32results about How to "Excellent calculation speed" patented technology

The invention relates to a CT (Computerized Tomography) image metal track prediction and artifact reduction method based on integral cosine. Aiming at metal area part cutting in a metal artifact reduction algorithm, compared with a common threshold algorithm which uses original sinogram data to reestablish images, then cuts an image domain into metal pixels and finally projects the cut metal pixels onto a sinogram domain to position a metal track, the CT image metal track prediction and artifact reduction method based on integral cosine firstly obtains various projection tracks according to a cosine projection relationship, projections on each track are added and values which are greater than a threshold are regarded as values corresponding to metal, so that the metal track is obtained. The CT image metal track prediction and artifact reduction method based on integral cosine has the advantages that the original images are not required to be reestablished, the time is greatly saved, the accurate positioning of metal areas in images is kept as much as possible and artifacts introduced in the reestablished images are ensured to be as few as possible. According to results, the CT image metal track prediction and artifact reduction method can be used in a metal artifact reduction algorithm of CT medical images and the metal artifact reduction effect of the repaired images is better.

The invention discloses a disturbing gravity approximation method for a large-range maneuvering trajectory space envelope along a near space. The method comprises the following steps of establishing mathematic models of the lateral width and longitudinal range of a trajectory envelope; establishing a pole-changing coordinate system; establishing an aircraft dynamic model in the pole-changing coordinate system; calculating a three-dimensional trajectory envelope of the pole-changing coordinate system; dividing the whole airspace of the pole-changing coordinate system; establishing a general coordinate system space envelope disturbing gravity reconstruction model; judging a grid where a current trajectory position is; establishing a local area coordinate system in the computational grid; and performing approximation calculation on a disturbing gravity net function in the grid. The trajectory space envelope calculation method disclosed by the invention can cover the large-range maneuvering trajectory along the near space in any condition; the disturbing gravity along the trajectory is calculated according to the method provided by the invention; and the method has the characteristics of small calculation scale, high calculation speed and high calculation precision, and can meet the requirements of trajectory planning, guidance calculation and the like on calculation amount and calculation speed.

The invention discloses a quick seam carving method based on strips and adjacency, and belongs to the field of images. A quick seam carving method is improved and constrained by combining the thought of the adjacency and the strips, so that seams can be uniformly distributed in each area of an image, and a satisfactory result is achieved. The method comprises the following steps of: dividing the image into a plurality of strips at equal intervals, calculating the average importance of the strips by using a significant diagram corresponding to the image, obtaining the target size of each strip according to the importance of the strip and the target size of the whole image by solving an optimization problem with a constraint condition, and acquiring a target size image by adopting the quick seam carving method combining the adjacency in each strip. The calculation speed of the method is further higher than that of other seam carving methods, and the quality of the obtained result image is better than that of the conventional quick seam carving method, so the method has certain application value and significance.

The present invention provides a laser speckle blood flow imaging enhancement method. The laser speckle blood flow imaging enhancement method is configured to perform noise reduction processing and the repairing processing of the laser speckle blood flow imaging to enhance the sharpness of the laser speckle blood flow imaging. Because the laser speckle blood flow imaging enhancement method employs the BEEMD processing algorithm for the laser speckle blood flow imaging, the microvessel image is more clearly displayed and more details are reflected so as to reduce the influence of the vibration noise on the blood flow dispersed map; because the employed BEEMD algorithm can effectively avoid the information loss at the aspect of the image rank correlation of the original EEMD algorithm to retain the completer image information as much as possible prior to the noise reduction operation; and finally, because the employed BEEMD algorithm is far better than each two-dimensional empirical mode decomposition (BEMD) on the computation speed, so that the laser speckle blood flow imaging enhancement method has a positive effect on the real-time monitoring in vivo.

The invention belongs to the technical field of manufacturing of integrated circuit semiconductor and provides a heuristic method for the dummy fill of a chemical mechanical polishing process. In the method, the dummy fill problem of the minimum dummy metal number is expressed as a standard linear programming problem and then a heuristic algorithm for dynamically increasing the dummy metal density in a grid is provided for solving the minimum dummy fill problem. In the method, the density value of dummy metal filled in the to-be-filled grid is dynamically determined during each optimization process according to a grid density cost function and approximation precision; meanwhile, the increment of the dummy metal density in the grid during each iteration is adjusted through an approximate constant epsilon; thus the compromise of the final result precision and the calculation speed can be realized. The method has high feasibility, extremely high-efficiency processing speed, superior calculation speed and result precision to those of the popular Monte-Carlo method and can be used for solving the large-scale territory dummy fill problem.

