75 results about "Numbering" patented technology

The embodiment of the invention provides a code repairing method, device and equipment based on a large language model.The method comprises the following steps that a code to be repaired is analyzed through a code scanning tool on the basis of a coding specification, error information of the code to be repaired is obtained, the error information comprises an error number, a violation rule, a supplementary description, an error example, a correction example, an error type and an error code segment; generating a cue word template according to a historical repair sample and a coding specification of the large language model, and filling the cue word template with the error information to generate a filled cue word; and inputting the filled cue word into the large language model to generate a repair code segment, judging whether the repair code segment accords with a set conversion specification, and if the repair code segment accords with the conversion specification, replacing the code to be repaired with the repair code segment to generate a repaired code. According to the scheme, the code is repaired through an end-to-end automatic process, and the code repairing efficiency is improved.

The invention relates to the technical field of code pre-configuration, in particular to a demand-oriented code pre-configuration method, system and equipment and a storage medium. Matching a plurality of performance function number sequences from the code function library according to the function requirements of the target scene; performing function demand sample frequent mining on the target scene to obtain a function demand input parameter and a function demand output identifier set; inputting the function demand input parameters into a plurality of function number sequences to obtain a plurality of function demand prediction outputs; traversing the plurality of function demand prediction outputs for outlier analysis to obtain a plurality of output prediction outlier factors; traversing the plurality of performance function number sequences to carry out calculation power demand prediction to obtain a plurality of expected calculation power; and based on the plurality of expected computing power and the plurality of output prediction outlier factors, sorting the plurality of performance function number sequences to obtain a target performance function number sequence, and executing code pre-configuration. The code development efficiency is improved, and the code practicability is enhanced.

The invention discloses a policy service recommendation method and system based on a large language model, and relates to the field of policy information, and the method comprises the steps: analyzing a policy file, extracting policy terms with a numbering structure, building a unique identifier, and forming a term node set; identifying explicit or implicit reference behaviors in terms, constructing a reference path, and generating a reference directed graph; constructing a clause mapping tree based on the target clauses; mapping tree nodes are extracted to form structured prompt information, and the structured prompt information is embedded into large language model input; generating a policy report paragraph containing clause reference content; and outputting the structured policy text with clause reference chain closure and recommending the structured policy text to the user. According to the method, the clear reference context combined with the user information can be provided for the large language model, the large language model is guided to generate a text with a reasonable structure and complete terms for recommendation, and the problem of inaccurate generation when an existing model processes a complex reference structure is solved.

The invention discloses a power grid equipment intelligent numbering and anti-error checking method and system constructed based on a dispatching numbering agent, equipment and a medium, and belongs to the technical field of power systems and intelligent dispatching. The method comprises the steps that a knowledge graph is constructed through semantic analysis of a power dispatching standard document; extracting equipment attributes and topological contexts and organizing the equipment attributes and the topological contexts into structured prompts; the scheduling numbering agent generates a candidate number with an interpretable reasoning chain based on the knowledge graph; and verifying the number compliance through multi-dimensional introspection check and outputting a final number. According to the method, the intelligent workflow is constructed, the progress from rule matching to standard understanding is realized, and the traceability and logic consistency of the numbering process are ensured while the rule priority and the topology context are precisely processed by utilizing interpretable thinking chain reasoning and auto-reflection check closed loop.

The invention relates to the technical field of data acquisition, in particular to an AI-based electric power big data acquisition and processing method. According to the method, numbering extraction is carried out on field contents and upper and lower positions of the power maintenance log and the transaction contract data, a propagation path between fields is constructed on a semantic level, and field groups with semantic offset and structural dislocation are subjected to bidirectional alignment after difference identification; according to the method, field semantic expressions and sequence positions are synchronously corrected in the association process, the accuracy of field connection between different types of data is improved, continuous judgment is conducted in combination with time parameters, connection between maintenance and contract fields better fits the actual business process, field contents and connection relations are further archived after field combinations are aligned, and the efficiency is improved. And a structured basis is provided for data reconciliation and scheduling collection, and the semantic consistency, the structure matching degree and the application availability of an electric power big data acquisition processing result are remarkably improved through the processing flow.

