28 results about "Code space" patented technology

The invention relates to the technical field of entity relationships, and discloses a multi-feature fused entity relationship extraction optimization model construction method and system, and the method comprises the steps: obtaining an input text sequence and a relationship label set, and carrying out the coding processing, and obtaining a text embedding vector and a relationship embedding vector; calculating the similarity between the text embedding vector and the relation embedding vector, screening in combination with a similarity threshold to obtain a candidate relation subset, and fusing the relation embedding vector and the text embedding vector in the candidate relation subset to generate a relation enhancement vector; processing the relation enhancement vector through a mixed attention mechanism to obtain a semantic enhancement vector; constructing a three-dimensional marking matrix based on the semantic enhancement vector, and marking the three-dimensional marking matrix by adopting a diagonal marking strategy; and carrying out decoding processing on the three-dimensional mark matrix, and generating a structured entity relationship triple by adopting a constraint decoding strategy. The interactive fusion of the text and the relation label can be accurately processed in a unified coding space.

The invention belongs to the technical field of optical transport networks (OTN), and particularly relates to a resource identifier storage and reading method for network management system data acquisition of OTN and WDM communication equipment, which comprises the following steps of: when the network management system data acquisition and reading are performed on the OTN and WDM communication equipment, performing bidirectional transcoding conversion between a resource identifier in a five-section layered form and an rmUID (Radio Mode Unified Identifier) identifier; a database static mapping table is prevented from being introduced, disk IO is reduced, the processing process is carried out in a memory, and the conversion efficiency is effectively improved; meanwhile, the 36-system is fully used for encoding each encoding segment in the rmUID, and under the encoding limiting condition that the longest bit of the rmUID limits 16 bits, the data encoding space is increased by about 10000 times compared with a 35-system and separator scheme, so that the utilization rate of the encoding space is expanded and increased to the maximum extent; the problems that in the prior art, conversion efficiency is poor, and the utilization rate of coding space is poor are effectively solved, and the method has good technical application prospects.

The invention discloses a discrete dung beetle optimized adaptive scanning VMama image denoising method, and relates to the field of image processing. In order to solve the problems of computation redundancy and denoising detail loss caused by a fixed scanning path of an existing VMama network, a hybrid coding space containing the number of network layers, state dimensions and binary scanning masks is constructed. According to the method, an S-type transfer function is introduced to improve a discrete dung beetle algorithm, an optimal architecture is adaptively searched by using behaviors such as rolling and dancing of a dung beetle population, a scanning path of an SS2D module is dynamically pruned according to a binary mask, performance is evaluated by fusing a fitness function of PSNR and FLOPs, and finally, a de-noised image is output based on the optimal architecture. According to the method, the balance between the denoising quality and the reasoning speed is effectively realized, and the model calculation amount is reduced.

The application relates to the technical field of archive management, in particular to an archive intelligent question-answering and automatic recording method and system based on a large language model. The method encodes archive business rules and original data into rule vectors and data vectors, and establishes a bijective mapping relationship to generate a reciprocal coding space. By encoding the query request into a query tensor, the tensor contraction operation is used to constrain the reasoning path, and the reconstruction is triggered when the rule is violated to generate the reasoning result. Then, the semantic gradient is calculated to identify and correct the recording field, and the correction is propagated in the association graph, and the rule is used to make a decision when there is a conflict. Finally, the field difference set is calculated, marked, merged and written to generate a recording version chain. The application realizes the intelligent linkage of question-answering and recording, and improves the automation degree and data consistency of archive processing.

