Development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements
2024, vol.16 , no.2, pp. 63-70
Article [2024-02-06]
The article continues to review the approach to designing the architecture of a distributed information monitoring system and quality management of communication services provided by the infrastructures of the Internet of Things and the industrial Internet of Things, based on solutions that support machine-to-machine and human-machine interaction. The development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements is proposed. The matrix structure of the LSTM network memory cell is proposed, which takes into account the spatio-temporal correlation of load parameters associated with the time lag of its propagation and is a matrix of connectivity of LSTM network hyperparameters and accumulated values of load parameters of monitoring nodes in the vicinity of a controlled monitoring node, taking into account the characteristics of the time series of propagation of load in stationarity moments.
distributed information monitoring system, quality management of communication services, network traffic forecasting, neural networks, decentralized control
https://doi.org/10.59035/OBHP8561
Osamah Adil Raheem, I. A. Aksenov , Yu. V. Redkin, A. V. Gorshkov , S. A. Sorokin , I. V. Atlasov , O. Ja. Kravets . Development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements. International Journal on Information Technologies and Security, vol.16 , no.2, 2024, pp. 63-70. https://doi.org/10.59035/OBHP8561