A circuitry punching creation method is characterized in that gaining corresponding punching parameters in a punching database according to the preset hole parameters in a circuit draft; meanwhile, provide the punching parameters on the circuit draft according to the position of the preset hole; moreover, provide a punching list on the circuit draft according to the punching parameters, so that relevant personnel can perform verification. The invention can improve the speed and correctness of the punching parameters that are created.

The invention discloses a method for realizing container truck positioning based on monocular vision measurement. The method comprises the following steps: 1, obtaining the actual height h of a container truck and the height H of a monocular camera relative to the ground through measurement, and customizing a calibration plate composed of square black and white grids according to the size of an actual site; 2, establishing a default coordinate system of the ground to be detected by using the pictures selected in the step 1; 3, when the container truck is not loaded with the container, sequentially carrying out graying, morphological hybrid filtering based on multiple structural elements and edge detection on the shot images of the end part of the truck; and when the container truck loads acontainer, using Hog + SVM to identify the position of a container truck end lock hole in the image; 4, calculating the parking position error b of the container truck according to the formula (2); and 5, calculating the actual distance between the end part of the container truck and the parking line and the relative angle between the straight line at the end part of the container truck and the parking line to realize accurate container truck positioning. The beneficial effects of the method are that the method is low in cost, and can achieve the quick and accurate positioning of the container truck.

The invention discloses an IGR_OMP based high-dimension sparse vector reconstruction method. An incremental IGR_OMP algorithm is provided according the characteristic that the least square solution needs to be calculated in each step of an OMP algorithm and on the basis of a Greville recursion process, a series of useful recursion properties is obtained, and the calculation speed is improved effectively. On the basis of analysis on the IGR_OMP algorithm, relation between the Greville recursion algorithm and QR decomposition is used, the incremental IQR_OMP algorithm on the basis of QR decomposition is established, the workload of calculation is reduced effectively, The algorithm can be used to solve a large problem more effectively; and simply, high-dimension sparse vector reconstruction provides a sparsest coefficient representation of the high-dimension vector in a complete vector system.

The invention discloses a self-adaptive electric vehicle SOC estimation method based on big data, and the method comprises the steps: the time, longitude, latitude, SOC value, vehicle speed, odometertotal mileage value, battery pack output total current and battery pack output total voltage of a vehicle are collected from the vehicle in advance, and serve as a training data set; acceleration, distance and energy consumption values are calculated according to time, speed, longitude and latitude, current and voltage values in a training data set, characteristic speed, acceleration, distance anddependent variable energy consumption values are used for constructing an extreme random decision tree model, and an SOC prediction model based on mileage and energy consumption is obtained accordingto a total mileage value, an energy consumption value and an SOC value of an odometer. Therefore, the final SOC prediction model is obtained by the SOC prediction model based on mileage and energy consumption according to the genetic algorithm, the model can update the data in the training data set every other T time, and the self-adaptive prediction effect is achieved.

The invention discloses a high-dimensional sparse vector reconstruction method based on IQR_OMP. According to the characteristic of the OMP algorithm in which calculate the least square solution in each step, an incremental IGR_OMP algorithm is proposed based on the Greville recursive process, and a series of useful recursive properties are obtained, so that the calculation speed is effectively improved. The incremental IQR _ OMP algorithm on the basis of QR decomposition is established, based on analyzing the IGR _ OMP algorithm, by utilizing the relationship between the Greville recursive algorithm and the QR decomposition, so that the calculation workload is effectively reduced, and the effectiveness of the algorithm to solve large problems is improved. In addition, the high-dimensionalsparse vector reconstruction is simply to give the most sparse coefficient representation of a high-dimensional vector on an over-complete vector system.

