240 results about "Logic structure" patented technology

The invention relates to the technical field of software development management, in particular to an internet software development management system and method. The method comprises the following steps: collecting an original function demand set and carrying out function clustering analysis; extracting and classifying demand function features and generating independent demand units; carrying out dependency analysis on the independent demand units; constructing a dependency relationship set and a demand logic structure; the method comprises the following steps: generating a demand framework matrix, carrying out organization network simulation to obtain a demand connection network, carrying out code reverse evolution according to the demand connection network, carrying out basic parameter matching to obtain evolution basic parameters, carrying out a pressure simulation test on the evolution basic parameters to generate a pressure test result, and capturing resource pressure defects based on the pressure test result. And optimizing and adjusting the evolution basic parameters to generate optimized development parameters. According to the invention, a more efficient Internet software development management method is realized.

The invention relates to the technical field of data optimization, and discloses a financial data warehouse intelligent SQL (Structured Query Language) optimization method based on a large model, which comprises the following steps: S1, SQL statement analysis and preprocessing: carrying out word segmentation, grammatical analysis and logic structure analysis on an SQL statement submitted by a user, and identifying keywords, table structures and query conditions in query; s2, large model semantic understanding and optimization suggestion: performing semantic understanding and logical reasoning on the analyzed SQL statements by using a large model, and automatically generating optimization suggestions, the optimization suggestions including index recommendation, query rewriting and execution plan optimization; and S3, generating and selecting a dynamic execution plan. According to the method, the advantages of a large model in the aspects of natural language processing and intelligent decision making are fully utilized and combined with the specific requirements of the financial data warehouse, and the execution efficiency of SQL query and the overall performance of the system are remarkably improved; the query response time of the financial data warehouse can be effectively shortened, and the resource utilization rate is improved.

The invention relates to the field of computer vision, and particularly provides a table recognition reconstruction method and system, a terminal and a medium, and the method comprises the steps: firstly decomposing a large-size table image into a plurality of overlapped sub-images, and carrying out the table structure detection and OCR character recognition of each sub-image through parallel recognition; then, sub-graph recognition results are integrated through a coordinate mapping and confidence coefficient weighted fusion algorithm, and boundary errors are eliminated; then, automatically distinguishing common cells based on an area clustering algorithm, merging the cells and a header region, and reconstructing a complete table logic structure; further understanding header semantics through a natural language model and repairing identification errors; and finally, realizing intelligent splicing and standardized output of the cross-page table. According to the method, the memory limitation of the traditional OCR technology is broken through, an oversized table can be processed, the recognition accuracy of a complex structure is improved, and the digitization efficiency of professional documents such as financial statements and engineering drawings is improved.

The invention relates to the technical field of data processing, and discloses a big data-based file analysis storage division mode and a distributed storage system.The method comprises the following steps: S1, file analysis: analyzing an input big data file, and extracting a logic structure, field content and an association relationship of the big data file; s2, data block generation: dividing an analysis result into data blocks, and generating size and relevance information of the data blocks; s3, association weight generation: establishing a weight relationship between the similarity between the data blocks and the joint access frequency; and S4, storage division optimization: based on the association weight, optimizing the distribution of the data blocks among the storage nodes. According to the method, distribution of the data blocks is optimized through the synergistic effect of the association weight generation module and the dynamic decision-making module, so that the data blocks with high association degree are preferentially distributed to the same storage node, cross-node data transmission is greatly reduced, a storage strategy can be adjusted in real time, and the storage efficiency is improved. Therefore, communication delay and network resource consumption caused by cross-node access are reduced.

The invention discloses a multi-modal index knowledge base and a construction method thereof. The construction method comprises the following steps: processing a heterogeneous document to obtain a semi-structured document; identifying a title hierarchical relationship of the document to construct a document logic structure; carrying out minimum chapter blocking on the text of the semi-structured document to obtain logic blocks; performing semantic segmentation on each logic block to obtain text blocks; the method comprises the following steps: constructing text block nodes by meta-information of text blocks, constructing non-text block nodes by meta-information of non-text elements, extracting document nodes, chapter nodes and chapter-chapter inclusion relationships according to a document logic structure, respectively extracting semantic information from the text blocks and the non-text elements, and storing the semantic information in a database; recording the corresponding relationship between the text block nodes and the semantic information and between the non-text block nodes and the semantic information; constructing a knowledge graph based on each node and relationship and storing the knowledge graph into a graph database; and constructing semantic knowledge based on the semantic information and storing the semantic knowledge into a vector database. According to the scheme, lossless retention of multi-modal information and structured organization of document logic are realized, and efficient indexing and accurate recall are facilitated.