The invention provides a building standardization knowledge base building method and system based on a large language model, and the method comprises the steps: carrying out the semantic partitioning of a building specification document set, and obtaining knowledge unit blocks and the logic association relation thereof; processing the knowledge unit blocks by using a large language model, generating a complete coding identifier of an independent knowledge unit and a boundary association identifier of an associated knowledge unit, and determining an association type mark; for the associated knowledge units, determining adjacent knowledge unit blocks and candidate knowledge units according to association type marks and logic association relationships, matching target knowledge units through global positioning identifiers, and allocating same integration numbers; counting the number of independent knowledge units and the number of integrated numbers, and calculating the sum to determine the total quantity of knowledge entities. According to the method, accurate association and integration of knowledge units are realized through a hierarchical numbering system and semantic association strength. According to the method, the construction efficiency of the building standardized knowledge base and the semantic consistency of the knowledge entities can be improved.

The invention relates to the technical field of teaching management systems, in particular to an artificial intelligence teaching model construction method based on big data driving, and the method comprises the following steps: extracting a task jump combination, generating a jump amplitude sequence, dividing sections, recognizing a path structure, counting numbering frequency changes, analyzing a path activeness state, and marking a degradation and unlocking path. And adjusting model path configuration, and reconstructing a structure path mapping table. According to the method, cross-segment behaviors of task numbers in a capability target space are analyzed by constructing jump node combination data, segments are divided based on jump amplitude, number boundary offsets are compared, a path division mode with number structure change characteristics is formed, and a target descending trend is extracted by combining number frequency change and a path activation proportion. The path state attenuation features are screened out, synchronous analysis of the number activeness and the structure participation degree in path selection is realized, and the distinguishing capability and the updating response speed of the path state identification are improved.

The invention discloses a biomass pyrolytic reaction network prediction method based on a graph theory and quantum chemistry, which comprises the following steps: analyzing the molecular structure of a biomass initial reactant, abstracting the molecular structure into a directed graph molecular model, marking a potential conversion path after molecular mechanics optimization, generating a unique identifier by using an atom numbering rule and a Hash algorithm, and predicting the biomass pyrolytic reaction network. Functional groups are extracted and packaged into sub-graph modules, chemical bond parameters are obtained in combination with quantum chemistry calculation and are converted into fracture probabilities, basic reaction building blocks are predefined to traverse and mark breakable bonds, fragments are recombined and then de-weighted through Hash, and then reaction activation energy weights are given to side chemical bond fracture reactions; an energy optimal path is screened by means of a priority queue search algorithm, accurate analysis of a chemical bond fracture path and intermediate product conversion in the biomass pyrolysis reaction network is finally achieved, reaction path and product distribution are efficiently predicted, and the calculation efficiency and precision of a complex system are balanced.

The invention provides a circular target design and detection method for a multi-task scene, and the method comprises the steps: image preprocessing, candidate contour extraction, affine transformation correction, circular contour recognition, arc segment recognition, central point positioning, and coding and decoding, and the target is composed of a central circle, a positioning ring, and 12 arc segments. 12-bit binary codes are constructed through black and white binary arc sections, rotation invariant recognition is achieved by adopting a minimum decimal numbering rule, in the recognition process, high-precision positioning of a center point is achieved through multi-circle contour weighted fusion, and screening of the arc sections is completed according to angle and radius variance features; according to the method, a plurality of circles of circular structures including the center circular contour, the positioning ring and the coding ring are designed in the circular coding mark target, and a multi-circle-center weighted fusion positioning strategy is introduced in the target center point calculation process, so that errors caused by local contour recognition deviation can be effectively counteracted, and the center point positioning precision of the target is improved.

