135 results about "Error location" patented technology

The invention relates to the technical field of drawing auditing, and discloses an artificial intelligence assistant for auditing a CAD drawing of a transformer substation. The artificial intelligence method for auditing the CAD drawing of the transformer substation comprises the following steps: obtaining a DWG drawing and an auditing specification PDF file through a uniform interface, analyzing a primitive by using a pyautocad or ezdxf library, extracting equipment information and a topological relation, constructing a position-based drawing knowledge graph, and storing the position-based drawing knowledge graph in a Neo4j database. And performing OCR and BERT vectorization on the PDF, and storing the PDF into an FAISS search library. A LangChain framework is utilized to integrate a knowledge graph and a text library to construct a mixed retriever, an optimization cue word is generated and input into a Deepseek large model for examination and reasoning, and finally, an error position is marked in AutoCAD with a red box. According to the method, the equipment information can be automatically extracted from the drawing, the topological relation of the equipment can be identified, and accurate and rapid auditing is performed in combination with related auditing rules, so that the substation drawing auditing efficiency and accuracy are remarkably improved.

The invention relates to an intelligent error correction method and system based on a deep thinking dialogue large model, and the method comprises the steps: receiving a to-be-detected text, guiding a large language model to execute a content correction and verification task for the to-be-detected text through employing a pre-constructed multi-modular prompt instruction, and generating a preliminary processing result containing structured error information and correction suggestions; based on context information of a to-be-detected text, error positioning in the primary processing result is accurately calibrated, verification is carried out through three verification mechanisms of semantic verification, knowledge graph verification and historical verification, and a final processing result is generated and stored in a data storage unit; the final processing result is analyzed in real time in a data stream transmission mode, an analysis result is displayed on a user interface, and a corresponding position in the to-be-detected text is synchronously displayed in a highlight mode. According to the method, errors can be accurately positioned, model illusion is reduced, the correctness of terms and factual contents is ensured, and an efficient and reliable solution is provided for new media content auditing.

The embodiment of the invention discloses a method for intelligently assisting in reviewing a water conservation scheme of a water and soil conservation production and construction project, and the method achieves the intelligent feature matching of a new scheme and similar cases through the construction of a tagged knowledge base integrating historical cases of multiple industries, so as to recognize the generality compliance. A double-engine review mechanism is adopted, a form review module automatically checks document structure integrity and format specifications, and a logic review module executes cross-chapter data consistency check and business logic compliance analysis and highlights and positions error positions in a document. And recording decision logic in real time to form a feedback closed loop. And dynamically optimizing case library matching weight and recognition rules based on high-frequency error statistics and expert correction records. The modes of positioning review key points to chapters and sections, describing specific requirements of each review key point in a language, adding a check formula among data to review content needing to be calculated, determining a check type to which each review key point belongs, and the like are adopted, and the model is trained more clearly, so that the model has relatively professional review ability.

The invention provides an automatic workflow code generation method driven by a large model, which comprises the following steps: sequentially converting an original demand into a subtask set, a node relation graph and structured workflow description data through multi-stage agent cooperation, and forcibly checking a data closed loop between nodes by the last-stage agent; tool nodes and content generation nodes are defined in the workflow description data, and decoupling of content generation and tool calling is achieved; analyzing the structured workflow description data, dynamically generating a strong type state class mapped with the description data, and automatically filling a node calling logic and a parallel routing rule based on a preset code template to generate a workflow code; when the code runs wrongly and the number of retry times exceeds a preset threshold value, an execution track is generated through the error positioning agent, candidate schemes are generated in parallel through the multiple repairing agents, and after self-adaptive scoring is conducted through the scoring agent based on the error type, the repairing schemes are verified and executed in sequence.

The invention discloses a data error correction method and device based on low-density parity check, equipment and a medium, and relates to the technical field of data error correction, and the method comprises the steps: reading data to be corrected from a data memory, and carrying out the pre-verification of the data to be corrected and a verification matrix of a preset low-density parity check code, and obtaining a pre-verification result; based on the pre-verification result, determining a first error position set in a code word position set; performing bit flipping operation on code words indicated by the first error position set to complete pre-error correction; and inputting the code word after pre-error correction processing into a low density parity check decoder for decoding, outputting data after error correction, pre-detecting the error position of the code word, and performing bit flipping on the code word at the error position, thereby reducing the number of error bits entering LDPC decoding, and improving the decoding efficiency. Therefore, the number of error bits does not exceed the decoding capability limit of hard decoding, the probability that the system enters soft decoding is reduced, and the decoding throughput rate of the system is ensured.