The invention relates to a node current injection based single three-phase hybrid tide calculation method. The technical feature of the method is that the method includes steps of 1, constructing a single three-phase hybrid model used for power distribution network tide calculation; 2, performing power distribution network calculation by adopting a node current injection method based on the singlethree-phase hybrid model used for power distribution network tide calculation constructed in step 1. According to the invention, influence due to zero sequence and negative sequence components are taken into account, and calculation precision is ensured at the same time of ensuring the calculation speed.

The invention discloses a high-dimensional sparse vector reconstruction method based on IQR_OMP. According to the characteristics of the least squares solution in each step of the OMP algorithm, an incremental IGR_OMP algorithm is proposed based on the Greville recursive process, and a series of useful recursive properties are obtained, which effectively improves the calculation speed; on the basis of the analysis of the IGR_OMP algorithm , using the relationship between Greville's recursive algorithm and QR decomposition, an incremental IQR_OMP algorithm based on QR decomposition is established, which effectively reduces the computational workload and improves the effectiveness of the algorithm in solving large-scale problems; high-dimensional sparse vector weight Simply speaking, the structure is to give the sparsest coefficient representation of high-dimensional vectors on the over-complete vector system.

The invention discloses a computing method for improving small signal stability and providing aid decision making, which is suitable for computation of output power adjustment measures of units for improving a plurality of dampers in weak damping modes under the determined mode of operation. The method is characterized by considering the weak damping modes and the modes close to safe damping threshold while determining the coordination control properties of the units, selecting the units with larger participation factors in the weak damping modes to participate in output power adjustment, dividing the units participating in output power adjustment into two groups according to the unit mode information in each mode, determining the output power adjustment directions of the two groups of units by a method of perturbation of power, determining the output power adjustment directions during coordination control by combining the participation factors and the output power adjustment directions of the units in different modes, computing the output power adjustment measures of the units for improving the dampers in the single mode by a sensitivity method, checking the combined control measures by computing the eigenvalues in the given range to determine the effectiveness of the control measures and giving the output power adjustment measures of the units for coordination control of a plurality of weak damping modes.

The invention discloses a disturbing gravity approximation method for a large-range maneuvering trajectory space envelope along a near space. The method comprises the following steps of establishing mathematic models of the lateral width and longitudinal range of a trajectory envelope; establishing a pole-changing coordinate system; establishing an aircraft dynamic model in the pole-changing coordinate system; calculating a three-dimensional trajectory envelope of the pole-changing coordinate system; dividing the whole airspace of the pole-changing coordinate system; establishing a general coordinate system space envelope disturbing gravity reconstruction model; judging a grid where a current trajectory position is; establishing a local area coordinate system in the computational grid; and performing approximation calculation on a disturbing gravity net function in the grid. The trajectory space envelope calculation method disclosed by the invention can cover the large-range maneuvering trajectory along the near space in any condition; the disturbing gravity along the trajectory is calculated according to the method provided by the invention; and the method has the characteristics of small calculation scale, high calculation speed and high calculation precision, and can meet the requirements of trajectory planning, guidance calculation and the like on calculation amount and calculation speed.

The invention relates to a visible light infrared cascade video tracking method. The method uses the cascading method of the visible light data channel and the infrared data channel to obtain the tracking results of the two data channels respectively, and chooses the tracking results. It takes into account the advantages of the two channels of target detection, makes up for their respective defects, and improves the tracking ability.

The invention discloses a remote sensing scene image classification method based on multi-level dense feature fusion, and relates to a remote sensing scene image classification method. The objective of the invention is to solve the problem of low classification accuracy of hyperspectral images caused by high-dimensional characteristics of the hyperspectral images and small training samples in existing hyperspectral image extraction processes. The method comprises the following steps of: step 1, acquiring a hyperspectral image data set X and a corresponding label vector data set Y; step 2, establishing a lightweight convolutional neural network BMDF-LCNN based on dual-branch multi-level dense feature fusion; step 3, acquiring an optimal network BMDF-LCNN; and step 4, inputting a to-be-measured hyperspectral image into the optimal network BMDF-LCNN to perform classification result prediction. The method is applied to the field of image classification.

The present invention proposes a pose measurement method based on semantic segmentation and Kalman filtering under monocular vision, which includes calibrating the measurement site; taking pictures of the measurement objects and making data sets for semantic segmentation training; the trained model Realize image positioning, and combine the mathematical model in this paper to realize position and attitude measurement. The invention is based on monocular vision measurement and semantic segmentation, and can adapt to various objects with known width and unknown height, and related parameters are optimized by Kalman filter, so that positioning can be realized quickly and accurately.

