15 results about "Hilbert curve" patented technology

This invention provides a method, apparatus, device, and medium for UAV route planning based on Hilbert curves. The method includes: collecting real-time position, attitude, and environmental information of the UAV; constructing an initial UAV route using a Hilbert curve based on the UAV's mission requirements and the collected information; smoothing the initial UAV route and removing redundant paths using a Bézier curve to obtain an optimized UAV route; correcting the optimized UAV route based on real-time environmental changes to generate a safe route; and converting the safe route into executable control commands for the UAV to drive its operation, thereby solving the problems of insufficient space filling efficiency, poor adaptability to dynamic environments, and low path smoothness in dynamic path planning.

The application discloses a non-full-field data synchronization method based on a Hilbert curve and related equipment thereof, and belongs to the technical field of big data. The application obtains the primary key information of non-full-field data, performs a hash operation on the primary key information to obtain a hash value corresponding to the primary key information, maps the hash value to a two-dimensional space where a Hilbert curve of full-amount data is located, obtains coordinate data of the hash value on the Hilbert curve, inputs the coordinate data into a preset Hilbert space curve algorithm model to obtain position information of the non-full-field data, obtains a synchronization mode corresponding to the non-full-field data, and synchronizes the non-full-field data based on the synchronization mode and the position information. In addition, the application also relates to the technical field of blockchains, and the non-full-field data can be stored on nodes of a blockchain network. The application can realize fast query and positioning of non-full-field data, quickly complete synchronization of non-full-field data, and improve the efficiency of data synchronization.

This invention discloses a liquid-cooled plate flow channel structure based on Hilbert curves, belonging to the field of power battery thermal management technology. It mainly involves a coolant flow channel network composed of multiple flow channel units. The coolant flow channel network includes multiple integrated main channels, each consisting of multiple flow channel units connected in series. Each flow channel unit includes a unit inlet end, a Hilbert curve flow channel, and a unit outlet end. The liquid-cooled plate has inlets on both sides of its long side and outlets on both sides of its short side, forming intersecting transverse flow channels. This invention utilizes the self-similarity and high spatial coverage of the Hilbert curve to achieve near-full coverage flow of the coolant, expanding the heat dissipation area. Furthermore, it enhances heat transfer through continuous turns and flow channel contraction-expansion, significantly improving temperature uniformity and heat dissipation efficiency, and solving problems such as localized overheating in traditional straight channels or serpentine flow channels.

The invention relates to the technical field of location service privacy protection, in particular to a location privacy protection method based on regional confusion and differential privacy, which comprises the following steps: S1, dividing regions, processing a location set uploaded by a user, constructing a probability distribution matrix, and generating a user pseudo location; and S2, request forwarding: the relay server receives a user query request and generates a hidden area, forwards the query request to the LBS server based on the hidden area, and finally returns a query result to the user. According to the method, the positions are mapped and sorted through the Hilbert curve, so that the spatial proximity of the positions is accurately reflected; and the optimal clustering number k is adaptively determined in combination with a QK-means clustering algorithm, so that PLS division is more reasonable, and the accuracy and matching efficiency of region division are improved.

The invention discloses a sea wave disaster early warning information precision verification method, and relates to the technical field of intelligent management, and the method comprises the following steps: dividing a three-dimensional space-time grid, calculating sea wave energy characteristics, reconstructing the monitoring data of a problem node, generating an analysis link, and carrying out the first verification of alarm information based on the time characteristics of a sea wave disaster; and updating the alarm information according to the first verification result. According to the method, the global sea area is divided into the three-dimensional grids with the unified temporal-spatial resolution, spatial-temporal alignment of multi-source monitoring data is achieved through three-dimensional Hilbert curve coding, the precision and consistency of sea wave energy feature extraction are improved, a comparison mechanism of theoretical energy and actual energy is constructed based on an inter-node energy propagation model, and the real energy feature extraction accuracy is improved. The reliability and robustness of monitoring data are improved, the accuracy and authority of early warning information are improved by constructing an analysis link, and the node with the highest error risk is preferentially processed by adopting a strategy of firstly verifying problem nodes and then rechecking reliable nodes.