The invention relates to the technical field of post training simulation, in particular to a virtual internet-of-things practical training post skill platform construction method, which comprises the following steps of: spreading a serial number state among nodes through a graph neural network, forming a comparable arrangement structure in a plurality of dependency paths through serial numbers, and presenting a post task start-stop relationship in a continuous serial number chain form; the execution sequence of post tasks is expressed by an extensible number sequence, and the tail number difference and the repeated numbers are memorized and expressed through a long-short-term memory network, so that subsequent post operation numbers can form continuous inference according to preorder number characteristics, and post action changes form distinguishable paragraphs in a number chain; by counting inconsistent parts of action numbers and writing the inconsistent parts into a deviation number sequence, deviation positions are presented in a centralized manner in a number form, and abnormal numbers form clear identifiers in a record set, so that workflow identification, step deviation positioning and abnormal operation calibration have recordable and traceable coherence.

This invention discloses a method, system, and medium for storing degree-of-freedom numbers in a numerical computation grid, relating to the field of numerical computation technology. By improving the storage structure of degree-of-freedom numbers, the storage and access efficiency of degree-of-freedom numbers is optimized, and different numbering methods can be selected according to actual needs, thereby improving the flexibility and overall performance of numerical computation. Two data sets are designed for each variable group to uniformly store the degree-of-freedom numbers of variables within the group, and the storage space occupied is effectively reduced through data compression.

The present invention belongs to the field of civil engineering tests, and specifically relates to a concrete test mold with a numbering function, including a test mold body and a sealing cover, wherein the sealing cover has a plurality of numbering modules inside, wherein the numbering modules include an embedded body fixed to the sealing cover and a numbering key, wherein the bottom of the numbering key has a character mold, and the numbering key can be moved and fixed in the embedded body, and can also be separated from the embedded body. The present invention solves the problem that the concrete test mold cannot be numbered in time after casting, and the numbering characters are easy to fall off during the maintenance of the test mold, resulting in poor marking effect. The present invention has the effects of rapid numbering, clear numbering, and good numbering durability.

The invention discloses a variable topology system dynamics recursion grouping method based on graph theory description, and belongs to the field of spacecraft dynamics. The implementation method comprises the following steps: automatically calculating a cyclic dimension based on a graph theory algorithm, matching non-tree edges, generating pseudo nodes, and converting a ring-containing structure into a connected ring-free tree structure; multi-module topology automatic continuation: through a node number continuation method, automatically identifying repeated nodes, deleting redundant description and splicing new module topology, and realizing topology unified description of multi-module assembly; according to the method, a dynamic model is automatically grouped, manual derivation is not needed, a constraint equation is described by a body-pseudo body recursive relationship, a unified recursive relationship of rigid body-rigid body, flexible body-flexible body and rigid body-flexible body connection is combined, modal parameters are automatically called, a grouping matrix is generated, and the dynamic equation is output, so that automatic modeling updating can be realized. According to the method, automatic dynamic grouping of the variable topology system can be realized, dynamic reconstruction is avoided, and characteristic analysis and attitude control of an on-orbit assembly system are facilitated.

The application discloses a hot data reading method and related device, and relates to the technical field of computers.In the application, the target data is determined as hot data based on a target count identifier of the target data; a target logical address of the target data is subjected to a shift operation according to a set step length, and a target number of a target red-black tree is obtained; the target red-black tree is obtained from a red-black tree set based on the target number; a target offset is obtained based on the target logical address and the set step length, a target physical address is obtained from the target red-black tree based on a first address of the target red-black tree and the target offset, and the target data is obtained according to the target physical address.In this way, cold and hot data are distinguished through variable count identifiers, the accuracy of hot data screening is improved, and the physical addresses of the hot data are stored in the red-black tree through a hash algorithm, so that the hot data searching speed is also improved in the case that the hot data amount is large.

