153 results about "Recursive algorithms" patented technology

Techniques are described for partitioning B-tree keys of file systems into key ranges for parallel processing in delta generation during file storage replications between file systems in different cloud infrastructure regions. In certain embodiments, a delta generation processing for cross-region replication may utilize a key-range splitting mechanism involving a recursive algorithm that partitions B-tree keys of a source file system into roughly equal-size key ranges. All the partitioned key ranges may be processed in parallel and concurrently by different processing threads, one thread per key range, to improve the performance of the delta generation and achieve scalability.

The invention discloses a pepper freezing temperature gradient dynamic adjusting method and system, particularly relates to the technical field of industrial freezing temperature control, and is used for solving the problem of temperature gradient misalignment caused by the fact that a static model does not sense dynamic changes of material thermodynamic parameters in real time in an existing freezing control method. Temperature distribution and gas flow rate data in the freezing process are collected in real time, a high-confidence-coefficient data subset of a low-flow-rate area is screened based on spatial correlation, the dynamic heat conduction coefficient of the material is identified online through a recursive algorithm, and the dynamic heat conduction coefficient of the material is identified through a double-threshold-value judgment mechanism of the energy release rate and the phase lag angle. Performing segmentation fitting to generate a stable parameter sequence; further dynamically adjusting a preset temperature gradient model through a nonlinear correction strategy to generate a self-adaptive gradient control curve, and finally driving heat exchange rate adjustment to realize closed-loop tracking of the actual temperature gradient on a target curve; the freezing uniformity and energy efficiency of the high-moisture material are remarkably improved, and the control precision caused by thermal response mismatch is improved.

The invention discloses an intelligent document analysis method and system, the method is executed by the intelligent document analysis system, and the method comprises the following steps: carrying out layout analysis on a PDF page by adopting a deep learning model; merging the block list from bottom to top by adopting a recursive algorithm; carrying out balance optimization on the binary tree structure; and outputting a result of the processed binary tree structure by adopting a preorder traversal mode. Layout analysis is carried out by adopting a deep learning model, various complex typesetting formats such as multi-column layout, image-text mixed typesetting, tables, lists and the like can be effectively identified and processed, and semantically continuous text blocks are ensured to keep continuity in a tree structure through a tree structure optimization module; a global semantic error correction module is added to carry out global document semantic representation learning and carry out adaptive adjustment and error correction on a preliminary structure, so that deep ambiguity is eliminated, logic errors are repaired, and the consistency of a final analysis result and human reading logic on the semantic level is maximized.

The invention discloses a cue word compression method and device of a large language model and a medium. The method comprises the steps that redundant vocabularies and redundant statements are recognized and removed according to the size relation between the vocabulary importance score and the importance threshold value of each vocabulary after original cue word segmentation; constructing a local syntax tree of each statement, and constructing a global analysis tree by the local syntax trees according to the dependency relationship among the cue words; calculating a local information entropy so as to align the LLM word segmentation device with nodes on the global analysis tree and adjust node values of the global analysis tree; trimming the global analysis tree through a recursive algorithm according to the adjusted node value, and generating a compression prompt corresponding to the prompt word; according to the method, the compression prompt is evaluated, the compression prompt is iteratively optimized according to an evaluation result, the cue word is reconstructed according to the optimized compression prompt, and compression of the cue word is achieved.

The invention discloses an intelligent power prediction method considering dynamic load change, and relates to the technical field of power grid load prediction, and the method comprises the steps: collecting original load data, carrying out the preprocessing, constructing a VMD constraint optimization model, carrying out the four-stage improvement of optimization parameters through employing an improved dung beetle optimization algorithm, so as to generate IMF components, reconstructing the IMF component by calculating a sample entropy to obtain a low-frequency component and a high-frequency component; establishing a Kalman filtering state space model based on the low-frequency component, and decomposing the low-frequency component into a residual component and a pseudo trend component through a Kalman filtering recursive algorithm; external features are obtained, the high-frequency component, the residual component and the pseudo trend component are aligned and spliced with the external features, multi-component collaborative prediction is carried out through a local-global interactive attention mechanism, and a final load prediction result is obtained; and generating a power demand visualization chart based on the final load prediction result. And reliable decision support is provided for power dispatching and energy management.

