13results about How to "Save computing time" patented technology

The invention discloses a high-precision coordinate calculation method based on Matlab, and belongs to the field of coordinate calculation technology and data processing, and the method comprises the steps: firstly, obtaining the combination of all points and vectors through a specific combination generation function, and then initializing a result vector; aiming at each combination, calculating intersection point coordinates and parameters by virtue of an accurate geometric intersection point calculation function, storing the intersection point coordinates and parameters in a result vector, and distributing the intersection point coordinates and parameters to a working area according to a rule by virtue of a working area assignment function; then, a midpoint coordinate matrix is obtained by applying a midpoint calculation function based on the coordinates of the intersection points, the distance between the points is calculated, a clustering center is determined by adopting a clustering algorithm, points of an intersection point concentrated area are screened out according to distance characteristics in a cluster, and finally, high-precision coordinates are calculated through a weighted average calculation function in combination with priori knowledge and weights. According to the method, the coordinate calculation precision can be effectively improved, good noise immunity is achieved, priori knowledge can be fully fused, and the method is suitable for numerous fields with high coordinate precision requirements.

The application belongs to the field of computer vision, and discloses a local refinement mapping system and method based on SLAM and semantic segmentation, which applies binocular camera video acquisition images, a semantic segmentation module is built by a DANet model based on an FCN network framework, channel attention modules and spatial attention modules in the network model are applied to the DANet model to process scene images, target recognition and semantic segmentation are realized, feature points extracted from a target scene segmented by the semantic segmentation are subjected to pose estimation with the same feature points in other images through a front-end visual mileage module, a key frame is selected from the global of camera pose by a back-end optimization module, a global constraint is established by using the relationship of key frame inspection, a pose graph is constructed, a loop detection module optimizes the pose graph according to the error of camera pose and the pose graph, global consistent pose estimation is obtained, and the performance of SLAM local refinement mapping is improved.

The application discloses a kind of battery core temperature online estimation and prediction method, system, equipment and storage medium based on mixed TSDM-AMBO-GRU, applied to lithium ion battery core temperature estimation and prediction field, comprising: obtaining battery operating data, and utilizing TSDM to create synthesis of battery operating data, as training set with battery operating data together;Training set is input to BO-GRU-AM framework, and the battery core temperature prediction model based on BO-GRU-AM is obtained by training;Input test set to battery core temperature prediction model, and obtain battery core temperature prediction result.The application not only can effectively overcome the problem caused by uneven distribution of temperature sensors and limited data in lithium ion battery system, and can realize real-time, efficient and accurate battery core temperature prediction under various temperatures and complex conditions, provide reliable fault warning and real-time monitoring support for BMS in practical application.

The chain system fixed-point resampling method belongs to the technical field of rotating machinery signal processing, and aims to solve the problems that the time domain signal regularity of a single chain link is poor, the dynamics characteristics of the whole system are difficult to directly reflect, and the frequency domain feature extraction cannot be performed. The method comprises the following steps: extracting original data of discrete motion units from multi-body dynamics simulation results; at the preset data monitoring point position of the system, the nearest discrete motion unit is searched as a monitoring unit in real time by calculation; according to the data type, one of a direct method, a synthetic method and an average method is adopted to process the original data of the monitoring unit, and feature data representing the dynamics state of the fixed position are generated; and finally, the feature data are written into a file in time sequence. The time sequence data of the fixed position are collected through the fixed-point resampling method, and the problems that the data is strong in contingency, poor in regularity, and difficult to perform in-depth frequency domain and statistical analysis due to tracking a single motion unit are solved.

The present application belongs to the technical field of seismic wave acquisition, and particularly relates to an abnormal seismic wave data correction method, device, equipment, medium and program product. The present application provides an abnormal seismic wave data correction method, which comprises the following steps: acquiring seismic wave data sets collected by each geophone in a target geophone group; determining abnormal data in each seismic wave data set by using an isolated forest algorithm; determining the position of an interference source causing data abnormality according to each abnormal data; and correcting the abnormal data according to the position of the interference source. The present application solves the problem that a large amount of computing resources are wasted to calculate interpolation when correcting abnormal data in seismic wave data in the prior art, realizes fast correction of abnormal data in seismic wave data, saves computing resources and computing time, and can quickly locate the position of an interference source, thereby providing technical support for solving the problem that seismic wave acquisition is easily disturbed.

The invention provides an audio processing method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring an audio to be played, and converting time domain data of the audio to be played into frequency domain data; detecting a tone type contained in the audio to be played based on the frequency domain data; in response to a target timbre existing in the timbre type, obtaining a timbre operator corresponding to the target timbre; and performing signal enhancement for the target tone on the frequency domain data according to the tone operator to obtain an audio to be output. According to the method, selective enhancement can be carried out by applying the timbre operator only when the target timbre is detected, so that the timbre operator is prevented from being used for all to-be-played audios without difference, and the pertinence and accuracy of audio processing are realized.