The present invention provides a configuration synthesis method for the planetary gear mechanism of a floor grinding machine based on graph theory. This method first deeply analyzes the planetary gear mechanism to determine the quantitative relationship of basic elements, and obtains a new quantitative relationship of elements through high pair-low substitution. Then, it uses adjacency matrix interpolation to generate the adjacency matrices of all configurations, and on this basis, eliminates various unreasonable monochromatic topological graphs. According to the method of the canonical adjacency matrix set, the configuration synthesis of monochromatic topological graphs is carried out, and combined with the length requirement of the longest transmission chain of the planetary gear mechanism, the monochromatic topological graphs that do not meet the conditions are excluded. Finally, the position points suitable for high pairs and compound hinges are selected to generate a multicolor topological graph. After carrying out canonical point numbering and one-to-one correspondence verification on the multicolor topological graph, the entire configuration synthesis process is completed. This method realizes the configuration synthesis of complex planetary gear transmission coefficients, ensuring comprehensiveness and high efficiency.

The invention provides an intelligent cargo box loading control method, which comprises the following steps of: classifying cargo boxes in a current order by sizes, and sequencing and numbering the cargo boxes according to a delivery quantity; according to the truck bed size and the cargo box size, calculating the whole-row cargo stacking parameters of each cargo box according to a gap filling optimization dynamic planning algorithm; according to the sizes of various containers in the current order, calculating a mixed code corresponding table of the containers with mixed codes; the mixed code corresponding table is looked up, whether the cargo box A with the serial number being 1 can be mixed with other cargo boxes or not is judged, and if not, the cargo box A is stacked in one row again; if yes, finding a container B which corresponds to the container A with the number of 1 and can be mixed in code and has the first sequence number, selecting the containers of the type for mixing in code, and calculating the number of mixed-code containers of the last layer; modifying the mixed code corresponding table; and step 6, according to the numbering sequence in the step 1, and so on, finishing the goods stacking planning of all types of containers in the current order. According to the invention, the automation level, the operation efficiency and the operation stability of container loading operation are greatly improved.

The invention relates to the technical field of prefabricated member construction buildings, in particular to a modeling method based on a 3D complex frame structure in three-dimensional modeling, which comprises the following steps: S1, numbering one by one; s2, dividing a space region; s3, the assembly bodies are numbered in order; s4, obtaining a reference surface; s5, determining a character writing area; s6, determining the joint of the assembly body; and S7, determining a character writing direction. The method has the beneficial effects that the part structures are marked again, and the connecting surfaces, the character areas and the connecting areas are determined by utilizing the geometric topological structure data, so that personnel can be helped to quickly understand the connection of the structures, the possibility of errors during manual sectional material distinguishing, measurement and construction is reduced, and the working efficiency is improved. And the connection relationship between the structures is determined, so that the construction efficiency of the structures is improved.

The application discloses a kind of batch fast creation pile foundation model and batch parameter assignment method and system programmed using Python language, and its method includes: S1: extracting the parameter data required for modeling from pile foundation CAD design drawing, and collating to form standardized data table;S2: using Python language and its pandas data processing library, write the data matching and structured script of pile foundation;S3: in the Dynamo visual programming environment of Revit platform, construct Dynamo node package, and node package is used to define the creation rule and parameter assignment logic of pile foundation model;S4: run Dynamo node package in Revit project file, use intermediate file as the input data of Dynamo node package, automatically batch create pile foundation model and give each pile foundation model corresponding parameter.The application innovatively uses Python space index grid algorithm, realizes the automatic accurate matching of pile foundation center circle graphics and numbered text in CAD drawing, solves the problem of artificial checking of massive pile foundation data.