The invention provides a large language model JSON output repairing method and system based on ANTLR grammar analysis, and belongs to the technical field of model repairing. The method comprises the following steps: preprocessing an original output text of a model to obtain a to-be-repaired JSON text; constructing a fault-tolerant grammar rule, and generating a JSON grammar parser according to the fault-tolerant grammar rule; a JSON text to be repaired is input into an analyzer, grammar analysis is carried out in stages by adopting a progressive grammar matching strategy, and error node position coordinates and error types of grammar analysis anomalies are positioned by analyzing a context tracking mechanism; according to the position coordinates of the error nodes and the error types, performing context-aware repair on the text by adopting a hierarchical repair strategy to obtain a repaired JSON (JavaScript Object Notation) text; and performing multi-layer verification on the repaired JSON text by using a multi-layer verification mechanism, and outputting the repaired JSON text after the multi-layer verification is passed. According to the method, the error classification accuracy and the error positioning precision in the JSON output repairing process are improved, and then the repairing success rate of large language model JSON output is improved.

The invention provides a user-defined script dynamic editing and executing method and system of a Unity engine. The method comprises the following steps that codes are input and preprocessed; executing text cleaning, word segmentation and annotation preprocessing according to the line feed as a code line set; grammatical analysis and semantic understanding; constructing an abstract syntax tree, identifying a syntax structure, and combining context analysis semantics to generate a symbol table; processing errors in real time; positioning an error line through a multi-stage matching strategy, highlighting an error position through a visual interface, and generating a repair suggestion in combination with a line number mapping table, error propagation analysis and a multi-evidence fusion mechanism; executing dynamic codes; explaining and executing the corrected script, and feeding back an execution result; through interaction with a Unity engine, operation control of a script on a game object and a scene is realized; through three core technologies of semantic weight dynamic matching, an anti-interference navigation state machine and a hybrid sorting algorithm, the long-standing problems of low matching precision, poor interaction experience and the like in the field of code completion are solved.

The invention relates to a data verification method, a data verification device and a storage medium. The method comprises the following steps: firstly, through semantic analysis, establishing a mapping relationship between a first position corresponding to first text data in an editable format in a to-be-verified first document and a second position of second text data in a target format in a second document, so that an original to-be-verified text and a to-be-verified text after format conversion form a position corresponding relationship; then, verifying the second document through semantic analysis, and taking second text data which does not pass verification in the second document as annotation data; and finally, based on the mapping relationship, determining the labeling position of the labeling data in the first document, and generating an editable error prompt at the labeling position. Therefore, the time for manually searching the error position of the original document is shortened, and the verification and correction efficiency is improved, so that the data verification efficiency is improved.

The embodiment of the invention provides a purchase file verification method and device, a medium and a product, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring an electronic purchase file subjected to format standardization preprocessing; comparing the electronic purchase file with a preset early warning knowledge base to obtain a comparison result; under the condition that the comparison result shows that the electronic purchase file passes verification, atomic knowledge points of the electronic purchase file are obtained by using a preset hybrid neural network model, and a verification report is generated based on the atomic knowledge points; the verification report includes at least one of a pass item, an error location, or a correction suggestion. According to the scheme of the invention, the format of the electronic purchase file is unified according to the electronic purchase file subjected to standardized preprocessing, and the defects of a traditional contract generation technology are overcome by using the dual verification of the preset early warning knowledge base and the hybrid neural network model.

A memory device includes a syndrome calculator configured to generate an error location signal based on first data and an error correction code; an error corrector configured to generate second data by correcting an error in the first data according to the error location signal; and a data mask (DM) calculation circuit configured to generate a DM signal according to logic high bits of the first data and change a logic level of the DM signal according to at least one of an increase signal and a decrease signal, by activating the increase signal when an error bit is detected in logic low bits of the first data and activating the decrease signal when the error bit is detected in the logic high bits of the first data, based on the error location signal.

