7results about How to "Reduce communication data volume" patented technology

The invention relates to the technical field of micro-grids, and discloses an AC micro-grid distributed power control method with quantitative event triggering. According to the method, due to droop control in an island DC micro-grid, distribution of reactive power and unbalanced power in a system cannot be guaranteed, and a distributed control method with quantitative event triggering is provided for solving the problem. According to the control scheme provided by the invention, communication is reduced on the basis of realizing reactive power and unbalanced power distribution among distributed power generation units by adding a designed distributed secondary controller with a quantitative event triggering method, and parts which cannot be accurately distributed can be readjusted by a negative feedback system through PI control; in addition, the proposed method does not need global power information, each distributed generator only communicates with a neighbor when meeting a triggering condition, the communication burden of a micro-grid communication network is greatly reduced, the stability of the method is proved through a Russell invariant set principle, and Zeno behaviors are also eliminated through an anti-security method.

The invention discloses a progressive federal learning method and system based on model pruning. The system comprises a central server and a plurality of local clients. The central server gathers the uploaded local update, calculates to obtain the gathered global model update and expands the global model to obtain a new global model; and the local client performs local model training on the local data in parallel, performs layered pruning on the local model, and uploads the local model to the central server. The global model is gradually expanded, so that the communication overhead is reduced, the parallel computing amount of a server is reduced, and the training delay is reduced. And meanwhile, a hierarchical pruning technology is used, and the local update model of each client is pruned before the local update model is sent to the central server. According to the method and the system provided by the invention, the communication data volume between the terminal user and the cloud center can be reduced, and the accuracy of the training model can be extremely reduced.

The application relates to the technical field of unmanned aerial vehicle scheduling and intelligent optimization, and discloses a multi-unmanned aerial vehicle cooperative task allocation method and device for complex task scenarios, which has the technical scheme as follows: global multi-source data acquisition and space-time heterogeneous hypergraph representation, complex task causal emergence decoupling and counterfactual deduction optimization, hierarchical federated heterogeneous matching degree accurate representation, distributed external generalization causal element reinforcement learning dynamic allocation decision, distributed conflict resolution and digital twin closed loop iterative optimization; by adopting frontier technologies such as space-time heterogeneous hypergraph representation, causal emergence reasoning, hierarchical federated learning, causal element reinforcement learning and digital twin closed loop optimization, a causal driving full-link algorithm architecture is constructed to break through the inherent limitations of traditional correlation-based data-driven algorithms, so that efficient cooperative operation of a large-scale heterogeneous unmanned aerial vehicle cluster in a strong coupling task and an extreme dynamic environment can be realized.

The distributed adaptive estimation method based on fusion trigger detection and quantized transmission of the present application, nodes do not interact with neighbor nodes at the beginning, only use local information for single point estimation. When the fusion trigger condition is reached, communication with all neighbor nodes and fusion estimation are carried out, thereby reducing the communication times of distributed adaptive estimation. Further, the nodes only send quantized information in the fusion process, thereby reducing the communication data volume.

The application discloses an edge-computing-based lighting control panel energy consumption real-time optimization and early warning system and relates to the technical field of energy consumption optimization.The system solves the technical problem that independent optimization of control panel data uploaded to the cloud causes waste of calculation and bandwidth and poor real-time performance because a large number of control panels have similar states, and that a group aging benchmark is lacking, so that life balance cannot be achieved, resulting in premature failure of some equipment.Through clusters divided based on historical similarity maps, combined with average aging tracks in the clusters and real-time group feature centers, global collaborative optimization parameters are dynamically calculated by a multi-panel collaborative optimization module.The parameters are sent to the edge end, so that control panels in the same cluster with similar behavior characteristics can be collaboratively adjusted, redundant lighting and energy consumption waste in the region can be avoided, and energy consumption optimization at the group level can be achieved.Through construction of the average aging track in the cluster, the normal aging trend of each cluster can be mastered.

The invention provides a control method and system for remote touch of mobile terminal equipment, and the method is used for the control system for remote touch of the mobile terminal equipment: a control end responds to an external triggering touch event, obtains an original touch point sequence, and carries out the track thinning of the original touch point sequence to obtain a first touch point sequence; the first touch point sequence and the time increment of each touch point in the first touch point sequence are packaged and sent to a controlled end through an IMS network signaling channel; the controlled end stores the first touch point sequence into a jitter buffer queue and sorts the first touch point sequence to obtain a second touch point sequence; performing track fitting reconstruction on the second touch point sequence based on the time increment to obtain a target touch point sequence; and performing normalization processing on the target touch point sequence, mapping the coordinates into absolute coordinates of the local resolution of the controlled end, and executing the touch effect of the absolute coordinates according to the time increment. Through the method, the smoothness, the stability and the adaptability of remote touch control of the mobile terminal equipment are improved.