The invention provides a malicious code detection method and system based on semantic analysis, and the method comprises the steps: determining a space where a suspicious code is located based on a monitoring behavior record of security software in a terminal, extracting a target code in the space, and reducing a subsequent malicious code detection interval range; based on the semantic feature extraction model and the text semantic classification model, generating a word sequence containing semantic information corresponding to the target code, and correcting the word sequence; analyzing the corrected word sequence based on a deep text classification model to obtain global text semantics of the target code so as to calibrate malicious code snippets in the target code, and performing code change operation on the space based on distribution characteristics of the malicious code snippets to obtain the target code. And meanwhile, global recognition is performed on the codes by utilizing a semantic feature extraction model and a text semantic classification model, efficient and accurate analysis of code semantics is considered, semantic information of the codes is comprehensively extracted, malicious code components are recognized and positioned in massive codes, and the working accuracy and reliability of security software are improved.

The invention discloses a knowledge decision supervision method for watershed flood prevention, and relates to the technical field of watershed flood prevention, and the method comprises the steps: obtaining watershed flood prevention data and real-time meteorological data of a target region; performing knowledge extraction on the flood prevention data of the drainage basin to obtain spatial element information and non-spatial element information; coding the space element information according to a preset identity coding rule to obtain coded space element information; performing spatial topological relation construction on the encoded spatial element information by utilizing a geographic information system, and constructing a knowledge relation of a root primitive according to the constructed spatial topological relation to obtain a spatial element knowledge relation; fusing the non-spatial element information and the spatial element knowledge relationship, and converting a fusion result into a knowledge graph to obtain a fused knowledge graph; and inputting the meteorological data and the fused knowledge graph into a preset knowledge aided decision-making model, and outputting a decision-making result. According to the invention, the decision-making precision, the response speed and the early warning response efficiency are improved.

The invention relates to a pixel antenna multi-objective optimization method based on a BPSO-MLP algorithm, and is applied to the technical field of wireless communication antennas. Global search is carried out in a high-dimensional discrete coding space of a pixel antenna through an improved binary particle swarm optimization algorithm, a dynamic temperature parameter is introduced to adjust the shape of a Sigmoid mapping function, and a probability-driven variation mechanism is adopted to effectively balance exploration and development capabilities; a performance prediction model is established through the designed multilayer perceptron neural network, and rapid and accurate prediction of key performance indexes such as bandwidth, gain and radiation pattern of a candidate antenna structure is realized; and submitting the predicted and screened high-potential solution to full-wave electromagnetic simulation through an intelligent optimization mechanism, feeding back a simulation result to an optimization algorithm, and dynamically updating a prediction model. According to the method, the problems of high-dimensional discrete search, high simulation cost and multi-performance index coordination in pixel antenna multi-target optimization are effectively solved, and an efficient solution is provided for reconfigurable antenna design of a new-generation communication system.

The invention discloses a method, system and equipment for optimizing SSD log records and a medium, and relates to the technical field of solid state disk log management.The method comprises the steps that description characters and formatted character strings in an original log printing function are removed, key parameters are reserved, and meanwhile retrieval fields are added; printing the simplified log containing the retrieval fields and the key parameters; establishing a mapping relationship among the description characters, the formatted character strings and the retrieval fields, and generating a log retrieval table; and based on the log retrieval table, analyzing the simplified log through a tool or a script, and restoring the real log to print. Only the key parameters are printed during printing, and other description characters (including formatted character strings) are omitted, so that the effect of not compiling the description characters in the compiling stage is achieved, the code space of an executable file after compiling is reduced, the consumption of a log function on the code space is reduced, the utilization rate of the log space is improved, and the user experience is improved. And meanwhile, the logs are compressed and restored without damage.

The invention discloses a stratum fracture pressure prediction method of a multi-input depth operator network with double embedding of physical information. Comprising the following steps: acquiring logging data and engineering parameter data of a to-be-predicted well section, then executing target perception mutual information grouping, calculating an input feature mutual information matrix, constructing a mutual information fingerprint vector, weighting and clustering according to the correlation between the mutual information fingerprint vector and fracture pressure, obtaining feature subsets, and respectively inputting the feature subsets into a multi-branch sub-network; a depth operator network is constructed, a backbone network takes well depth as input coding space dependence, a multi-branch sub-network extracts grouping features, an attention module performs adaptive weighted fusion on each branch representation, and adaptive physical constraint is performed through a physical layer; according to the method, the prediction curve of the fracture pressure changing along with the well depth can be output through the physical information double-embedded multi-input depth operator network, the prediction accuracy, the physical consistency and the cross-well-section generalization ability are improved, and the method is suitable for well wall stability analysis and fracturing parameter optimization.

