5results about How to "Reduce the calculation dimension" patented technology

The application discloses a kind of arbitrary multiport S parameter calibration and de-embedding method, belong to multiport calibration field.Method includes: using network analyzer respectively on interpolation after S parameter data base of calibration piece each single-port measurement, error term of each single-port is solved;Using network analyzer respectively on calibration piece multiport measurement, determine the arbitrary multiport S parameter measurement data of switch item and isolation item correction completion;Based on the multiport error of target through path generated by radiation, and using the multiport error of target through path, the multiport error of other path outside target through path is completed, to combine the error term of each single-port to the arbitrary multiport S parameter measurement data of switch item and isolation item correction completion is calibrated and de-embedded, and the multiport calibrated S parameter matrix is obtained.This scheme can improve calibration accuracy and calculation efficiency.

The application provides a power grid fault traveling wave positioning method based on a fusion optimization algorithm, comprising: establishing a dynamic virtual fault framework model of a power grid, randomly generating a plurality of virtual fault particles containing position coordinates, and constructing an initial virtual fault particle cluster; using a shortest path algorithm to calculate the topological path length of each virtual fault particle in the virtual fault particle cluster to all measurement points in the power grid, and then calculating a virtual fault space-time feature vector; setting the traveling wave arrival time when a real fault occurs as a target clustering centroid in a feature space, and calculating a feature matching fitness; constructing a non-convex optimization problem with the optimal feature matching fitness as a target, solving the problem using a fusion optimization algorithm, and thus obtaining a fault positioning result and a traveling wave velocity, so as to realize traveling wave positioning. The application can solve the problems of local optimum, slow convergence speed and high calculation cost in the prior art.

The application discloses a multi-agent cooperative navigation optimization method, and the optimization method takes a multi-agent deep deterministic policy gradient algorithm as a basic framework; the following mechanism is introduced in the training stage: in the multi-agent cooperative navigation training stage, a joint priority experience extraction mechanism is introduced, joint experience samples are extracted and spliced according to the time difference error priority through cross-agent synchronization indexing; an information discarding and correction compensation mechanism is introduced at the input end of the centralized Critic network, information from other agents is divided into independent information blocks, the information blocks are randomly discarded with a preset probability, and a correction factor is applied to the retained information blocks to maintain the mathematical expectation of the input data unbiased, and the input of the reduced Critic network is obtained. The application provides a multi-agent cooperative navigation optimization method which can improve the key experience utilization rate, reduce the dependence of the model on high-dimensional global input, and enhance the robustness in a communication limited environment.

The application relates to the technical field of electric power transaction data processing, and discloses a power spot transaction data time sequence mining method capable of representing market fluctuation characteristics, which comprises the following steps: performing variational mode decomposition on electric price data, locking a probability density trough by using kernel density estimation to determine a dynamic shunt threshold, routing components to a trend or fluctuation channel according to the dynamic shunt threshold, respectively generating prediction values by using a linear extrapolation model and a multi-head attention mechanism with a causal mask introduced and superimposing the prediction values, the application realizes adaptive boundary locking in a non-stationary environment by using data topological morphology, and blocks invalid feature interference by mutual information causal gating, solves the contradiction between mean regression and peak capture of a traditional model, and improves the effectiveness of a prediction result.

This invention relates to the field of drone smoke grenade generation and control technology, and provides a drone smoke grenade deployment control method and system. The method includes: constructing calculation models for calculating the real-time coordinates of a threat, a drone, and a smoke grenade; based on the calculation models, determining the effective shielding conditions of the smoke cloud formed by the smoke grenade against a real target in the vertical and horizontal directions; based on the calculation models and the effective shielding conditions, constructing an optimal deployment model for the drone to deploy a single smoke grenade; and deploying the smoke grenade based on the optimal deployment model to form a smoke cloud that effectively shields the real target, thereby avoiding interference from the threat. According to the solution of this invention, the effective shielding determination conditions provided by this invention are easy to operate and calculate, have high timeliness, and can accurately calculate the effective shielding duration of the smoke cloud generated by the smoke grenade against the target.