The invention relates to the technical field of quality monitoring, in particular to a virtual simulation and real-time decision-making system for canned fish production quality risks, which is characterized in that data stability and jump accuracy are improved by adopting a filtering mode, a key path area is screened, a conduction trunk is formed, synchronous construction of a mapping and adjusting strategy is realized, and a real-time decision-making result is obtained. By introducing action time, a control time consumption difference value and a node jump amplitude trend multi-dimensional quantitative judgment standard into an execution structure, a feedback recognition mechanism of index fluctuation is enhanced, the abnormal trend response granularity is improved in cooperation with multi-dimensional nested calculation of temperature and pressure parameters, synchronous association of key control parameters and historical operation tracks in a fault chain is complemented, and the reliability of the fault chain is improved. Through starting from a beat logic structure, data cleaning, trend grouping and traceability return are performed alternately, so that a risk propagation chain obtains collaborative modeling among a pressure difference, a temperature difference and a control instruction, and risk path response consistency and intervention precision under a beat driving condition are enhanced.

The invention relates to the technical field of protection device testing, in particular to a verification method of an intelligent comprehensive protection device, which comprises the following steps of: extracting starting time and response time in a tripping state transition sequence of the protection device, calculating execution delay and action segment length, and comparing and identifying an abnormal link based on a state number sequence; the method comprises the following steps: realizing analysis and standard reconstruction of a state logic structure, forming an ordered tripping path, introducing a long short-term memory neural network to carry out time alignment on a state change sequence and a current signal segment, identifying a potential mismatch or abnormal change trend in a state chain through linkage analysis of a state-current abrupt change position, and reconstructing a state path. According to the method, path continuity and dynamic adaptability are enhanced, a random forest is adopted to take device numbers, the number of jump segments and response residual errors as multiple inputs for training modeling, device scores are output through an integrated tree voting mechanism, and recognition sorting of abnormal frequency significant devices is achieved.

The invention relates to a matrix storage operator optimization method and device, computer equipment and a readable storage medium. The method comprises the following steps: allocating memory resources for target data; determining a logic structure corresponding to the source data, establishing a first mapping relation between each logic index in the logic structure and a register address of the source data, and establishing a second mapping relation between each logic index in the logic structure and a memory address of the target data; and determining a corresponding relationship between a memory address of the target data and a register address of the source data based on the first mapping relationship and the second mapping relationship, and storing the source data stored in a register into a memory resource corresponding to the target data based on the corresponding relationship. By adopting the method, the generalization ability of the matrix storage operator can be improved.

The invention discloses a PDF (Portable Document Format) conversion multiplexing method and device, computer equipment and a storage medium. The method comprises the following steps: extracting metadata features, logic structure features and visual layout features of a PDF document; performing dynamic partitioning according to the type of the PDF document to obtain a plurality of document blocks, and performing hash processing on each document block to generate a corresponding hash value; performing first-level comparison on the PDF document and a PDF document in a historical record according to the metadata features; performing second-level comparison on the PDF document and a PDF document in a historical record according to the logic structure feature; performing third-level comparison on the hash value of each document block in the PDF document and the hash value of each document block in the PDF document in a historical record, and determining whether different document blocks exist in the PDF document or not; if yes, incremental conversion processing is conducted on the difference blocks, the difference blocks obtained after incremental conversion are spliced with the converted parts of the unchanged content in the corresponding PDF document in the historical record, and a complete conversion result is formed. The method greatly improves the conversion efficiency.