To prevent degradation of service to users by analyzing reading errors of an absolute positioning system that detects absolute positions.SOLUTION: An elevator system includes an APS tape on which absolute position information is continuously set corresponding to the position of the car in the direction of movement within the elevator shaft, an APS sensor installed on the car and equipped with two cameras that read absolute position information corresponding to the car's position, and an information processing device that processes the absolute position information read by the APS sensor. The two cameras are positioned so that the reading positions of the absolute position information are separated by an offset distance in the direction of movement. The information processing device includes a recording processing unit that records error information including the error position when a reading error occurs in each of the two cameras, and a compilation processing unit that compiles compilation data that associates the error position with the number of errors based on the recorded error information.SELECTED DRAWING: Figure 8

The invention discloses a dynamic error correction system and method for an OTP (One Time Programmable) memory, a computer and a storage medium, and the system comprises a cross-clock synchronization module which is used for synchronizing asynchronous data of an OTP interface to a system clock domain and generating a control signal according to a data format; the double-buffer-area module is used for alternately writing data and reading a control signal by utilizing two independent buffer areas, and correcting and outputting the written data; the CRC decoder module is used for carrying out error detection on the synchronous data; the error position searching module is used for positioning an error position candidate item of each channel; the error position matching module is used for finding out a uniquely matched error position; and the read control module is used for judging whether data reading needs to be paused or not and starting error correction operation, and sending a control signal to the double-buffer module. According to the invention, a modular architecture design is taken as a core, and a complete processing flow from data receiving, error detection, error positioning to error correction output is constructed.

The present invention provides a novel storage device. A test bit generation unit has the function of generating a test sequence from an information sequence. A storage unit has the function of storing, in a flip-flop circuit, a codeword that is constituted by the information sequence and the test sequence, and outputting the codeword as a received word. An error detection correction unit has the function of outputting an error vector which indicates the position of an error in the received word and a decoded word in which the error in the received word has been corrected. The storage unit has the function of storing the decoded word in the flip-flop circuit in accordance with the error vector, the function of writing the decoded word to a holding circuit, and the function of writing back, to the flip-flop circuit, the decoded word written in the holding circuit. The flip-flop circuit has a first transistor. The holding circuit has a second transistor. The off current of the second transistor is smaller than the off current of the first transistor.

The invention belongs to the technical field of artificial intelligence, and relates to an image encryption method, which comprises the following steps: acquiring a to-be-encrypted original image; preprocessing the original image based on a preprocessing module to obtain a state matrix corresponding to the original image; performing dynamic key generation processing on the state matrix based on the target zero neural network to obtain an original key; performing random enhancement processing on the original key based on a random security enhancement module to obtain a target key; performing encryption processing on the original image based on the target key to obtain an encrypted image corresponding to the original image; and carrying out output processing on the encrypted image. The invention further provides an image encryption device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the error positioning information can be stored in a block chain. The image encryption method and device can be applied to business scenes of image encryption in the financial field and the medical field, and dynamic adaptability and safety of the image encryption process are effectively ensured by combining multiple function modules.

The invention discloses a flash memory error correction method and system based on adaptive learning, and relates to the technical field of data storage.The flash memory error correction method comprises the steps that flash memory voltage distribution and error code positions are collected in real time, and dynamic feature vectors are generated in combination with environmental parameters; constructing a hypergraph neural network based on the dynamic feature vectors, obtaining error propagation risk scores of the storage areas, and generating a priority list; based on the priority list, the check connectivity of the low-density parity check matrix is adjusted through matrix reconstruction, and a sparse check matrix is formed; an initialization parameter and a solution vector are generated based on the decoder ready state signal, sampling iteration and threshold judgment are carried out, and a decoding result is output; and when decoding fails, performing multi-device parameter updating by adopting aggregation optimization, and performing decoding again to output final correction data. According to the method, collaborative error correction is optimized through multi-device parameter aggregation, so that the limitation of single-device decoding is solved, the global error correction performance is optimized, and the fault-tolerant capability is enhanced.

The invention provides an automatic software test method and system, a storage medium and equipment, and the method comprises the steps: obtaining a target code, extracting related information and test requirements, and generating a test case according to the target code and the test requirements through a trained large model; in response to the code change information, evaluating the influence range of code change on the test case, performing static analysis, determining the change of a code structure, performing dynamic analysis, and determining the change of a code execution path; according to the evaluation result of the influence range of the code change on the test case, determining a test case automatic adjustment strategy, running the adjusted test case, obtaining log data in the running process, extracting error information in the log data, performing code mapping on the error information, and determining an error position. According to the method, a large model technology is utilized, and the processes of automatic generation, intelligent adjustment, automatic result analysis, accurate problem positioning and the like of the test case are optimized, so that the efficiency and the accuracy of software testing are remarkably improved.