The invention discloses an adaptive electric vehicle SOC estimation method based on big data. The time, longitude, latitude, SOC value, vehicle speed, total mileage value of the odometer, and total output current of the battery pack are collected in advance from the vehicle. and the total output voltage of the battery pack as the training data set, calculate the acceleration, distance, and energy consumption values ​​according to the time, speed, latitude and longitude, current, and voltage values ​​in the training data set, and then calculate the characteristic speed, acceleration, distance, and dependent variable energy consumption values It is used to construct an extremely random decision tree model, and then the SOC prediction model based on mileage and energy consumption is obtained from the total mileage value, energy consumption value and SOC value of the odometer, so that the SOC prediction model based on mileage and energy consumption is obtained according to the genetic algorithm. The SOC prediction model, every T time, the model will update the data in the training data set, so as to achieve the effect of adaptive prediction.

The invention discloses a binocular three-dimensional ranging method for a bionic underwater robotic fish. The matching algorithm of SGBM can not only obtain more effective depth points, but also be superior to the algorithm of SIFT feature extraction and matching in terms of calculation speed; at the same time, in the water In the case of severe light attenuation in the lower scene, the image binocular distance measurement with higher precision in the short distance is used, combined with the long-distance sonar detection method; it not only makes up for the lack of interference of the sonar short-distance flow field, but also reduces the lack of light received by the long-distance binoculars to achieve high-precision underwater obstacle avoidance detection.

The invention provides a method for quickly predicting a directional diagram of a microwave antenna under the occlusion of a near-field complex barrier. The method specifically comprises the following steps: 1) approximating near-field properties of the microwave antenna based on expansion of a spherical surface wave source: by taking an origin of coordinates as a center of circle, making a smallest sphere surrounding a to-be-predicted antenna, wherein an antenna field represents weighted sum of vector wave functions in a space outside the sphere, and an electric field intensity vector and a magnetic field intensity vector are used for expression, so that a radiation near field of a reflector antenna is approximated as the expansion of the spherical surface wave source; 2) constructing a simulation scene by the expanded spherical surface wave source and a complex barrier model, wherein the complex barrier model has coexistence complexity of a dielectric material and a metal material; and 3) performing simulation calculation on the simulation scene constructed in the step 2) with a geometric optical method to obtain a directional diagram curve. According to the method, the problem of near-field occlusion can be solved, the material range is relatively wide and the electric dimension is relatively high in problem solving, the calculation speed is remarkably higher than that in a conventional method, and a prediction result is relatively matched with a test result.

The invention discloses an agricultural machinery operation area calculation method and system based on machine learning. The system comprises a terminal for realizing an acre calculation algorithm and a storage medium. The invention aims to solve the problem of low working area calculation precision of a single mu calculation algorithm under various driving tracks and various complex working scenes. The method comprises the following specific steps: acquiring operation data of an agricultural implement, and removing a track drift point and a stay point by using a lof algorithm; performing clustering segmentation on the data in time and space by using a Hopkins statistic and a dbsca algorithm so as to obtain an operation plot; using a CNN algorithm to identify a track type; calculating the tillage missing rate according to the image pixel points; and selecting a proper interpolation method and an area calculation method through a decision tree algorithm, and calculating the operation area. Compared with an existing algorithm, the method is suitable for various operation scenes and various operation track types, the influence of missing tillage on the area measurement result is avoided, and the accuracy of operation area calculation is effectively improved.

The invention discloses a signature algorithm for preventing large-batch data from being tampered in the Internet of Vehicles. The algorithm adopts a combination of a chain storage structure, a hash digest algorithm and the CBC-MAC algorithm to perform tamper-proof protection on large-batch data, such as vehicle speed, GPS and the like, which are stored locally in the Internet of Vehicles and generated periodically. According to the algorithm, batch data is stored in different files according to data generation time, and the files are connected through a text data signature algorithm to realize a chain storage structure; and the data frames are connected in the same file through a non-text-head signature algorithm. According to the algorithm, AES encryption operation is added to avoid therisk of packet replacement attacks; moreover, the algorithm only needs to perform AES and SHA256 once, and the calculation speed is superior to that of the CBC-MAC. Through the algorithm, no matter whether an attacker deletes the previous data or modifies the content of the previous data, the data can be detected through signature check of the group of data. By means of the algorithm, tamper-proofsignature and authentication of the original data frame can be achieved, and higher safety and higher calculation efficiency are achieved.

