dc.contributor.author | Ustebay, Serpil | |
dc.contributor.author | Atmaca, Tulin | |
dc.contributor.author | Sertbas, Ahmet | |
dc.contributor.author | Aydin, M. Ali | |
dc.contributor.author | Yiner, Zuleyha | |
dc.date.accessioned | 2021-03-03T10:43:00Z | |
dc.date.available | 2021-03-03T10:43:00Z | |
dc.identifier.citation | Ustebay S., Yiner Z., Aydin M. A. , Sertbas A., Atmaca T., "An Approach for Evaluating Performance of Magnetic-Field Based Indoor Positioning Systems: Neural Network", 24th International Conference on Computer Networks (CN), Ladek Zdroj, Polonya, 20 - 23 Haziran 2017, cilt.718, ss.412-421 | |
dc.identifier.other | av_243b3272-d140-4fe0-ac66-2ca1fde9f79f | |
dc.identifier.other | vv_1032021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/29252 | |
dc.identifier.uri | https://doi.org/10.1007/978-3-319-59767-6_32 | |
dc.description.abstract | Indoor Positioning Systems are more and more attractive research area and popular studies. They provide direct access of instant location information of people in large, complex locations such as airports, museums, hospitals, etc. Especially for elders and children, location information can be lifesaving in such complex places. Thanks to the smart technology that can be worn, daily accessories such as wristbands, smart clocks are suitable for this job. In this study, the earth's magnetic field data is used to find location of devices. Having less noise rather than other type of data, magnetic field data provides high success. In this study, with this data, a positioning model is constructed by using Artificial Neural Network (ANN). Support Vector Machines(SVM) was used to compare the results of the model with the ANN. Also the accuracy of this model is calculated and how the number of hidden layer of neural network affects the accuracy is analyzed. Results show that magnetic field indoor positioning system accuracy can reach 95% with ANN. | |
dc.language.iso | eng | |
dc.subject | BİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEM | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | Bilgisayar Bilimi | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Biyoenformatik | |
dc.subject | Bilgi Güvenliği ve Güvenilirliği | |
dc.subject | Bilgisayar Bilimleri | |
dc.subject | BİLGİSAYAR BİLİMİ, BİLGİ SİSTEMLERİ | |
dc.title | An Approach for Evaluating Performance of Magnetic-Field Based Indoor Positioning Systems: Neural Network | |
dc.type | Bildiri | |
dc.contributor.department | Centre National de la Recherche Scientifique (CNRS) , , | |
dc.identifier.volume | 718 | |
dc.contributor.firstauthorID | 150746 | |