The application discloses a kind of distributed mixed flow water workshop scheduling optimization methods based on greedy workpiece insertion, comprising: obtaining current scheduling solution, identifying key factory and key workpiece;Select the non-key factory with the minimum completion time as the target factory;From the first process of key workpiece, sequentially insert each process into the best insertion position of the corresponding processing stage of target factory to make the longest path length through the process minimum;After insertion, update the head length of affected process, obtain new scheduling solution.The present application is based on the longest path length minimization criterion of solution space, greedily inserts each process of key workpiece into the best position one by one and updates the head length in real time, realizes the accurate disturbance of critical path and the rapid evaluation of neighborhood solution, significantly improves the search accuracy and calculation efficiency of neighborhood movement between factories, solves the technical problems of poor controllability, low precision and long time caused by extensive movement and global re-encoding in the coding space.

The invention relates to the technical field of industrial robot and mechanical arm motion control, in particular to a mechanical arm multi-target motion path planning method and system. The method comprises the following steps: firstly, constructing a scene graph state structure containing geometric, topological and real-time states by integrating multi-source data; constructing a multi-objective cost function fusing time, energy consumption, risk and collaborative constraint based on the structure, and coding by using a graph neural network; carrying out state construction and strategy training on the coding space by applying reinforcement learning, and generating a candidate path set of cooperation of multiple mechanical arms; and finally, performing collision detection, optimization screening and smoothing processing on the candidate paths through digital twinborn simulation, configuring a local re-planning mechanism, and finally generating a control instruction. According to the method, the path planning collaboration, safety and comprehensive efficiency of the multi-mechanical-arm system in a complex scene are effectively improved.

The invention discloses a video compression method based on motion estimation and affine transformation substitution. The method comprises the following steps of: 1, performing feature analysis and initial coding on an image to realize initial compression of an original video frame, and establishing spatial geometric association between adjacent frames; 2, mapping high-resolution homography to a low-resolution coding space by using a down-sampling matrix based on spatial geometric correlation to obtain a down-sampling homography matrix; step 3, according to the mask region of the moment coding data obtained by calculation in the step 2, separating to obtain a code of a cutting background, namely a code of an increment background, and realizing differential compression; and 4, according to the codes of the incremental background obtained in the step 3, the decoding end combines the stored codes at the T-1 moment to splice and fuse reconstructed coding data at the T moment, and then video frames are decoded. According to the invention, the adaptive compression coding capability for different regions in the video compression process is effectively improved.

This invention discloses a spectral coding optimization method and imaging system based on the minimum distance in the coding space. The core of this invention lies in proposing a design criterion that maximizes the minimum Euclidean distance between the corresponding vectors of any two different spectral samples in the coding response space. This directly improves the separability of different spectra at the detector end from a geometric perspective, thereby enhancing the system's robustness to noise and disturbances. To efficiently solve this non-convex optimization problem, this invention proposes a global-local joint optimization strategy. The spectral encoder structural parameters optimized based on this method can be applied to computational spectral imaging systems. This system, through encoder modulation, signal detection, and sparse reconstruction, ultimately outputs a spatial-spectral three-dimensional data cube of the target object. This invention effectively overcomes the shortcomings of traditional design criteria that do not directly consider geometric separability and the tendency of single optimization methods to get trapped in local optima, significantly improving the system's reconstruction accuracy and stability.