Receiving a codeword of a forward error correction (FEC) code, each codeword in the FEC code having a minimum distance of at least seven to any other codeword in the FEC code, calculating multi-bit syndromes by applying columns of a check matrix to the received codeword using combinatorial logic, and responsively determining the received codeword comprises at least three errors, determining coefficients of an error locator polynomial using a coefficient combinatorial logic circuit by combining the multi-bit syndromes using non-iterative combinatorial logic performing arithmetic operations in a finite field F(2 n ), determining respective error positions for each error of the at least three errors by determining roots of the error locator polynomial using a non-iterative root-finding combinatorial logic circuit, the non-iterative root-finding combinatorial logic circuit performing arithmetic operations in the finite field F(2 n ), and correcting each of the at least three errors in the received codeword.

A method may include generating a state signal indicating a state of error location polynomial (ELP) determination by an ELP determination circuit; and control the ELP determination by the ELP determination circuit in response, at least in part, to a value of the status signal.

Embodiments of the present invention provide a memory operation method, a memory, an electronic device, and a storage medium. The memory operation method comprises: in response to detecting an error in a storage array of a memory during a working state of the memory, determining an error location of the error in the storage array; after the memory enters an idle state, controlling the memory to initiate a post-package repair process, and on the basis of the error location, performing replacement of a target storage cell at the error location with a replacement storage cell in the storage array used for the post-package repair process; and after the post-package repair process, switching the memory back to the working state, and using the replacement storage cell to replace the target storage cell for operation. The memory operation method can improve the reliability of the memory.

A decoder includes a syndrome generator and an error pattern classifier. The syndrome generator generates a first syndrome, a second syndrome, and a third syndrome based on a reception vector and a parity check matrix and outputs the first syndrome, the second syndrome, and the third syndrome, The error pattern classifier receives the first syndrome, obtains symbol error location information obtained based on mapping information between a spotty and adjacent symbol error (SASE) and the first syndrome, changes the first syndrome to a normalized syndrome based on a first received symbol, obtains an adjacent error vector based on mapping information between the normalized syndrome, the second syndrome, and the third syndrome and the SASE, and corrects an error of the reception vector based on the symbol error location information and the adjacent error vector.

The embodiments of the present invention relate to the field of natural language processing technology and provide a text error correction method, device, electronic device, and storage medium. The method comprises: obtaining a target text to be corrected and performing semantic boundary recognition to obtain all semantic boundaries; then dividing the target text into multiple clauses, assigning IDs according to the order in which each clause appears, and generating structured data with sequence IDs; inputting the structured data into a language model, and calling the target domain knowledge base corresponding to the target text as a constraint condition to perform semantic parsing and identify the error type; adjusting the error correction path based on the error type and then re-identifying the error information, wherein the error information includes error content, error type, and error location; and reorganizing multiple clauses based on the sequence ID and error content, error type, and error location to generate an error correction result including the error location, error type, and correction suggestions. Thus, the coordinated detection and correction of grammatical, semantic, and logical errors is achieved.

This application discloses a high-precision error compensation method for the optical axis of a continuous zoom lens, relating to the field of lens inspection. The continuous zoom system is disassembled into independent components and mounted on a rotating stage centering fixture. Static center offset data for each component is calculated by rotating and acquiring the image point trajectory circle. Sampling parameters are set according to the zoom ratio of the continuous zoom system and the movement speed of each component along the optical axis during zooming, while simultaneously acquiring dynamic optical axis offset data of the components. A nonlinear mapping relationship is constructed between the static center offset data and the dynamic optical axis offset data, and a center offset-optical axis error coupling model is established. Based on the deviation compensation amount, the actuator is driven to adjust the position and / or angle of the components, and the optical axis accuracy index is verified after compensation. This solution achieves deep coupling between static and dynamic data, improving the accuracy of error tracing and the specificity of compensation; ensuring coverage of key error locations during zooming; supporting real-time compensation, and enhancing the stability and accuracy of the system during zooming.

The invention provides a Verilog code repair method and system based on compiler feedback drive and Agent, and the method comprises the steps: obtaining a defect code, and carrying out the preprocessing, and obtaining a preprocessed defect code; constructing a structured abstract syntax tree AST; a Verilog compiler is used for compiling the preprocessed codes, error information is collected, error positions are mapped to corresponding nodes in a structured AST, and line-level and grammar node-level positioning is achieved; performing an iterative repair cycle based on the Agent to obtain a repaired Verilog source code; and outputting the restored Verilog source code and the restoration report. According to the Verilog code repairing method and system based on the compiler feedback driver and the Agent, the hierarchical structure and semantics of the Verilog code can be deeply understood, and the repairing accuracy and reliability can be remarkably improved.