The invention belongs to the technical field of PPT generation, and particularly relates to an automatic PPT generation method based on AI and a textbook resource library, and the method comprises the steps: analyzing first input information of a user through a natural language processing technology, recognizing a core concept and a logic structure, and obtaining an analysis result; automatically retrieving teaching materials related to the teaching subject from a teaching material resource library through an AI technology; the method comprises the following steps: selecting layout and design styles from a preset template library according to the characteristics of teaching materials, automatically generating a PPT frame containing characters, pictures and chart elements, and filling the teaching materials into the PPT frame to form a preliminary PPT; performing detail adjustment and optimization on the preliminary PPT by using an intelligent typesetting optimization technology, and generating a preview PPT; and optimizing the preview PPT based on a user feedback learning mechanism to generate a final PPT. According to the invention, intelligent, automatic and personalized generation of PPT can be realized, and the efficiency and quality of teaching resource preparation are improved.

The invention belongs to the field of natural language processing and artificial intelligence, and particularly relates to a long text writing generation method and system based on multi-agent cooperation. The method comprises the following steps: receiving a text theme input by a user, completing complex theme decoupling, and outputting an outline directory; the method comprises the following steps: collecting keywords according to a text topic and an outline catalog, obtaining a retrieval result by retrieving the Internet, a domain database and network resources, and preprocessing to obtain a reference with a uniform format; performing systematic evaluation on the reference literature from the field integrating degree and the logic relevance, and performing grading processing on the reference literature to obtain a high-quality reference literature; based on the text theme and the high-quality reference, long text content is generated according to a set logic structure and writing specifications. According to the method, the fragmented expression problem is effectively avoided, the academic value and reading experience of the text are remarkably improved, the inherent defects of a traditional long text generation technology are practically overcome, and a high-efficiency solution is provided for text creation in the professional field.

The invention relates to the field of databases, and discloses an archive-based data management method and system, which can complete aggregation management of most business data in a single archive, reduce high relational operation overhead caused by multi-table association, and significantly improve flexibility, security and consistency of data management. According to the method, firstly, multiple objects are abstracted from a business scene or a real concept, a main object is selected, other objects related to the main object are aggregated in the same archive model, and the archive model comprises attributes for structured, sequential, log and unstructured data references or pointers. The file model is described through predefined metadata, and a logic structure, integrity constraint, a physical storage position, a storage period, a file model validity period, file attributes, and multi-version management, transaction control and authority control strategies oriented to addition, modification, deletion and check operations are set in the metadata.

The invention provides an artificial intelligence-based interface circuit design method, which comprises the following steps of: S1, acquiring an RTL code for describing a logic structure of a digital circuit, and generating a digital circuit layout according to the RTL code by utilizing a preset neural network model; s2, acquiring a preset process library and design parameters of the analog circuit, and generating an analog circuit layout by using a preset neural network model according to the process library and the design parameters of the analog circuit; and S3, fusing the digital circuit layout and the analog circuit layout by using a preset neural network model to obtain the layout of the interface circuit.

The invention discloses a power distribution network layered optimization method oriented to source-network-load interaction, and relates to the technical field of power system automation. The method comprises the following steps: constructing a dynamic adaptive collaborative architecture, and dynamically generating a three-layer logic structure of global coordination, regional autonomy and local execution according to the real-time state of the power distribution network; operating a three-layer mixed game mechanism, and determining an optimal strategy of each main body through master-slave, cooperation and bilateral interactive games; executing an evaluation-planning-operation three-level closed-loop optimization process, and taking a key performance index fed back by an operation layer as a basis for scheme correction of a planning layer; and a mixed intelligent strategy combining multi-agent deep reinforcement learning and an improved particle swarm optimization algorithm is adopted for solving. According to the method, the problems of hierarchical solidification, benefit coordination imbalance and planning operation splitting in the prior art are effectively solved, and the adaptive capacity, the economical efficiency and the flexibility of the power distribution network in the high-permeability source-network-load interaction scene are improved.

The invention discloses an agent-based test case generation method and device, equipment and a medium, and relates to the technical field of software testing, the method comprises the following steps: in response to a test case generation instruction for a target function, displaying a test case framework of the target function; in response to an interaction instruction for a preset position in the test case framework, obtaining a target test code of the target function; wherein the interaction instruction is used for triggering interaction between a first agent and a second agent, and the first agent is configured to be used for analyzing a logic structure of a function code of a target function to obtain a structure code of a test point of the target function; the second intelligent agent is configured to be used for generating a target test code based on the structure code of the test point; and displaying the target test code at a preset position to obtain a target test case of the target function. The problem that the generation accuracy of the test case is low can be solved.

