Компьютерное регулирование состояния контуров резервов

For the compound-structural multi-component deposits one of the most laborious problems at the stage of initial treatment of geological information is the picking of the conditional intersections – the aggregate of deposed consecutively samples. The last ones must answer the demanded conditional limitations at mineral raw material and be a some row of the appointed typosort of ore or rock at the deposit considering part. The work effectiveness and reliability by this depends vastly on the executor's experience and intuition. The large volume of initial information, a lot of variants of its interpretation and problem decision's multiciphemess demand scientifically grounded approach to determination of the conditional intersections with the computers use. At the base of the elaborated algorithm the automated picking of the conditional intersections is proposed

Novel Modification of the Collective Dynamic Routing Method for Sensors’ Communication in Wi-Fi Public Networks

The widespread use of the Internet of Things makes it relevant to use public IP networks for simultaneous access by both users and wireless sensors. To achieve this, a significant reduction in the subscriber devices’ energy consumption is required. This paper analyzes the application features of the collective dynamic routing method both with and without the use of a robust method for estimating the channel data rate for sensors’ communication in wireless public networks. Based on the analysis, a novel modification of the collective dynamic routing method has been developed that reduces the sensors’ energy consumption while keeping a high data rate and short delivery time for users. An analysis of the network load, the total data transfer rate over the network, and the parameters affecting the sensors’ energy consumption was carried out for a segment of a seamless IEEE 802.11ax network. The simulation demonstrated a high efficiency of using a novel modification of the collective dynamic routing method for access to users and wireless sensors

An Approach for Using a Tensor-Based Method for Mobility-User Pattern Determining

Modern mobile networks exhibit a complex heterogeneous structure. To enhance the Quality of Service (QoS) in these networks, intelligent control mechanisms should be implemented. These functions are based on the processing of large amounts of data and feature extraction. One such feature is information about user mobility. However, directly determining user mobility remains challenging. To address this issue, this study proposes an approach based on multi-linear data processing. The user mobility is proposed to determine, using the multi-linear data, about the changing of the Signal-to-Interference-plus-Noise-Ratio (SINR). SINR varies individually for each user over time, relative to the network’s base stations. It is natural to represent these data as a tensor. A tensor-based preprocessing step employing Canonical Polyadic Decomposition (CPD) is proposed to extract user mobility information and reduce the data volume. In the next step, using the DBSCAN algorithm, users are clustered according to their mobility patterns. Subsequently, users are clustered based on their mobility patterns using the DBSCAN algorithm. The proposed approach is evaluated utilizing data from Network Simulator 3 (NS-3), which simulates a portion of the mobile network. The results of processing these data using the proposed method demonstrate superior performance in determining user mobility