The present application belongs to the technical field of electrocatalytic materials, and particularly relates to a method for screening high-selectivity iron-nitrogen-carbon electrocatalysts for NO3RR based on a curved structure. The method aims to solve the technical problem of low selectivity of ammonia, the target product, in the nitrate reduction process of existing iron-nitrogen-carbon electrocatalysts due to competing side reactions. The method comprises the following steps: firstly, constructing a planar iron-nitrogen-carbon structure model and a series of tubular iron-nitrogen-carbon structure models with different curvatures; secondly, calculating the adsorption energies of nitrogen atoms and oxygen atoms for the planar and tubular structure models, respectively, and selecting a target tubular iron-nitrogen-carbon structure model based on the adsorption energy data; thirdly, calculating the reaction Gibbs free energies of the planar model and the target tubular model for reducing nitrate to various nitrogen-containing products; and finally, drawing a reaction path free energy diagram at zero potential based on the reaction Gibbs free energies, and analyzing the specific influence of the curved structure on the selectivity of the iron-nitrogen-carbon electrocatalytic nitrate reduction reaction, thereby guiding subsequent experimental research.

The invention provides a method, device and equipment for determining a thickening CO2 flooding development scheme, a medium and a product, and relates to the technical field of oil and gas development. The method comprises the steps of obtaining a plurality of initial development schemes of a target oil reservoir, wherein the initial development schemes are obtained by permutation and combination of a plurality of preset values corresponding to a plurality of development characteristic parameters; inputting each initial development scheme into a pre-trained development dynamic prediction learning model to obtain development dynamic data corresponding to each initial development scheme; adopting a preset multi-target mathematical model to calculate a plurality of index values corresponding to each initial development scheme; determining a candidate development scheme set by adopting a multi-objective collaborative optimization algorithm according to the plurality of index values corresponding to each initial development scheme; and determining a thickening CO2 flooding target development scheme of the target oil reservoir based on the preset weight threshold values corresponding to the indexes. According to the method, through fusion of the preset multi-target mathematical model and the multi-target collaborative optimization algorithm, the optimization efficiency and precision of the thickening CO2 flooding development scheme are remarkably improved.

The application discloses an image generation method and device and an electronic device, relates to the technical field of image processing, and comprises the following steps: acquiring a reference image and a detailed text description corresponding to the reference image, wherein the detailed text description is used for describing a point of interest of the reference image; inverting the reference image to obtain a noise image containing feature information of the reference image; and matching the detailed text description, performing noise removal on the noise image to generate a similar image similar to the reference image. The application can enrich image data of a single scene.

The invention provides a time domain staggered grid finite difference method parallel computing method and a storage medium, and belongs to the technical field of electromagnetic, sound wave and elastic wave forward modeling. The method comprises the following steps: dividing three-dimensional data into a plurality of data blocks, and carrying out parallel calculation on the data blocks at each time point to obtain the boundary speed of the data blocks and the speed and pressure data in the data blocks. By using the method of the invention, the calculation efficiency of three-dimensional seismic forward modeling simulation can be improved. If the method is applied to three-dimensional wave field forward modeling in the engineering field of oil exploration and the like, the method can save the calculation time and machine time cost, reduce the calculation energy consumption, reduce the service cost and improve the calculation efficiency of the staggered grid finite difference method.

Embodiments of the present disclosure provide a decryption method, a variable storage method, and related devices, equipment, media and products. The decryption method monitors the current signal of the chip through the current probe, monitors the electromagnetic signal of the SRAM through the electromagnetic probe, determines the key bit value corresponding to the coordinate value stored in the SRAM based on the signal change mode of the current signal and the electromagnetic signal, and then obtains the decryption result. Through the current-electromagnetic dual-channel acquisition and analysis scheme, the ability to obtain effective information in the decryption process is improved, the redundant information processing process is reduced, and the password cracking efficiency is improved. The variable storage method stores the coordinate values of at least two coordinate dimensions of at least one password intermediate variable in at least two SRAMs, or stores the coordinate values of at least one coordinate dimension of at least two password intermediate variables in the same SRAM, which can avoid local electromagnetic radiation analysis and the storage process does not affect the execution efficiency of the encryption algorithm.

The application provides a real-time target detection method in an ultrahigh-resolution image scene, comprising: processing an original image to generate a high-resolution image and a low-resolution image; processing the low-resolution image to obtain a reserved area; cutting the high-resolution image according to the reserved area to generate a plurality of regional subgraphs; and detecting the regional subgraphs to obtain a detection result. The application can quickly detect the area requiring further fine-grained detection from an ultrahigh-resolution image through resolution processing, multi-scale density regression, area determination and area generation processing. In addition, due to the scale normalization, target detection and result merging processing, the final ultrahigh-resolution detection result can be generated. In the target detection stage, the plurality of regional subgraphs can be processed in parallel, which can greatly improve the inference time. Since part of the object-free area can be discarded in the density estimation stage, the required storage resources and calculation time can be saved.

Embodiments of the present disclosure relate to the technical field of target tracking, and specifically relate to a multi-target association method, system, computer device and storage medium. The main steps of the foregoing method include: obtaining a plurality of candidate bounding boxes corresponding to a plurality of to-be-associated targets in current frame data, taking each to-be-associated target and its corresponding plurality of candidate bounding boxes as a sample, determining the sample type of each sample, extracting the appearance features of the candidate bounding boxes and the to-be-associated targets in difficult samples, obtaining association probability data based on a preset classification model according to the basic bounding box features of simple samples, the basic bounding box features and the appearance features of difficult samples, and determining the target bounding boxes having an association relationship with each to-be-associated target from the plurality of candidate bounding boxes according to the association probability data and a preset matching algorithm. The foregoing method can improve the accuracy of target object recognition.