The invention relates to the technical field of geographic information processing, in particular to a real estate surveying and mapping resource sharing system and method, and the system comprises a heterogeneous primitive analysis module which constructs a spatial topological incidence matrix and generates a standardized semantic feature set, and a distributed index module which generates spatial position hash codes by using a Hilbert curve to perform fragmentation storage, the vision field verification module uses a ray crossover algorithm to calculate a space inclusion state and generate a dynamic access authorization token, and the increment synchronization module calculates a geometric element difference package to complete instant redrawing. According to the method, topological dislocation caused by source data format difference is eliminated by constructing a heterogeneous semantic mapping matrix, bandwidth occupation and loading delay are reduced based on a differential transmission mechanism of viewpoint coordinates, and self-adaptive adjustment of access granularity is realized by utilizing a dynamic geofencing algorithm; the problem of I / O blocking under high-concurrency requests is solved by adopting distributed hash fragment index logic, and accurate distribution and real-time synchronization of resources are ensured.

The invention discloses a wind power generation power estimation method based on data fusion processing, and relates to the technical field of wind power generation power prediction, and the method comprises the steps: collecting real-time multi-modal data, carrying out the preprocessing, generating a real-time feature set, extracting a power sequence, calculating the number of IMFs through a cyclic autocorrelation function and a similarity coefficient, and carrying out the prediction of the IMFs. The method comprises the following steps: performing EEMD decomposition in combination with noise amplitude to obtain an IMF sequence, dividing a wind power plant into equal-proportion grids, mapping geographic coordinates of a fan into a two-dimensional grid index, converting the two-dimensional grid index into one-dimensional codes through a Hilbert curve algorithm, constructing space-time grids in combination with time binary codes, mapping multi-dimensional feature vectors to generate an aggregation space-time feature cube, and performing power prediction; according to the method, the input quality and precision of the prediction model are improved through time alignment and feature extraction of the multi-modal data, and the prediction robustness and the system adaptability are improved by using EEMD decomposition and space-time grid modeling.

The invention discloses a large-scale spiking neural network efficient partitioning method based on a connection mode index, and the method comprises the following steps: aiming at the characteristics of brain-like computing hardware, carrying out the topological sorting, carrying out the locality-keeping index sorting of neurons through employing a Hilbert curve, and carrying out the resource-limited segmentation algorithm based on binary search, neurons with common pre-synaptic inputs are clustered into the same computing core. According to the method, a pulse sharing mechanism of hardware can be utilized to the maximum extent, the pulse broadcast flow of the network-on-chip is remarkably reduced, and core resource waste caused by axon memory limitation is reduced. Compared with the prior art, the compiling speed is increased by several orders of magnitude when the network with the gigons of neuron scale is processed, and the communication delay and the energy consumption during operation are greatly optimized at the same time.

The invention provides an anti-counterfeiting image texture feature extraction method and system, and the method comprises the steps: carrying out the YCbCr color space conversion of an anti-counterfeiting image, carrying out the two-dimensional dual-tree complex wavelet transformation of Y, Cb and Cr components, and obtaining a multi-scale multi-direction high-frequency sub-band coefficient matrix; energy of each high-frequency sub-band is calculated, global texture complexity parameters are determined based on the energy, a dynamic selection threshold value is generated, and the high-frequency sub-bands with the energy exceeding the threshold value are effective texture sub-bands; for the effective texture sub-band, calculating information entropy, determining the size of a sub-block, dividing the sub-block, and reserving the sub-block of which the standard deviation is greater than the mean value of the standard deviation of the sub-block in the sub-band; the effective texture sub-band reserved sub-block coefficients are scanned and spliced into a one-dimensional feature vector according to a Hilbert curve, sliding windows with odd lengths are used for traversing, a bit 1 is generated when window center coefficients are larger than a left neighborhood coefficient mean value and a right neighborhood coefficient mean value at the same time, otherwise, a bit 0 is generated, and an anti-fake image texture feature hash sequence is generated through splicing.

