Object Position Estimation Using Naive Bayes Classifier Algorithm

被引：0

作者：

Malik, Reza Firsandaya ^{[1
]}

Pratama, Eko ^{[1
]}

Ubaya, Huda ^{[1
]}

Zulfahmi, Rido ^{[1
]}

Stiawan, Deris ^{[1
]}

Exaudi, Kemahyanto ^{[1
]}

机构：

[1] Univ Sriwijaya, Fac Comp Sci, Commun Network & Informat Secur Res Lab, Palembang, Sumatera Selata, Indonesia

来源：

2018 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (ICECOS) | 2018年

关键词：

Position Estimation; RSS Fingerprint; RSSI;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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 m(2) 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).

引用

页码：39 / 43

页数：5

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