11 results about "Network awareness" patented technology

The invention provides an aluminum substrate drilling tool wear prediction method based on reinforcement learning, and the method comprises the steps: collecting working condition parameters, such as main shaft rotation speed, feeding speed, cutting depth, material type and historical vibration energy, through the deployment of an industrial sensor network, and achieving data standardization through feature extraction and normalization processing; a dynamic cognitive map with process meaning is constructed by adopting semantic analysis and a map generation strategy, key semantic nodes are identified by utilizing a map attention network, reinforcement learning is driven through a structured reward function, and self-adaptive optimization of a wear prediction strategy is realized; according to the method, abnormal detection and working condition abrupt change increment updating are supported, map consistency optimization is achieved by fusing expert experience, the tool wear prediction precision and the environment adaptability can be improved, and the intelligent sensing and dynamic response capacity to the complex manufacturing process can be enhanced.

The invention discloses a fault diagnosis method and device for electrical equipment, electronic equipment and a storage medium. According to an electromagnetic interference index, the data acquisition frequency and range are dynamically adjusted, high-frequency acquisition is pertinently started for state abnormal equipment so as to accurately capture abnormal signals, and multi-source data such as partial discharge pulses are fused. An equipment state feature sequence is constructed in combination with historical operation data, and high-correlation sensitive features are screened, so that the limitation of a single parameter is avoided; meanwhile, early faults are recognized and early warning is output through a pre-trained long-short-term memory neural network, a protection constant value is rechecked in cooperation with a rule engine and a convolutional neural network, a standby loop is automatically switched or the constant value is adjusted when abnormity occurs, and a complete monitoring-early warning-response closed loop is formed; the technical effects of improving the equipment state evaluation comprehensiveness, enhancing the early fault recognition capability, improving the early warning accuracy, increasing the response speed of the protection system and guaranteeing the operation safety and reliability of the electrical equipment and the power grid of the power plant are achieved.

The invention discloses a cross-data center RDMA network congestion control method and device based on in-band telemetering, and belongs to the technical field of network transmission control. The method comprises the following steps: sending a first cross-data center flow to an upstream DCI switch at an initial rate; according to a Switch-INT message returned by an upstream DCI switch, a first fair rate is calculated, a second cross-data center flow is sent to the upstream DCI switch at the first fair rate, an ACK message of a downstream data center responding to the first cross-data center flow is obtained, and the ACK message comprises a suggested rate; and generating a final rate in combination with the first fair rate and the suggested rate, and sending a third cross-data center flow to an upstream DCI switch at the final rate. According to the method, the network sensing capability of the cross-data center flow can be improved, the fairness of the flow in the data center and the cross-data center flow is improved, and the transmission delay of the datagram is optimized.

The embodiment of the invention relates to a processing method and device for planning a short message retransmission strategy based on a network awareness state. The method comprises the following steps: carding a state type set S, defining a cost index C, and configuring a strategy parameter set and a strategy parameter value domain DP corresponding to the strategy parameter set; constructing an index prediction model and a strategy prediction model; constructing a first data set; training an index prediction model based on the first data set; optimizing the optimal strategy configuration corresponding to each state sample by taking the minimum cost index as an optimization target, and constructing a second data set based on all the state samples and the corresponding optimal strategies; training a strategy prediction model based on the second data set; and the strategy prediction model and the index prediction model dynamically plan the short message retransmission strategy of the server according to the real-time network state of the short message sending server and predict the cost index of the planning strategy. According to the invention, the configuration flexibility of the short message retransmission strategy can be improved, and the cost control can be optimized.

This invention relates to the field of human-computer interaction and intelligent control technology, and discloses a control method and system for an intelligent mouse. The method comprises five steps: user action acquisition, action feature encoding, semantic intent recognition, mouse behavior mapping, and feedback adjustment and optimization. The system comprises a motion acquisition and feature extraction module, an intent recognition and control signal generation module, and a behavior feedback and adaptive optimization module. By integrating an inertial measurement unit and a pressure sensor to acquire three-dimensional hand motion data, combining temporal convolutional coding and a Transformer network to recognize user operation intent, and generating mouse control signals based on context, precise control and adaptive optimization of the mouse are achieved. This invention enables complex operations without physical buttons, improving the personalization and intelligence of mouse control. It is applicable to intelligent interactive devices, auxiliary input systems, and other scenarios.