The present invention discloses a malicious program behavior characterization method based on a morpheme word vector model, which includes sorting and abstracting the captured malicious program function call information, extracting high-frequency sequences, and setting segmentation points; performing redundancy removal and de-obfuscation to obtain a new function sequence S'; obtaining the morphemes in the function name f to obtain the corresponding morpheme list M of the function, filling the marker Mask for the morpheme list with a non-maximum length, numbering the morphemes and function names respectively, and applying one-hot encoding to the numbers of the function names, morphemes, and placeholders to train the word vector model; calculating the feature vector of the function and calculating the TF-IDF of each function. It effectively solves the encryption and obfuscation problems existing in dynamic function calls and can quickly perceive and understand the behavior of malicious programs.

A design tool is disclosed for using determination and generation of port connection of a network-on-chip (NoC), wherein the connections are presented in regular expression to allow for increase in speed of connection and reducing the potential for user introduced errors. The design tool allows for use of regular expressions to automate the process and autogenerating of names by the design tool using numbering in regular expression as a suffix. The design tool includes a large language model or a machine learning model that is trained for synthesis and generation of the NoC and is capable of providing suggested connections based on intake of regular expressions. The model can also receive feedback from past or previous synthesis for further training of the model.

The invention relates to a code generation method based on artificial intelligence, and relates to the field of electric digital data processing. The method comprises the following steps: executing a task number by adopting a convolutional neural network model according to various function association information of a latest writing function of a current executable code file, intelligently analyzing the function name of the next writing function of the newest writing function by the preorder task number and the subsequent task number of the execution task and the binary data flow corresponding to the written code paragraph; and automatically generating a function frame corresponding to the function name below the latest compiled function. The invention further relates to a code generation system based on artificial intelligence. According to the method and the device, aiming at the technical problem that the code knock-in task of a programmer is heavy due to the fact that the subsequent function framework cannot be automatically generated, the framework of the subsequent function which is not manually knocked in can be automatically generated by adopting the artificial intelligence model according to the overall information of the code file and the existing function data, so that the technical problem is solved.

The invention provides an optimization method of a software model and related equipment. The optimization method of the software model comprises the following steps: determining correlation parameters among various states in a to-be-optimized software model; in the framework of the software model, moving two states corresponding to associated parameters greater than an associated threshold value, so that the two moved states are adjacent; according to the positions of the states after the frame is moved, numbering each state; and according to the serial numbers of the states, generating state machines corresponding to any two states with a jump relationship, and storing the state machines. According to the method and the device, the skipping efficiency between the states in the software model is improved.

The application discloses a Token marking method and a cognitive system for large language model input data, and belongs to the technical field of artificial intelligence. The application generates corresponding discrete coordinates for each Token input into the large language model, including: a time coordinate for providing a unified time reference; a context coordinate for identifying a dialogue time sequence; a logic coordinate for identifying the sequential position of the Token in a text or instruction, and the logic coordinate is independently numbered within the range defined by the time coordinate or the context coordinate; and a device coordinate for identifying an Internet of Things device, a role or a priority. The coordinates jointly constitute a unified discrete space-time cognitive framework, and provide a structured worldview for the large language model, so that the large language model can perform structured understanding based on multi-dimensional information such as time, context, logical sequence and identity. The application does not change the core architecture of the model, has strong compatibility, and can be widely applied to the fields of multi-round dialogue, intelligent customer service, industrial automation, smart home, Internet of Vehicles and the like.

The invention discloses a method for changing graph numbers of technological equipment products in batches based on Catia secondary development. The method mainly solves the problems that the process of changing the graph numbers of the technological equipment products by means of an existing method is tedious, the efficiency is low, and errors are prone to occurring. The implementation method comprises the following steps: 1) arranging and opening process equipment products; (2) obtaining a Catia active window document object and carrying out non-null judgment on the Catia active window document object; 3) collecting all product objects on the process equipment product assembly tree; 4) inputting an original graph number, changing the name of the graph number, and performing non-null judgment; (5) the changed product file is constructed, and original product document objects are collected; the method comprises the steps of (1) collecting product items, (2) collecting the product items, (3) collecting the product items, (4) collecting the product items, (5) collecting the product items, (6) changing reference links, instance names and part numbers of all the collected product items, and (7) storing and closing movable window document objects, closing Catia software and deleting original product document objects.

