학술논문
Justification of the choice of neural networks learning algorithms for indoor mobile positioning
Document Type
Conference
Source
Proceedings of the 11th Central & Eastern European Software Engineering Conference in Russia. :1-6
Subject
Language
English
Abstract
Indoor Mobile navigation systems are becoming more widespread in many areas (transport, public institutions, logistics and others.). It is becoming popular navigation based on fingerprint radio access points Wi-Fi. As a mechanism for storing and processing the radio fingerprint is often considered a model of artificial neural networks (ANN). The paper examines the main issues related to the creation of complex programs for indoor mobile navigation using neural networks. We justify the choice of AAN learning algorithms for an indoor mobile navigation system.