The invention discloses a dynamic course planning method based on an adaptive learning algorithm. The method comprises the following steps: S1, constructing a multi-dimensional data model of a learner knowledge space; s2, forming a knowledge graph represented by fractal characteristics; s3, identifying weak areas and potential knowledge blind spots in the knowledge space of the learner; s4, recursively decomposing the knowledge graph by using a fractal recursive algorithm according to a real-time knowledge state analysis result of the learner in combination with a learning target; s5, optimizing recommendation content and performing dynamic adjustment according to knowledge mastering conditions, weak knowledge points and learning behavior preferences of the learners; and S6, according to the learning resources recommended in the step S5, by monitoring the performance data of the learner in the learning process in real time and combining a performance data analysis result, dynamically adjusting a learning path and resource recommendation content, optimizing learning suggestions and updating the knowledge state of the learner in real time until course planning is finished. According to the method, the personalized learning requirement can be better met, and the learning effect and the cross-scene adaptability of the system are improved.

Provided are a deformable tracked pipeline robot, and a differential turning method thereof. The deformable tracked pipeline robot includes a robot main body. Three tracked foot modules in a circular array are arranged on an outer side surface of the robot main body, each tracked foot module is connected to the robot main body through a center variable-diameter module. A spacing between the tracked foot module and the robot main body can be adjusted through the center variable-diameter module, making all three tracked foot modules in contact with an inner wall of a pipeline. According to a differential turning method based on space curve measurement, the pipeline robot can pass through pipelines with various curvature radii. A pipeline axis is measured by a Charge Coupled Device camera module as a bending curvature of a space curve. The accuracy of space curve fitting is improved by a recursive algorithm.

The invention belongs to the technical field of information security, and relates to an Android malicious software detection method based on API semantic enhancement, and the method comprises the steps: obtaining a to-be-detected Android application; performing static analysis on the to-be-detected Android application, and constructing a function call graph of the to-be-detected Android application; optimizing the function call graph of the Android application; extracting a complete API context sequence of a corresponding function from the optimized function call graph by adopting a recursive algorithm; adopting Skpi-Gram to map the complete API context sequence into feature vectors, and adopting a clustering algorithm to divide the feature vectors with close distances into the same class; inputting the clustered feature vectors into a trained graph convolutional neural network model to obtain a detection result of the to-be-detected Android application; according to the method, the extracted function call graph nodes are optimized by adopting the graph convolutional neural network, so that information loss caused by feature structure conversion is avoided, and the efficiency of model training and the accuracy of a detection result are improved.

The invention provides a high-order Bezier curve automatic edge sealing method in three-dimensional printing, and the method comprises the steps: extracting model edge points, calculating control points, and generating a smooth Bezier curve edge sealing path; the method relates to de-noising processing, curve point calculation through a recursive algorithm, edge point extraction and connection sequence recognition, control point optimization, path planning and optimization and solidification through the laser or electron beam solidification technology, in the process, a high-precision sensor monitors the edge sealing quality in real time, imaging parameters are automatically adjusted to optimize the effect, and the quality of the edge sealing is improved. According to the method, the edge sealing accuracy and the surface quality are improved, the method is suitable for complex model printing, material waste is reduced, and related computer programs are stored in a medium and used for achieving the method.

The present invention discloses a program static analysis method and system based on LLVM, belonging to the technical field of computer program analysis. The technical problem to be solved is that the existing program analysis technologies have low accuracy, low efficiency and limited application scope in estimating program performance characteristics and memory reuse distance distribution. The method includes: converting a source file into an LLVM IR file with source-level debugging information; traversing modules, functions, basic blocks and instructions in the LLVM IR file to obtain static trace information of a target function; constructing a basic block-level control flow graph of the LLVM IR file and annotating relevant information; identifying and annotating loop information when traversing paths to obtain an execution path with loop annotations, replacing basic blocks in the execution path with corresponding memory access information, and generating a static memory trace with loop annotations; calculating the memory access reuse distance distribution through a recursive algorithm based on the static memory trace with loop annotations.

