体积庞大。因此,数据存储和适当的挖掘技术成为该领域的关键问题。从无线传感器网络数据中提取知识是近年来数据挖掘技术的新进展。针对基于无线传感器网络的牛健康监测系统,提出了一种基于多维关联规则的数据挖掘技术。我们还概述了数据挖掘概念,并选择了一些用于wsn数据的挖掘技术。我们已经讨论了在牛身上发现的不同疾病及其症状。最后,我们提出了一种基于规则的基于症状的疾病识别挖掘技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multidimensional Association rule based data mining technique for cattle health monitoring using Wireless Sensor Network
Wireless Sensor Networks produce large amount of data during their lifetime operation. Sometimes this data is in unknown format and bulky. Hence data storage and appropriate mining technique become a critical issue for this domain. Recent innovation in data mining technique receives attention in extracting knowledge from WSNs data. In this paper, we have proposed a Multidimensional Association rule based data mining technique for a cattle health monitoring system based on WSN. We have also given an overview of data mining concept with some selected mining techniques used for WSNs data. We have discussed the different diseases and their symptoms found in cattle. Finally we have proposed a rule based mining technique for identifying the disease based on symptom.
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