The application belongs to the technical field of computer software and information security, and particularly relates to a pseudo-random dictionary generation and distribution method and system based on index mapping. The method comprises the following steps: obtaining a character dictionary and a target string length to obtain an initial character sequence; randomly rearranging the initial character sequence to generate a disordered character dictionary; calculating a total combination space of the string according to the disordered character dictionary and a character repetition constraint condition; mapping a numerical index into a target string on demand based on the total combination space of the string through a pseudo-random dictionary mapping method; grouping the numerical index to form a serial number pool, and persistently storing the index sequence in each serial number pool after randomly disturbing the index sequence; and taking out an actual index value from the current serial number pool according to a distribution cursor during the running period, converting the actual index value into a final string result through a mapping method, and outputting the final string result. The application realizes the unique generation and safe distribution of the string through the index mapping and double disordering mechanism, avoids the running period repetition verification, and prevents the number from being speculated.

The application discloses a construction method table identification method and device, computer equipment and a storage medium, and relates to the technical field of table identification. The method comprises the following steps: acquiring a construction method table, extracting text rows from the construction method table; performing semantic classification on the text rows to determine the field types of the text rows; dividing all method content fields into at least one method block based on semantics; and determining the method number fields, method name fields and applicable part fields matched with the method block based on the position information of the method block, the method number fields, the method name fields and the applicable part fields in the construction method table. The application overturns the traditional table identification process of "restoring the physical structure first, and then extracting the content according to the columns", and breaks through the dependence of traditional table identification on the physical structure through the "semantic aggregation + spatial reverse matching based on the method block" strategy. The "semantic aggregation + spatial positioning" method significantly improves the field recognition accuracy for complex construction method tables.

Disclosed is a method and system for automatically generating question and query pair from a knowledge base that involves accessing a knowledge base to extract one or more entities and one or more predicates, generating a baseline question template from a context free grammar rule, inputting the one or more entities and the one or more predicates into the baseline question template to generate a numbered question template, generating a typed question template by traversing the numbered question template through a predicate type-graph, generating a SPARQL query by inputting the one or more entities and the one or more predicates into a SPARQL query template, generating a question by inputting the one or more entities and the one or more predicates into the typed question template, and constructing a question and query pair by combining the question and the SPARQL query.

The present invention relates to the technical field of prefabricated construction, and specifically to a modeling method for a 3D complex frame structure based on three-dimensional modeling, comprising S1: numbering one by one; S2: dividing spatial regions; S3: sequentially numbering assemblies; S4: obtaining reference surfaces; S5: determining text writing areas; S6: determining assembly connections; and S7: determining text writing directions. Beneficial effects of the present invention: This application renumbers component structures and uses geometric topological structure data to determine connection surfaces, text areas, and connection areas, thereby helping personnel quickly understand the connections of structures, reducing the possibility of errors in manually distinguishing profiles, measuring, and building, clarifying the connection relationships between structures, and thereby improving the efficiency of building structures.

1. The name of this design product: automatic numbering machine. 2. Purpose of this design product: used for number printing and numbering. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Design 1 3D drawing. 5. Designate Design 1 as the base design.

The present invention discloses a method for generating an automated test process, including: receiving a test case set input by a user client and a selected automated test framework, inputting the test case set into the automated test framework, within the automated test framework, performing label numbering on the test case set to obtain a test case label set, performing missing value filling and dictionary format conversion on the test case label set to obtain a dictionary test label set, performing dictionary level division on the dictionary test label set to obtain hierarchical test labels, and adjusting the operation priority of the hierarchical test labels to obtain a test process. The present invention also proposes an automated test process generation device, an electronic device, and a computer-readable storage medium. The present invention can improve the selectivity and dynamicity of the test process.