The invention provides a self-adaptive regulation and control method for a hydrogen production system based on real-time parameter feedback, and relates to the technical field of process control, the method comprises the following steps: collecting an input instruction signal and a controlled state variable signal of the hydrogen production system, and comparing a fluctuation energy index with a preset identification dead zone threshold; if the fluctuation energy index is lower than the identification dead zone threshold value, the current controller parameter is kept unchanged; if the fluctuation energy index is higher than the identification dead zone threshold value, activating an online parameter identification step; calculating a dynamic confidence interval of process model parameters; judging whether the process model parameters estimated in real time fall into the dynamic confidence interval or not; if the process model parameters fall into the dynamic confidence interval, converting the process model parameters estimated in real time into control parameters of a PID (Proportion Integration Differentiation) controller, and updating the control parameters into a control loop of the hydrogen production system; and if the process model parameter exceeds the dynamic confidence interval, resetting an internal state vector of the recursive algorithm in the online parameter identification step by using a boundary value.

The invention relates to the technical field of information processing, in particular to a parallel computing method and system for a tensor protocol and computer equipment, and the method comprises the following steps: a tensor segmentation step: dynamically segmenting a high-dimensional tensor based on a non-protocol dimension to obtain a plurality of sub-tensors; a sub-tensor distribution step: distributing a plurality of sub-tensors to a plurality of calculation processing units based on the number of the sub-tensors; a sub-tensor parallel reduction step: performing parallel reduction on the plurality of sub-tensors by the plurality of calculation processing units based on a recursive algorithm to obtain a reduction result tensor; and a reduction result tensor writing-back step: writing the reduction result tensor back to the main memory.

The invention belongs to the technical field of microscopic image panoramic stitching, and provides an image stitching technology for a digital microscopic scanning system. Comprising the steps of panoramic focal length strategy setting, mobile shooting, label processing, local feature point extraction, single image matrix determination, overall splicing and non-blank overlapping region splicing, sliding feature fine alignment path deviation data calculation, panoramic focal length strategy adjustment and gap fusion processing. According to the method, the ResNet-18 model is used for performing high-density region judgment, so that the feature point detection efficiency is improved; through a linear gradual change technology and a recursive algorithm, the splicing problem of non-blank overlapping areas is solved, and the quality of the spliced image is improved; weighted average fusion is carried out through a Gaussian function, the problems of brightness difference, color non-uniformity, edge blurring and the like of a splicing area are solved, and the visual effect of the image is improved. By judging the position deviation function, the objective table is adjusted in real time, the operation process is simplified, and the cooperative efficiency of scanning and splicing is improved.

The invention relates to the technical field of data processing, and discloses a shape space-based face continuous expression migration method and system. The method comprises the following steps: obtaining shape space representation data through Kendall shape space transformation, generating a source face continuous expression curve by using a spherical B-spline interpolation algorithm, constructing a two-parameter geodesic mapping function, calculating a target face interpolation point by using a De Boor recursive algorithm, obtaining a deformation sequence through Riemannian manifold parallel transmission, and obtaining the shape space representation data through the deformation sequence. And finally, performing Kendall shape space inverse transformation to obtain expression migration data. According to the method, continuous and natural expression migration is realized, and meanwhile, the workload of manual adjustment is reduced.

In an aspect, there is provided a computer-implemented method for approximating product production in a bioreactor. The method comprises: providing a bioreactor containing live cells in a substrate, the bioreactor for cultivating, over a time period, a product derived from or of the cells during a manufacturing process; providing two or more sensors for measuring respective two or more different physical attributes of the substrate during the time period; receiving, at a processor, sensor data from the two or more sensors; and determining via the processor, based on a predetermined or recursive algorithm that correlates the sensor data and the product production by independent consideration of the sensor data of the two or more different physical attributes or by multivariate consideration of the sensor data of the two or more different physical attributes, an approximate amount of the product.

The invention provides a processing method and system for multiplexing low-code platform components and related equipment. The method comprises the following steps: acquiring project component parameters and managing component states by using a Vuex mode; deeply copying the multiplexing component by using a Loash library; performing data serialization on the multiplexing component to obtain to-be-processed component data; carrying out ID related parameter replacement on the to-be-processed component data based on a preset rule; performing event decoupling on the to-be-processed component data through an observer mode, and processing a nested task by using a recursive algorithm; performing message subscription, equipment resource updating, API resource updating and page resource updating on the to-be-processed component data; performing variable mapping relation updating of a preset processing mode on the to-be-processed component data based on the component type; and performing CSS style modularization and style isolation on the to-be-processed component data to obtain target component data, and registering the target component data. According to the method, the automatic processing of the component ID, the dependency relationship, the associated resources and the nested structure in the component multiplexing process is realized.

The invention belongs to the technical field of industrial automation control, and relates to a seasoning filling PID parameter adaptive optimization control method and system. The method comprises the steps that the real-time temperature of fluid in a filling pipeline, the static pressure of a valve inlet, the instantaneous flow and a valve opening instruction are collected, and moving average filtering preprocessing is carried out; constructing a self-adaptive forgetting factor calculation model based on the viscosity-temperature characteristics, and calculating a current optimal forgetting factor according to the fluid temperature change rate, the flow prediction error and the fluctuation condition of the flow data; a recursive algorithm is used for identifying the system process gain online, and the proportional gain of a PID controller is calculated in real time according to the identified process gain and the ratio of the hydrostatic pressure to the standard reference pressure; and the gain is input into a controller, and a final valve opening instruction is generated in combination with integral and differential terms. According to the method, the dynamic adjustment of the algorithm memory length can be realized, the viscosity change can be quickly adapted, excessive filling and slow response are eliminated, and high-precision filling under complex working conditions is ensured.

The invention provides a motion platform magnetic compensation method based on a time-varying magnetic interference model, and the method comprises the steps: decomposing a magnetic interference compensation task into a development stage and a task stage, and obtaining an initial value of a magnetic compensation coefficient of a magnetic interference model through a conventional calibration mode in the development stage; in the task stage, the magnetic compensation coefficient of the magnetic interference model is decomposed into a time-varying coefficient and a time-invariant coefficient, high-altitude maneuvering does not need to be carried out through a traditional calibration mode, and rapid optimization of the magnetic compensation coefficient of the magnetic interference model is achieved on an air route flying to a task area through simple maneuvering flight in combination with a recursive algorithm. According to the method, the complexity of traditional calibration flight is reduced, the optimization speed of magnetic compensation coefficients of magnetic interference compensation in different task areas is improved, and the method has better adaptability to diversified scenes with limited cruising ability and high task instantaneity requirements.

The invention relates to the technical field of agricultural environmental engineering and control, and discloses an agricultural non-point source pollution multistage control planning system and method based on a discussion hall architecture, and the system comprises an organization-level module, an adaptation-level module, a coordination-level module, an operation control-level module, a controlled-level module, a comprehensive integration discussion hall module, and an open external interface module. The organization level uses deep learning and causal inference to generate a full-watershed strategy; the discussion hall module fuses expert experience conversion constraints and carries out case migration; the adaptation level utilizes a recursive algorithm to dynamically correct model parameters; the coordination level adopts a hybrid optimization algorithm to solve a multi-objective optimization problem; the operation control level is combined with a feedforward feedback mechanism to generate an instruction; the controlled level executes actions and collects feedback; and the interface module is responsible for security encryption and verification of data interaction. According to the method, the expert intelligence of the discussion hall and the five-level hierarchical architecture are fused, qualitative and quantitative combination and full-basin dynamic collaborative optimization are realized, and the management and control precision and the response speed are improved.

The present invention discloses a document intelligent parsing method and system, which is executed by a document intelligent parsing system. The method includes the following steps: using a deep learning model to perform layout analysis on PDF pages; using a recursive algorithm to merge the block lists from bottom to top; optimizing the balance of the binary tree structure; and outputting the result of the processed binary tree structure using a pre-order traversal method. By using a deep learning model to perform layout analysis, it is possible to effectively identify and process various complex typesetting formats such as multi-column layouts, mixed text and image layouts, tables, lists, etc., using a tree structure optimization module to ensure that semantically continuous text blocks also maintain continuity in the tree structure, and by adding a global semantic error correction module to perform global document semantic representation learning, adaptively adjust and correct the preliminary structure, thereby eliminating deep ambiguity, repairing logical errors, and maximizing the consistency of the final parsing result with human reading logic at the semantic level.

The invention discloses a low-orbit Doppler positioning method and device for dynamically weighting epochs based on an intelligent agent, and belongs to the technical field of satellite navigation positioning. According to the method, an initial position and an initial state covariance matrix of a receiver are determined based on an initial accumulation low-orbit non-cooperative signal of the receiver, an initial point location of a current epoch signal is determined when a new low-orbit non-cooperative signal is received so as to realize time frame synchronization, and a state characteristic of the current epoch signal is determined at least based on the initial point location. The state features at least comprise satellite features, epoch state features, signal state features and positioning state features, determining a weight of a current epoch signal based on the state features using a pre-training agent, and determining a real-time position of the receiver based on the current epoch signal and the weight of the current epoch signal using a recursive algorithm, according to the invention, adaptive empowerment based on the multi-dimensional features of the epoch signal is realized, the accuracy of the determined epoch signal weight is improved, and the positioning precision is improved.

The present invention discloses an automated integration method for IO signals based on a FADEC operating system. The method comprises the following steps: using Eclipse CDT to parse all structure variables in the As_interface.h file and store them in a linked list A; extracting valid information from each element in the linked list and storing the information in a new linked list B; using a recursive algorithm to convert linked list B into n syntax trees based on pre-defined structure variable names A0 to An-1 for signal interaction between the AS and the OS, with the root nodes of the syntax trees being A0 to An-1, respectively; performing a depth-first search on the generated n syntax trees to automatically generate all signal names; and generating an IO signal integration record file based on a pre-defined IO signal integration template. The method automatically converts nested structures into syntax trees, saving manual time. The method also performs a depth-first search on the syntax trees to automatically generate all IO signals, resulting in a concise and accurate method.

The invention relates to a monitoring data recursive calculation method and application thereof in a CCUS project. An estimation error used for describing the difference between an estimation value and a true value and a measurement error used for describing the difference between a measurement value and the true value are introduced; the comprehensive error is obtained by dividing the previous estimation error by the sum of the previous estimation error and the current measurement error; an initial estimation value and an initial estimation error are randomly given, then an initial comprehensive error is estimated, then a subsequent estimation value is calculated through a recursive algorithm, and the initial comprehensive error is updated to be used for calculation of the subsequent estimation value. After a plurality of rounds of measurement and calculation, an estimated value is closer to a real value, and all measurement data in the earlier stage does not need to be backtracked, so that the problems of a large amount of repeated redundancy and large error of monitoring data are effectively reduced; and the method provided by the invention is used for realizing carbon dioxide leakage monitoring in a CCUS project.

The present invention discloses a circuit grouping analysis method, system, terminal and medium based on graphic processing, which relates to the field of electronic design technology. The key points of the technical solution are: after parsing the PDF file, split it to obtain multiple circuit pictures, and perform binarization processing on the circuit picture to obtain a circuit image; use a recursive algorithm to seed fill the circuit image to obtain multiple circuit structures assigned different color labels, and each circuit structure is assigned a unique color label; obtain the center coordinates of each device schematic symbol from the design data, and map the center coordinates into pixels in the circuit image, and divide the two devices into the same device group when the color labels of the pixels corresponding to the two devices are the same; merge multiple device groups according to electrical rules to obtain functional groups; use multimodal large model technology to classify functional groups and device groups to obtain classification results. The present invention significantly improves the efficiency and accuracy of circuit grouping.

The application relates to a DAG-based hierarchical data storage and loading method, which comprises the following steps: step S1, constructing a DAG hierarchical data storage model and storing hierarchical data; step S2, traversing the data in the DAG hierarchical data storage model, loading the hierarchical data by using a depth-first recursive algorithm; and step S3, performing index extraction of information through a relationship link between hierarchical data. The application effectively solves the problem of hierarchical data storage and loading and has the advantages of high data storage efficiency and fast loading speed.

