naa a22 4500 510792731 CHVBK 20180411083325.0 cr unu---uuuuu 180411e20130701xx s 000 0 eng 10.1007/s11277-012-0844-7 doi (NATIONALLICENCE)springer-10.1007/s11277-012-0844-7 Classification of GPS Satellites Using Improved Back Propagation Training Algorithms [Elektronische Daten] [Hamed Azami, Mohammad-Reza Mosavi, Saeid Sanei] Factor geometric dilution of precision (GDOP) is an indicator that shows the quality of GPS positioning and has often been used for choosing suitable satellite's subset from at least 24 orbited existing satellites. The calculation of GPS GDOP is a time-consuming task which can be done by solving measurement equations with complicated matrix transformation and inversion. In order to decrease this computational burden, in this research the artificial neural network (ANN) has been used. Although the basic back propagation (BP) is the most popular ANN algorithm and can be used in the estimators, detectors or classifiers, it is too slow for practical problems and its performance is not satisfactory in many cases. To overcome this problem, six algorithms, namely, BP with adaptive learning rate and momentum, Fletcher-Reeves conjugate gradient algorithm (CGA), Polak-Ribikre CGA, Powell-Beale CGA, scaled CGA, and resilient BP have been proposed to reduce the convergence time of the basic BP. The simulation results show that resilient BP, compared with other methods, has greater accuracy and calculation time. The resilient BP can improve the classification accuracy from 93.16 to 98.02% accuracy by using the GPS GDOP measurement data. Springer Science+Business Media, LLC., 2012 GPS GDOP nationallicence Classification nationallicence Artificial neural network nationallicence Basic back propagation nationallicence Resilient back propagation nationallicence Conjugate gradient algorithm nationallicence Azami Hamed Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114, Narmak, Tehran, Iran aut Mosavi Mohammad-Reza Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114, Narmak, Tehran, Iran aut Sanei Saeid Department of Computing, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK aut Wireless Personal Communications Springer US; http://www.springer-ny.com 71/2(2013-07-01), 789-803 0929-6212 71:2<789 2013 71 11277 https://doi.org/10.1007/s11277-012-0844-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11277-012-0844-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Azami Hamed Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114, Narmak, Tehran, Iran aut NATIONALLICENCE 700 1- Mosavi Mohammad-Reza Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114, Narmak, Tehran, Iran aut NATIONALLICENCE 700 1- Sanei Saeid Department of Computing, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK aut NATIONALLICENCE 773 0- Wireless Personal Communications Springer US; http://www.springer-ny.com 71/2(2013-07-01), 789-803 0929-6212 71:2<789 2013 71 11277 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer