Geodesic
Development of a system of proactive localization of the сyber-physical space based on machine learning methods
Informacionnye tehnologii i vyčislitelnye sistemy, no. 4 (2018), pp. 72-83 Cet article a éte moissonné depuis la source Math-Net.Ru

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Cyberphysical systems (CFS) are based on the seamless integration of computing power into the physical environment within an organization, enterprise, or production. In this paper we propose a system of proactive localization for tracking and forecasting the location of users and mobile robots. The developed system allows to predict the activity of the monitored object using various methods of machine learning. The paper presents comparative analysis of various machine learning models, as well as the concept of a proactive localization system.
Keywords: Cyberphysical system, time series forecasting, proactive localization, recurrent neural networks, reinforcement learning. 
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     author = {D. A. Malov and A. Y. Edemsky and A. I. Saveliev},
     title = {Development of a system of proactive localization of the {\cyrs}yber-physical space based on machine learning methods},
     journal = {Informacionnye tehnologii i vy\v{c}islitelnye sistemy},
     pages = {72--83},
     year = {2018},
     number = {4},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ITVS_2018_4_a7/}
}
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D. A. Malov; A. Y. Edemsky; A. I. Saveliev. Development of a system of proactive localization of the сyber-physical space based on machine learning methods. Informacionnye tehnologii i vyčislitelnye sistemy, no. 4 (2018), pp. 72-83. http://geodesic.mathdoc.fr/item/ITVS_2018_4_a7/