The embodiment of the invention provides a category and library table dependency relationship determination method and device, equipment, a medium and a product. The method comprises the following steps: for any data access layer bean in a target project, running a first execution code corresponding to the data access layer bean; according to an SQL statement generated during the operation of the first execution code and a method name for calling the SQL statement, determining a first dependency relationship between a method contained in the data access layer bean and library table information; for any control layer bean in the target project, detecting dependency classes of all hierarchies corresponding to the control layer bean through a recursive algorithm, and when the dependency classes are data access layers bean, determining methods included in the data access layers bean; and determining the dependency relationship between the classes and the library table information in the target project according to the dependency classes of all hierarchies corresponding to each control layer bean, the methods contained in the data access layer bean and the first dependency relationship corresponding to each data access layer bean, so that the overall efficiency of analysis can be improved, and the probability of misplacement missing and misplacement can be reduced.

The embodiment of the invention discloses a superconducting quantum chip wiring path optimization method and device based on an RDP algorithm. A specific embodiment of the method comprises the following steps: simplifying an initial wiring path in a superconducting quantum chip wiring diagram through an RDP recursive algorithm to obtain a simplified wiring path; carrying out collinear point identification on the simplified wiring path, and optimizing the simplified wiring path; for each line segment in the optimized wiring path, executing the following processing steps: in response to determining that a global minimum distance corresponding to the line segment is greater than or equal to a preset safety buffer distance, determining the line segment as a compliant line segment; and performing line segment safety verification on the optimized wiring path, and determining the optimized wiring path as a target optimized wiring path in response to the fact that the optimized wiring path passes the safety verification. According to the implementation mode, through iterative collinear point elimination, the curvature change rate smoothness of a wiring path is improved, and the requirement for low-impedance connection between superconducting quantum bits is met.

The invention discloses an emergency evacuation whole-course commanding and dispatching method based on a big data model, and relates to the technical field of emergency management, and the method comprises the steps: dividing an evacuation region into a plurality of dynamic grid units, distributing and calculating weights, building a hierarchical data processing model, forming a self-adaptive data flow, and carrying out the hierarchical extraction of the data flow through a weight recursive algorithm, the method comprises the following steps: generating a regional feature matrix, constructing a multi-dimensional evaluation index, carrying out combinatorial analysis on the evaluation index by using a deep reinforcement learning model, outputting a decision suggestion sequence, generating an optimal resource allocation scheme, dynamically partitioning a withdrawal region, formulating a withdrawal time sequence for each partition, and establishing a partition cooperation mechanism. Calculating an optimal withdrawal sequence among the partitions through a game theory model; and generating a scheduling instruction according to the partition cooperation mechanism, and performing real-time optimization on the scheduling instruction based on the withdrawal process feedback data. According to the invention, intelligent commanding and dispatching of the emergency evacuation process are realized, and the safety and efficiency of large-scale crowd evacuation are improved.

The invention provides a satellite hyperspectral channel selection method and device, and the method comprises the steps: calculating the drop rate of a value function corresponding to each satellite hyperspectral channel, and taking the channel with the maximum drop rate as a first selection channel; an alternative channel is screened through an included angle range of Jacobin vectors of an unselected channel and a selected channel after linear transformation, so that atmosphere information contained in the alternative channel is remarkably different from that contained in the selected channel; combining each alternative channel with the selected (n-1) channels, calculating the drop rate of the value function by using a recursion method, and taking the channel with the maximum drop rate as the nth selected channel; and calculating a weight inverse matrix after the combination of the selected n channels by using a recursive algorithm for selecting the next channel, and repeating the above process until n is equal to a preset value. According to the method, the maximum decline rate of the value function is used as a channel selection standard, the assimilation reliability and accuracy of the variational method are ensured, and due to the calculation complexity and the parallel function of O (n2), the method has high calculation efficiency.

An embodiment of the present invention discloses a method, device, equipment and computer program product for obtaining and identifying data lineage, which relates to the field of big data technology, and includes: obtaining a data lineage query instruction input by a user, where the data lineage query instruction contains the data to be queried; querying the data to be queried through a recursive algorithm to obtain associated data that has a dependency relationship with the data to be queried, where the dependency relationship includes a direct dependency relationship or an indirect dependency relationship; determining the data lineage of the data to be queried according to the associated data and the dependency relationship, and displaying the data lineage in a specified format. By using a recursive algorithm to obtain associated data that has a direct dependency relationship or an indirect dependency relationship with the data to be queried, it will not cause the lack of intermediate links when determining the data association relationship, so as to display a comprehensive data lineage according to the user's data query requirements.