The invention belongs to the technical field of mixing test design, and particularly relates to a mixing test method and system with a limited test space, and the method comprises the steps: obtaining a test space based on response variables, test factors, and equality constraints and lower bound constraints among the test factors in a mixing test; obtaining a transformation relation between coordinates of any point in the test space and a natural space and a coding space; based on the transformation relation, obtaining distribution of test points and a test scheme by adopting a simplex gravity center design method; performing a mixing test based on the distribution of the test points and the test scheme, collecting test data, and constructing a regression model; and obtaining the optimal combination proportion of each mixing component based on the regression model. According to the method, the accurate mixing test regression model can still be efficiently established under the condition of extremely limited test times, and optimization of key performance indexes and cooperative control of component cost are achieved.

The application discloses a method for recognizing distraction driving behavior based on an improved DCH neural network, which comprises the following steps: constructing a hyper-dimensional calculation model; firstly, constructing an improved DCH neural network; replacing an ADAM optimizer in the DCH model with an improved artificial traveling mouse optimizer; then, using the improved DCH neural network to perform hyper-dimensional vector coding; in a hash code space, the Hamming distance of hash codes of semantically similar images is close, and the Hamming distance of semantically dissimilar images is far; finally, classifying image information of the same category to form a category hyper-dimensional vector; constructing an AdaptHD retraining model; using the model to calculate a classification accuracy rate, and calculating the similarity between all training samples and the category hyper-dimensional vector again; training the model, testing a data set by using the trained model; and outputting a test result; and the application improves the efficiency of the algorithm within an acceptable range of detection precision, reduces the time for training the model, and no longer depends on high-performance edge computing devices.

The invention discloses a pedestrian detection-oriented physical adversarial patch generation and migration method, and belongs to the field of computer vision and artificial intelligence security. The invention provides a shape-texture two-stage layered optimization and Min-Max robust migration framework aiming at the problems of abrupt patch shape, difficulty in reproduction of pixel-level noise and poor environmental adaptability in the existing physical countermeasure attack. The method comprises the following steps: firstly, constructing a smooth patch contour by using a centripetal Catmull-Rom spline curve, and optimizing an anchor point coordinate through a differential evolution algorithm so as to lock an effective receptive field which is most sensitive to a model; secondly, constructing a discrete texture coding space based on a physical adhesive tape, and searching an optimal stripe texture formed by the color, width and direction of a standard adhesive tape in a fixed shape; meanwhile, a Min-Max robust optimization strategy is introduced, and the anti-interference capability of the patch is improved by minimizing the maximum confidence coefficient under the worst illumination transformation; and finally, a physical mapping strategy based on vector reconstruction is adopted, a precise transformation model from pixels to millimeters is established, and an SVG vector manufacturing file irrelevant to resolution is output. According to the method, precise closed loop of the anti-patch from digital algorithm optimization to physical object manufacturing is realized, and the method has the advantages of high physical realizability, natural and hidden shape, high environmental robustness and the like.

This application provides a method, apparatus, and device for managing the storage space of a smart card, applicable to the field of smart card technology. The storage space of the smart card includes a code area and a data area. The method includes extracting code to be released from the COS code based on a preset code extraction strategy. The code to be released is code that will only be executed a preset number of times before the smart card is personalized. A compilation tool is used to compile the code to be released into the code to be released area, and the storage space occupied by the code to be released is calculated. The code to be released area is located at the end of the data area. The space to be released is released based on a space release command sent by a host computer. The released code to be released area is allocated to the data area of ​​the storage space. This method can solve the problem of limited code space savings in current methods for optimizing the storage space of smart cards.

The invention provides a training method, device and equipment of a large model for PLC code generation and a medium. Obtaining a programmable logic controller code generated by the current large language model, physical state data corresponding to industrial equipment and equipment information; determining a code space vector and a physical space vector based on the programmable logic controller code, the physical state data and the physical constraint encoder, and determining a condition vector based on the device information; determining a physical constraint loss value according to the code space vector and the physical space vector; determining a condition loss value according to the code and the condition vector; determining a total loss value based on the physical constraint loss value and the condition loss value; if the total loss value is greater than a preset loss value, updating parameters of the large language model based on the loss value; returning to execute the step of obtaining the programmable logic controller code generated by the current large language model; and the total loss value is not greater than the preset loss value so as to complete the training of the large language model.