A network awareness assisting method and a communication device are applied to the technical field of communication. The method comprises the following steps: a terminal sends first request information, wherein the first request information is used for requesting first sensing information; then, the terminal receives first sensing information from the access network equipment, and the first sensing information indicates one or more of the following items: first environment point cloud information, first environment power spectrum information or first obstacle position information; and then, the terminal performs task reasoning based on the first perception information. By adopting the method, the task execution efficiency can be improved.

A network perception method, distributed device, equipment and computer readable storage medium. In the device forwarding layer, the message is not encapsulated, the device bandwidth during forwarding is guaranteed, and the device bandwidth utilization is improved; real-time detection and flow sampling reporting are performed to guarantee data accuracy and low overhead of the control layer; the control layer sends information of the control layer state table according to a sending weight, so that the management layer can receive important network state information more preferentially, and the overall overhead of the management layer is reduced; compared with the existing network perception technology based on in-band measurement, by maintaining the forwarding layer state table, the perception level is adjusted from a data packet to a data flow level, the consumption of network bandwidth resources is reduced, and the processing complexity and the consumption of computing resources of the management layer are also reduced.

The invention provides a network security event analysis method and system through network awareness, and the method comprises the steps: obtaining channel data of a base station, the channel data comprises a physical layer channel parameter and a transmission layer channel parameter, building a first initial time domain tensor based on the historical data of the physical layer channel parameter, and transmitting the first initial time domain tensor to a second initial time domain tensor; constructing a second initial time domain tensor based on the historical data of the transmission layer channel parameters, inputting the second initial time domain tensor into a preset baseline construction model, and outputting baseline data; constructing a real-time time domain tensor based on the real-time data of the physical layer channel parameters, inputting the real-time time domain tensor into a baseline construction model, and obtaining a real-time feature vector based on the baseline construction model; calculating a network security event dynamic threshold based on the baseline information entropy of the baseline data, and calculating a real-time abnormal value based on the real-time feature vector and the baseline mean vector of the baseline data; and calculating a normalized deviation degree based on the real-time abnormal value and a security event dynamic threshold value, and judging whether a network security event occurs in the base station or not.

The invention provides a multi-network integration data processing method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring data traffic information in a plurality of systems, and carrying out preprocessing and time-space alignment on the data traffic information to obtain a plurality of data sequences for the plurality of systems; acquiring traffic statistical feature vectors of the plurality of data sequences, and performing feature fusion on the traffic statistical feature vectors of the plurality of systems based on an attention weighting algorithm to obtain a fused feature vector and a network state recognition result; generating a first network bandwidth resource allocation strategy based on the fusion feature vector, the corresponding network state recognition result and the flow feature vectors of the multiple systems; and executing at least one of bandwidth allocation, routing adjustment and link switching on the network bandwidth resources in the plurality of systems based on the first network bandwidth resource allocation strategy. According to the invention, dynamic resource allocation in a cross-network fusion scene can be realized, and the network awareness, intelligent scheduling and remote management capabilities of the system are significantly improved.

This disclosure describes methods and apparatus for UE to perform data collection for NW side model training with network awareness for wireless communication systems, further comprising the steps of the UE receives the data collection configuration from the serving cell, which provides the measurement configuration for the UE to perform measurement for an AI / ML-enabled feature / feature group or a functionality for the AI / ML-enabled feature / feature group; performs measurement according to the measurement configuration, logs and stores the data; receives RRCReconfiguration message from the serving cell and handles the measurement configuration and logged data according to the command. The overall procedure contains the stage of handle data collection configuration, data collection and storage, and data availability indication.

The invention provides a computer network alarm system and method, and the method comprises the steps: binding all communication interaction modes with risk verification links between corresponding communication nodes, and obtaining a weakness relation network which decides the network vulnerability distribution in a target communication network; identifying a plurality of attack threat paths from a network peripheral access point to internal protected resources, and determining an inherent threat value of each attack threat path; setting a behavior alarm rule of a real-time access behavior by comparing the access behavior characteristics with a basic threat level of a corresponding communication node, and determining a risk evaluation value of a current overall threat condition; and when the risk evaluation value is greater than a preset alarm trigger value, initiating directional inquiry to a communication node in the corresponding attack threat path, judging whether an attack activity exists according to returned exploration response information, and meanwhile, performing active isolation alarm. By adopting the scheme of the invention, the accuracy of computer network alarm can be improved through a global vulnerability assessment mechanism.