A file is received that includes locus information. The received file is preprocessed, including by selecting a size for a Hilbert curve. File contents are transformed using the Hilbert curve. The transformed file contents are down-sampled. A hashing operation is performed on the down-sampled result.

The invention provides a flow channel structure and a liquid-cooling cold plate, the flow channel structure comprises a fractal curve flow channel, the fractal curve flow channel is a Hilbert curve flow channel or a Petronol curve flow channel, and the fractal curve flow channel is used for increasing the heat dissipation area and strengthening the convection heat exchange efficiency in a limited plane space; wherein the Hilbert curve flow channel is constructed on the basis of a Hilbert curve, and the Peano curve flow channel is constructed on the basis of a Peano curve. According to the flow channel structure and the liquid-cooling cold plate provided by the embodiment of the invention, the heat dissipation performance is improved.

The invention provides an event flow action identification method and system based on a frame-point synergistic effect, and relates to the technical field of computer vision. The method comprises the following steps: extracting context event points from an original event stream by using a pulse type context learning device, and adaptively selecting a plurality of key event points from the context event points; sorting the key event points according to a Hilbert curve to reserve a spatial topological structure, and modeling long space-time dependence of the key event points to obtain event point features; converting the original event stream into a structured event frame through a time accumulation window; performing feature extraction on the event frame based on a Transform network to obtain an event frame feature; and fusing event point features and event frame features, introducing a CLIP text encoder to generate frame / point related semantic prompts, and finishing action recognition by comparing the consistency of loss constraint event features and text semantics.

This invention provides a cartographic method for optimizing real-time map rendering, belonging to the field of cartographic technology for real-time map rendering optimization. This invention pre-calculates the screen space projection area at the central processing unit (CPU) and repackages it into batches with varying loads, then asynchronously submits the batches to the graphics processor (GPU) via a drawing indirect instruction mechanism. It uses 3D Hilbert curves to map tile coordinates as linear indices, combining quadtree divide-and-conquer recursion with user motion prediction to drive tile prefetching. It reconstructs low-resolution tile textures using a bi-branch map texture super-resolution fusion model and adaptively adjusts the high-frequency gating weight inference scaling factor through a comprehensive quality adjustment value. It compresses the occlusion query overhead per frame through a bi-phase occlusion culling pipeline combined with temporal reprojection. This invention solves the technical problems of unbalanced geometric subdivision load, low tile scheduling cache hit rate, and difficulty in adaptively balancing texture super-resolution reconstruction quality and inference latency during real-time map rendering.

The invention discloses a new energy output scene generation method based on meteorological factor guidance, and relates to the technical field of scene generation, and the method comprises the following steps: S1, constructing a pre-training denoising diffusion probability model based on Hilbert curve projection distance and autocorrelation coefficient feature guidance, and achieving the rolling generation of continuous multi-day weather scenes; s2, freezing the pre-training de-noising diffusion probability model, adding a ControlNet control branch, inputting the weather sample with the condition label into the ControlNet control branch, and training to obtain a weather scene generation model; and S3, a weather-to-power conversion model is adopted, the generated weather scene is converted into new energy output, and a continuous multi-day new energy output scene meeting the condition control requirement is obtained. According to the method, probability distribution and correlation targets are considered, and a diversified scene which has high probability distribution consistency and time sequence correlation with a real scene in the next day can be generated.

This invention relates to the field of image encryption technology and addresses the problems of slow encryption speed and weak resistance to attacks in existing image encryption methods. The image encryption method described in this invention uses a ternary fractional discrete chaotic neural network system to generate a chaotic sequence related to the plaintext. A fractal sorting and scrambling process is then performed on the original image using a fractal model approach. To achieve better results, a double scrambling process is applied to both rows and columns. Finally, a synchronous scrambling and diffusion operation is performed according to the Hilbert curve traversal order, which can simultaneously change the position and size of pixel values. This method is the first to apply fractal thinking to the scrambling process in encryption, achieving good scrambling results. The synchronous scrambling and diffusion operation further improves the encryption efficiency to a certain extent.