The present invention provides a large language model JSON output repair method and system based on ANTLR grammar parsing, belonging to the field of model repair technology. The method preprocesses the original output text of the model to obtain the JSON text to be repaired; constructs fault-tolerant grammar rules, and generates a JSON grammar parser based on the fault-tolerant grammar rules; inputs the JSON text to be repaired into the parser, adopts a progressive grammar matching strategy to perform grammar parsing in stages, and locates the error node position coordinates and error type of the grammar parsing anomaly through a parsing context tracking mechanism; adopts a layered repair strategy to perform context-aware repair on the text based on the error node position coordinates and error type to obtain a repaired JSON text; utilizes a multi-layer verification mechanism to perform multi-layer verification on the repaired JSON text, and outputs it after passing the multi-layer verification. The present invention improves the error classification accuracy and error location accuracy in the JSON output repair process, thereby improving the success rate of repairing the JSON output of the large language model.

The invention relates to a code error feedback method combining static analysis and dynamic analysis, and mainly solves the problems of insufficient error feedback and low efficiency in an Online Judge system: reconstructing codes of correct and error versions, including alignment and renaming of variables, and rearranging statements on the premise of not influencing semantics; static and dynamic multi-level alignment is carried out, in the static alignment, an editing script with the minimum cost is calculated through a heuristic editing distance algorithm, an alignment block and a difference list are obtained, in the dynamic alignment, compiling execution is carried out on source codes of two versions, test cases which do not pass operation are dynamically printed through gdb, and execution track information of the test cases is dynamically printed through gdb; error positioning is achieved, data flow backtracking analysis and scoring are carried out on error positions, and error feedback is generated. The method has the characteristics of high execution efficiency, high accuracy and easier understanding of generated feedback, automatic feedback of error codes can be realized, and the learning efficiency of students in programming tasks is improved.

The application discloses a kind of method, device, edge controller and paver of controlling paver automatic driving.It includes: determining the initial position information of paver in stationary state;Determine the first position information of paver in first time after paver changes from stationary state to running state and the second position information of paver in second time, the second time is later than the first time, and the first position information and the second position information are determined by the camera device installed on the paving;If the second position information is error position information, the error position information is corrected to correct position information based on the initial position information and the displacement line fitted from the first position information, so that the paving is automatically driven according to the preset driving line.The method corrects error position information, and controls paver to automatically drive along the preset driving line according to correct position information.

The invention discloses a method for enhancing large model json generation capability and a plug-in tool, and relates to large models and computer technologies, the method comprises the steps that a json repair plug-in is provided to assist an input task prompt, and the json repair plug-in executes the following steps: according to recently output historical tokens reasoned by LLM, current accumulated output is recognized to reach a json repair condition, and repair of a json result is triggered; according to the format requirement of json, the content of the character string is analyzed into a corresponding josn format according to the historytokensstr generated by the LLM, and the reason and the position of an analysis error are recorded; and repairing the incomplete json character string by utilizing a json-mini-gpt repairing model according to the recorded cause and position of the error. According to the method, a feasible process is provided, the json generation capability of the large model is obviously improved, and the influence on the performance and intelligence of the LLM is obviously reduced.

An electronic memory device includes a cyclic redundancy check (CRC) checker configured to receive received data and a CRC codeword including a received CRC code, derive a comparison CRC code from the received data, and determine whether the received CRC code and the comparison CRC code are the same; and an error position estimation data sampler configured to sample error position estimation data indicating an estimated position of an error in the received data when the received CRC code and the comparison CRC code are different, and transmit the error position estimation data to a CRC checker in which the CRC checker recalculates the comparison CRC code from the error position estimation data, and transmits the error position estimation data to the CRC checker. And correcting an error in the received data reflected by the error position estimation data when the received CRC code and the re-calculated comparison CRC code match.

The present invention discloses a multi-FPGA global synchronization triggering method and system for an FPGA simulation and verification platform. The present invention includes that in each clock cycle, if any FPGA meets the triggering condition, the master node directly or indirectly obtains the timestamp of the triggering moment and the sampling address at the triggering moment, and calculates the depth of continuous sampling after the master FPGA node is triggered and the timestamp of sampling stop; sets the trigger status register to "1", and saves the trigger status register, the timestamp of the triggering moment and the sampling address at the triggering moment to the register module for the host computer software to read. At the same time, the master node encapsulates the timestamp of sampling stop into a message and broadcasts it to all slave nodes to control the slave nodes to stop sampling. The present invention can realize the synchronous triggering of multiple conditions of distributed FPGAs, and provide efficient error location and diagnosis capabilities for global debugging and diagnosis in the parallel simulation process of multiple FPGA chips.