The present invention relates to a single-phase hybrid power flow calculation method based on node current injection. The single-three-phase hybrid model constructed in 1 for the power flow calculation of the distribution network adopts the node current injection method to calculate the power flow of the distribution network. The present invention simultaneously considers the effects of zero-sequence and negative-sequence components on the single-phase model, and ensures the accuracy of the calculation while taking into account the calculation speed.

The application discloses a blood flow reserve fraction calculation method, device, electronic equipment and readable storage medium. The method provided by this application determines the pressure drop prediction value through the arterial characteristic parameters after dimension reduction, so compared with the calculation method of three-dimensional fluid dynamics, the calculation speed is faster, and the pressure drop correction value prediction processing is performed on the pressure drop prediction value to obtain The correction value of the pressure drop corrects the predicted value of the pressure drop, which overcomes the inaccurate shortcomings of the predicted value of the pressure drop. Therefore, the whole process of calculating the blood flow reserve fraction not only ensures that the calculation speed is better than the traditional method, but also ensures the blood flow obtained in the final calculation. Reserve scores are highly accurate.

The invention relates to a CT (Computerized Tomography) image metal track prediction and artifact reduction method based on integral cosine. Aiming at metal area part cutting in a metal artifact reduction algorithm, compared with a common threshold algorithm which uses original sinogram data to reestablish images, then cuts an image domain into metal pixels and finally projects the cut metal pixels onto a sinogram domain to position a metal track, the CT image metal track prediction and artifact reduction method based on integral cosine firstly obtains various projection tracks according to a cosine projection relationship, projections on each track are added and values which are greater than a threshold are regarded as values corresponding to metal, so that the metal track is obtained. The CT image metal track prediction and artifact reduction method based on integral cosine has the advantages that the original images are not required to be reestablished, the time is greatly saved, the accurate positioning of metal areas in images is kept as much as possible and artifacts introduced in the reestablished images are ensured to be as few as possible. According to results, the CT image metal track prediction and artifact reduction method can be used in a metal artifact reduction algorithm of CT medical images and the metal artifact reduction effect of the repaired images is better.

The invention discloses a tamper-proof signature algorithm for a large amount of data in the Internet of Vehicles. The algorithm uses a combination of a chain storage structure, a hash digest algorithm and a CBC-MAC algorithm to store locally stored data in the Internet of Vehicles, such as vehicle speed and GPS. Anti-tamper protection for large batches of data generated in equal cycles. The algorithm stores the batch data in files according to the data generation time, and connects the files through the header data signature algorithm to realize the chain storage structure; connects the data frames in the same file through the non-header signature algorithm. This algorithm adds AES encryption operation to avoid the risk of packet replacement attack; and this algorithm only needs to perform AES and SHA256 once, and the calculation speed is better than CBC-MAC. Through the above algorithm, no matter whether the attacker deletes the last piece of data or modifies the content of the last piece of data, he can detect it through the signature check of this group of data. Through this algorithm, the tamper-proof signature and authentication of the original data frame can be realized, which has stronger security and higher computing efficiency.

The invention discloses an analysis method of an analysis engine with node thread level non-redundancy calculation, and belongs to the technical field of information network security analysis. The working principle of the analysis engine is as follows: a strategy analysis part analyzes and loads strategies with different external view angles and different external filtering characteristic conditions; the loaded strategy is distributed to each concurrent statistical analysis module through a strategy distribution module; in individual node, the engine view angle classification processing logicalgorithm performs independent logic processing according to different view angle fields in the custom strategy; feature filtering conditions in the strategy are logically processed; and the analysisengine performs duplication elimination processing on all groups and individual statistical algorithms, filtering conditions and research and judgment conditions of the strategy allocated to the nodeto ensure that the filtering conditions, feature statistics and the research and judgment conditions in the single node are only processed once, and calculated feature values are stored in a calculated feature value set.