Adequate management of modern corporate communication networks is possible if many control procedures function in near real time. In this case, the processed network monitoring data must have accurate characteristics sufficient for making objective management decisions. This fully applies to the data monitoring of network traffic parameters, which determines the relevance of the proposed work. The proposed in the paper algorithm for on-line estimation of traffic parameters in corporate multiservice communication networks is based on the concept of conditional nonlinear Pareto-optimal filtering V. C. Pugachev. Its essence is that the estimation of traffic parameters is performed in two stages - in the first stage, we evaluate the forecast values of parameters, and in the second, with the next observations of random sequences, we make adjustments to their values. Traffic parameter values forecasts are constructed in a small-sized sliding window, and the adjustment is implemented on the basis of pseudo-gradient procedures whose parameters are adjusted using a fuzzy control algorithm based on the Takagi-Sugeno method. The proposed algorithm belongs to the class of adaptive algorithms with prior learning. The maximum value of the average relative error of estimation of traffic parameters was less than 8.2%, which is a sufficient value for the implementation of operational network management tasks. At the same time, the actual scientific and technical task is to analyze the comparison of the characteristics of the developed adaptive algorithm with the characteristics of the optimal algorithms, the characteristics of which are the maximum achievable. Translated with www.DeepL.com/Translator (free version). The results of a comparison of the proposed method with the optimal Coleman filtration (OKF) are presented.

An adaptive method for estimation the traffic characteristics in high-speed corporate multiservice networks based on the methods of preliminary indistinct computer training, functioning in real time mode, is proposed and investigated in this paper. The relevance of the study is due to the fact that many processes of network management in high-speed corporate multiservice communication networks need to be implemented in a mode close to real time. The approach proposed in the paper is based on the concept of conditional nonlinear Pareto-optimal filtering V. C. Pugachev. The essence of this approach consists in the fact that estimation of the traffic parameter is performed in two stages - on the first stage the parameter value prediction is estimated, and on the second stage, when the next parameter observations are received, the parameter values are corrected. In the proposed method and algorithm, predictions of traffic parameter values are made in a small sliding window, and adaptation is implemented based on pseudo-gradient procedures whose parameters are adjusted using the Takagi-Sugeno indistinct logic inference method. The proposed method and algorithm belong to the class of adaptive methods and algorithms with prior learning. The average relative error of the estimated traffic parameters estimation does not exceed 8.2%, which is a sufficient value for the implementation of operational network management tasks.

Modern research in the field of oceanology in the Arctic region, studying the ice conditions, environmental and climatic monitoring, prospecting and hydrographic works, monitoring of extended bottom structures, oceano-graphic measurements, search for sunken objects, chemical and physical measurements of the aquatic environment, research of underwater objects and bottom topography cannot be imagined without the use of autonomous unmanned submersibles. Underwater robotics is rapidly developing. In the course of technological progress the scope of applications of autonomous unmanned submersible crafts has significantly expanded. The priority areas of robotics involve developing the intelligent methods and models to control operation of the autonomous submersibles in the extreme and uncertain environmental conditions, developing the architecture of autonomous submersibles, and solving problems of navigation and communication. Each class of autonomous submersible crafts has not only the advantages, but also the disadvantages that limit the scope of their application. Analysis and comparison of autonomous submersibles are carried out, the trends in their development are determined. The alternative classification of autonomous unmanned underwater crafts by the shape of the hull. Various versions of autonomous underwater vehicles and examples of underwater robotics are illustrated. Autonomous unmanned submersible crafts having a bluff shape, well-streamlined cylindrical shape, well-streamlined non-cylindrical shape, well-streamlined bionic shape are considered in detail, the system of control over the submersibles is analyzed.

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