A system and method for indicating, via a heralding signal, that an amplitude damping decay event has occurred within a quantum low-density parity-check code is disclosed. Logical information may be encoded into a superconducting qubit using one or more transmons, wherein a first level and a second level are encoded into a code space of the qubit, and at least one intermediate level outside of the code space characterizes an amplitude damping decay channel which is then used to herald an amplitude damping decay event. Dynamical decoupling pulse sequences may be used to drive such qubit structures and bias noise towards the amplitude damping decay channel. The one or more heralding signals within a lower-level code may then be used as input to a quantum low-density parity-check code for decoding syndrome measurements with the knowledge of occurrences of amplitude damping decay as indicated via the one or more heralding signals.

Systems and methods are provided. An example method can include obtaining, by a quantum computing system comprising one or more quantum computing devices, first data indicative of a first risk of quantum error associated with a first quantum process and second data indicative of a second risk of quantum error associated with the first quantum process. The example method can further include routing, by the quantum computing system based at least in part on the first data, a first portion of the first quantum process to first quantum hardware implementing a first plurality of qubits in a first quantum code space. The example method can further include routing, by the quantum computing system based at least in part on the second data, a second portion of the first quantum process to second quantum hardware implementing a second plurality of lower-fidelity qubits outside of the first quantum code space.

The invention relates to a three-plane (Triplane)-based 3D Gaussian field generation method, which comprises the following steps of: firstly, inputting and standardizing 3D object data to adapt to three-plane representation; secondly, using a three-plane encoder to encode geometric and Gaussian attributes of the 3D object to three vertical planes, and constructing a three-plane grid; then, geometric and Gaussian field attribute branches of a three-plane renderer are trained, and decoding from a grid to a 3D grid and attributes is achieved; then, the geometrical shape and the attribute of the 3D object are decoded through a three-plane decoder; further, training VAE model compression and reconstructing three-plane representation; compressing the representation into a hidden code by using a VAE encoder, and training a diffusion model in a hidden code space; generating a hidden code of the new 3D object through an inverse diffusion process; and finally, decoding and rendering the implicit code into a 3D Gaussian field point cloud by using a VAE decoder and a three-plane renderer, and generating a high-quality 3D object geometry and rendering result from multiple perspectives. The method ensures the reconstruction quality and the high efficiency of multi-view rendering.

The application provides a training method and device of a large model for PLC code generation, equipment and a medium. The programmable logic controller code generated by the current large language model, the physical state data corresponding to the industrial equipment and the equipment information are obtained; and based on the programmable logic controller code, the physical state data and the physical constraint encoder, the code space vector and the physical space vector are determined, and based on the equipment information, the condition vector is determined; the physical constraint loss value is determined according to the code space vector and the physical space vector; the condition loss value is determined according to the code and the condition vector; the total loss value is determined based on the physical constraint loss value and the condition loss value; if the total loss value is greater than the preset loss value, the parameters of the large language model are updated based on the above loss value; and the step of obtaining the programmable logic controller code generated by the current large language model is returned; until the total loss value is not greater than the preset loss value, to complete the training of the large language model.

The invention relates to the technical field of network technologies, in particular to a data transmission method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a home terminal media access control address mapping relation database MMD table corresponding to a home terminal host and a remote MMD table corresponding to a remote host; according to the home-end MMD table and the far-end MMD table, address addressing and packaging are carried out on the initial source Internet protocol version 6 IPv6 data packet, and a target IPv6 data packet is obtained; wherein the coded address of the target IPv6 data packet comprises a site prefix, a virtual Ethernet identifier, extension information and a home terminal host identity identifier; and transmitting the target IPv6 data packet to a remote host. According to the method and the device, the IPv6 address addressing space is utilized, finer host information among different hosts can be addressed into the target IPv6 data packet, the unique identifier of the home terminal host is reflected on the premise that the MAC address of the home terminal host is not exposed through the home terminal host identity identifier, and the security privacy problem caused by exposure of the MAC address is avoided.

