基于朴素贝叶斯分类器的目标位置估计

2018 International Conference on Electrical Engineering and Computer Science (ICECOS) Pub Date : 2018-10-01 DOI:10.1109/ICECOS.2018.8605198

R. F. Malik, E. Pratama, H. Ubaya, Rido Zulfahmi, D. Stiawan, Kemahyanto Exaudi

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引用次数: 1

摘要

本研究以ieee 802.11标准上的接收信号强度指标(received Signal strength Indicator, RSSI)值为研究参数，讨论建筑物中物体的估计位置。RSS指纹测量的位置估计算法是朴素贝叶斯分类器。位置估算在sriwijaya大学计算机系统专业B栋1层进行，面积305,28 m2，长31.8米，宽9.6米。通过对比训练数据集和数据测试进行位置估计的结果表明，通过坐标点(11.3)对房间2的预测，估计是成功的。

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Object Position Estimation Using Naive Bayes Classifier Algorithm

This study discusses the estimated position of objects in buildings with the value of Recieved Signal Strenght Indicator (RSSI) on ieee 802.11 used as the research parameter. The algorithm used in estimating the location of the RSS Fingerprint measurement is the naive bayes classifier. Position Estimation is done on the 1st floor of building B majoring in computer system, university sriwijaya with an area 305,28 m2 with length 31.8 meters and width 9.6 meters. The result of the position estimation that has been done by comparing training dataset with data testing shows that the estimation is successful with the prediction of room 2 with the coordinate point (11.3).

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2018 International Conference on Electrical Engineering and Computer Science (ICECOS)

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