10 results about "Multiple aggregation" patented technology

The invention provides a pipeline overturning lining repair operation process monitoring and evaluation method and device and a computer readable storage medium, through introducing a PELT change point detection algorithm, time sequence data is divided into different time periods based on the detected change point number, and then feature vectors of different time periods are extracted; based on the multi-dimensional feature vectors, the Transform model is adopted to predict the future features of the process parameters, the prediction precision of the Transform model is improved, accurate process parameter monitoring is achieved, a multi-index decision CoCoSo method is introduced, through multi-aggregation strategy fusion, the optimal solution is pursued, the consistency of all strategies is considered, the reliability of the decision result is improved, and the method is suitable for large-scale popularization and application. Therefore, a reliable process state evaluation result is obtained, dynamic monitoring and adjustment of process parameters of overturning lining repair operation are achieved, the repair quality is improved, and safe and stable operation of a gas pipeline system is guaranteed.

A method for generating a spatial model tile data organization structure, relating to the field of geographic information technology, is characterized by the following steps: generating tile network leaf nodes; generating tile network intermediate nodes; selecting an initial aggregation point for the tile leaf nodes and performing multiple aggregation operations with each leaf-level tile until all leaf-level tiles are aggregated to obtain multiple tile aggregates; binding the tile network leaf nodes to their parent tile network intermediate nodes based on the correspondence between the tile network leaf nodes and the aggregated tile network intermediate nodes, ensuring that each tile network intermediate node has a logical relationship with its child nodes; and generating a tile network root node. Advantages: Effectively generates a multi-level detailed tile organization structure for model data in a given data block; the level of detail in each layer of tile data is reasonable, and the data organization is efficient; the data storage scale of a single tile is low and stable, saving network bandwidth and improving file transfer efficiency.

The application discloses a kind of object group determination method, device, equipment, storage medium and program product, involve artificial intelligence and data processing technical field.The method comprises: obtaining the aggregation zone structure graph corresponding to reference object group, and the multiple aggregation zone structure graphs corresponding to the network to be detected;Obtain the distributed representation corresponding to reference object group, and the multiple distributed representations corresponding to the network to be detected, the distributed representation is used to represent the structural features of aggregation zone structure graph;According to the distributed representation corresponding to reference object group, determine the target aggregation zone structure graph from the multiple aggregation zone structure graphs corresponding to the network to be detected;Obtain the target object group corresponding to target aggregation zone structure graph.The application determines the object group by supporting the aggregation zone level, without determining object one by one, and considering the overall correlation of object group, so as to improve the determination efficiency and determination accuracy of object group.

A computer system displays a graphical user interface that includes a data visualization region, a shelf region, and a schema information region. The computer system receives a first user input to place a first dimension data field from the schema information region into the shelf region. In accordance with the first user input, the computer system determines a visualization level of detail that is based on at least the first dimension data field. The computer system receives a second user input to specify a first aggregation. The first aggregation has a custom level of detail that is distinct from the visualization level of detail. The computer system builds a visual specification that includes the visualization and custom levels of detail. The computer system generates a data visualization corresponding to the visual specification and displays the data visualization in the data visualization region.

The application provides a kind of virtual power plant task scheduling processing method, electronic equipment and storage medium, belong to power distribution network control technical field.The method comprises: receiving to be scheduled task, to be scheduled task includes target power and power deviation threshold;According to to be scheduled task, select multiple aggregation units with different aggregation types and distribution positions from the regulation unit library as the first unit, and issue the first scheduling instruction of executing target power to the first unit;Select multiple aggregation units matched with the aggregation type and distribution position of the first unit from the margin unit library as the second unit, and issue the second scheduling instruction of executing power deviation threshold to the second unit;According to the response result of first scheduling instruction and second scheduling instruction, the first unit that does not satisfy the first condition is adjusted to the margin unit library, and the second unit that satisfies the second condition is adjusted to the regulation unit library.The application improves the test dynamicity and accuracy of aggregation unit response deviation degree.

To assist with replanting work. [Solution] The afforestation system includes a processor. The processor sets up multiple aggregation areas in an afforestation area where multiple plants are planted, calculates a numerical value related to plant death for each aggregation area, and generates display data showing the relationship between the aggregation areas and the numerical values ​​of the aggregation areas.

The invention discloses a traffic matrix calculation method and device, a storage medium and electronic equipment, and the method is applied to the field of network traffic detection, and comprises the steps: collecting the node information of each node in a target network, and determining the network information of a plurality of aggregation domains according to the network information of the target network and the node information of each node; expanding the target information according to the network information of the plurality of aggregation domains, and constructing a target mapping relationship between each node in the target network and the plurality of aggregation domains according to the expanded target information; collecting traffic data of each node in the target network through a distributed traffic collection tool; and calculating an aggregation traffic matrix of the target network according to the target mapping relation and the traffic data of each node. Through application of the method and the device, the problem that the response speed of a service system is relatively low due to the fact that the calculation load and the storage demand of the traffic matrix are increased in a square level along with the expansion of the network scale in a service scene of real-time traffic matrix updating in related technologies is solved.

The application discloses a kind of multistage cache aggregation computing method and device, it is related to cache aggregation computing technical field, the method includes: connecting message bus, obtains the first level cache corresponding to stack top;When subscribing to the data of same time dimension and device dimension, cumulative aggregation calculation is carried out with original data;Whether the first event task belongs to the time interval defined in range is judged;When the timing task corresponding to the first event task triggers, set delay waiting time;At the same time, the data of the first level cache is transmitted to external cache middleware, and the data of same time dimension, device dimension is updated and merged.The application solves the technical problems of single cache mode, limited aggregation mode, low data storage and processing efficiency in the prior art, improves the efficiency of time series data processing, reduces memory usage and delay, supports multiple aggregation modes, and enhances the technical effects of system performance and scalability.

The invention provides a virtual power plant task scheduling processing method, electronic equipment and a storage medium, and belongs to the technical field of power distribution network regulation and control. The method comprises the following steps: receiving a to-be-scheduled task, wherein the to-be-scheduled task comprises target power and a power deviation threshold value; selecting a plurality of aggregation units with different aggregation types and distribution positions from an adjustment unit library according to the to-be-scheduled task as first units, and issuing a first scheduling instruction for executing target power to the first units; selecting a plurality of aggregation units matched with the aggregation type and the distribution position of the first unit from the margin unit library as second units, and issuing a second scheduling instruction for executing a power deviation threshold to the second units; according to response results of the first scheduling instruction and the second scheduling instruction, the first units which do not meet the first condition are adjusted to the margin unit library, and the second units which meet the second condition are adjusted to the adjustment unit library. According to the invention, the test dynamics and accuracy of the response deviation degree of the aggregation unit are improved.

A federated learning method applied to the field of artificial intelligence technology. In the method, when the aggregation node obtains models of different network structures, the models of the same network structure are divided into the same group, and the parameters of the models in the same group are aggregated to obtain multiple aggregation models with different network structures; and for each aggregation model, knowledge distillation training is performed on each aggregation model based on the multiple models obtained originally, to realize experience transmission between models of different network structures, thereby integrating the knowledge and experience of models of various network structures, combining the advantages of parameter aggregation and knowledge distillation in integrating model experience, realizing aggregation of models of different network structures, and ensuring the prediction accuracy of the model obtained after aggregation.