The invention relates to a building data matching method in OpenStretMap based on a rule constraint A-LSTM model, and the method comprises the steps: firstly converting original building shape data in a target data set into a standardized uniform point sequence with the same length through geometric standardization processing and sequence equalization processing; then constructing a double-layer feature description system for the buildings, obtaining local structure feature descriptors and regional structure feature descriptors of all the buildings in the reference data set and the target data set, and forming a feature representation set of the buildings corresponding to the reference data set and the target data set; mapping the feature representation of the building into a compact representation vector in a feature space through an A-LSTM model; and finally, similarity measurement is performed on representation vectors output by the A-LSTM model based on multi-criterion constraints, and coding space representation information, spatial position constraints and geometric overlapping constraints are fused to obtain a matching result.

The application discloses a method for obtaining size-adjustable PUF based on mixed halogen pure inorganic perovskite phase separation, and the method realizes mixed halogen pure inorganic perovskite microspheres with random distribution of spatial positions and halogen proportions by introducing ion exchange through a two-step chemical vapor deposition method. According to laser beam array scanning, the application encodes collected fluorescent responses into keys, and based on the phenomenon of laser irradiation-induced mixed halogen pure inorganic perovskite phase separation, the application obtains independent keys under different laser intensities. By randomly combining the above independent keys, the application expands the key size and coding space, and can realize size-adjustable PUF with higher security.

The application discloses a text monitoring method and device based on mixed word vector coding; wherein the method comprises: crawling public opinion text; using a BERT model to encode the public opinion text to obtain a word vector corresponding to each character; performing word segmentation on the public opinion text to obtain a plurality of words; searching for a first word vector corresponding to the word from a preset dictionary; the first word vector is a spatial anisotropy improved word vector obtained by using a linear discriminant analysis method to perform word vector clustering on an initial word vector according to categories; obtaining a second word vector corresponding to the word according to the word vector; merging the first word vector and the second word vector corresponding to the word to obtain an improved word vector; and performing public opinion monitoring based on the improved word vector, which solves the problems of narrow word vector coding space and obvious anisotropy in the prior art when using a BERT model for word vector coding.

The invention discloses a fan blade deformation detection method and device based on time sequence multi-source fusion, computer equipment and a computer readable storage medium, and relates to the technical field of detection, and the method comprises the following steps: obtaining three-dimensional acceleration and angular velocity time sequence data of a plurality of inertial measurement units in a preset time window; mapping the multi-dimensional original data to a unified coding space through embedded layer representation processing, inputting the multi-dimensional original data into corresponding long and short-term memory networks respectively, extracting time sequence features and generating a hidden state matrix; and calculating a dynamic weight based on the matrix, and outputting a blade deformation parameter and a classification result through weighted fusion and one-dimensional convolution combined modeling. According to the time sequence multi-source fusion fan blade deformation detection method, multi-source IMU time sequence data are effectively fused, the nonlinear composite deformation feature capturing capability is improved, and the detection accuracy and adaptability are remarkably improved.

Systems and methods are provided. An example method can include obtaining, by a quantum computing system comprising one or more quantum computing devices, first data indicative of a first risk of quantum error associated with a first quantum process and second data indicative of a second risk of quantum error associated with the first quantum process. The example method can further include routing, by the quantum computing system based at least in part on the first data, a first portion of the first quantum process to first quantum hardware implementing a first plurality of qubits in a first quantum code space. The example method can further include routing, by the quantum computing system based at least in part on the second data, a second portion of the first quantum process to second quantum hardware implementing a second plurality of lower-fidelity qubits outside of the first quantum code space.