The invention relates to an optimization method of a data type conversion operator, computer equipment, a readable storage medium and a computer program product. The method comprises the following steps: allocating memory resources for target data; establishing a read mapping relationship between each logic index in the logic structure of the source data and the memory address of the source data, and establishing a write mapping relationship between each logic index in the logic structure and the memory address of the target data; traversing the logic structure, aiming at any traversed logic index, determining a read address corresponding to the logic index based on the read mapping relationship, performing data reading from the memory resource corresponding to the source data based on the read address, converting the read data element from the first data type to the second data type, and storing the converted data element in the memory resource. And writing the data elements subjected to data type conversion into memory resources corresponding to the target data according to the write mapping relationship. By adopting the method, the calculation capability of the data type conversion operator can be improved.

The invention provides a query statement generation method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the field of computers, the field of databases and the field of deep learning. The query statement generation method comprises the steps of performing intention recognition on a demand text based on business data to obtain a demand intention; in response to the demand intention meeting a preset demand condition, processing the demand intention by using a language model to obtain an execution logic structure, the execution logic structure comprising a plurality of execution logic elements based on structured representation, and a structured relationship among the plurality of execution logic elements representing an execution process of executing the query statement; determining target mode information matched with the text semantics represented by the execution logic element from preset database mode information; performing semantic understanding on the plurality of execution logic elements and the target mode information by utilizing a language model, and outputting a plurality of pieces of intermediate structured data for describing the query statement; and generating a query statement according to the intermediate structured data.

The invention discloses a phishing document de-obfuscation and feature extraction method and an application thereof in attack detection. The de-obfuscation comprises the steps of obtaining an obfuscation macro code of a phishing document, constructing a prompt engineering template by utilizing a pre-training language model, analyzing an obfuscation logic structure and generating a de-obfuscation rule and a reduction strategy; the method comprises the following steps: structuring a confused macro code into an abstract syntax tree through an analysis tool, matching a typical confusion mode based on a regular expression, and performing simulation and cell reference analysis in combination with a function to realize structure preliminary reduction, control flow semantic reduction and operation path construction; according to the unmixing rule and the abstract syntax tree, the confusion structure is converted into a readable macro statement, a macro code instruction sequence with confusion semantics removed is generated, and a semantic sequence obtained after unmixing is output. The feature extraction comprises word feature extraction, Token feature extraction, abstract syntax tree feature extraction and relation feature extraction. According to the method, the bottleneck that traditional phishing attack detection and confusion documents are difficult to recognize is broken through, and the detection accuracy of phishing document attacks is improved.

The invention relates to the technical field of large language models, in particular to an official document content generation and compliance verification system based on a large language model. Comprising an official document extraction module used for analyzing a model essay by using a large language model, extracting a writing style and a fixed sentence pattern, constructing a knowledge graph, storing format specifications, common expressions and logic structures, mining and constructing a core intention library, and storing typical intention prototype vectors; the content generation module is used for generating paragraphs through context sensing, expanding and writing keywords, analyzing behavior data, predicting writing intention vectors and performing condition control; the compliance verification module is used for warning improper words in real time, retrieving policy verification logic and verification formats, and performing pre-verification based on intention vectors; and the writing auxiliary module is used for providing real-time modification suggestions and forward-looking prompts based on writing intention vectors. According to the technical scheme, document writing efficiency and quality can be improved.

The invention relates to the technical field of block chain abnormal behavior detection, in particular to a block chain abnormal smart contract detection method and system based on multi-modal knowledge distillation. The multi-dimensional feature data comprises smart contract source code static logic structure features, smart contract source code dynamic execution state features and smart contract transaction data transaction mode features; and inputting the multi-dimensional feature data into an intelligent contract detection model, and detecting and outputting the abnormal state of the to-be-detected block chain intelligent contract by using the intelligent contract detection model, the intelligent contract detection model performing knowledge distillation by using a teacher-student network model architecture. According to the method, the teacher contract detector is pre-trained by using the multi-source features, so that the student contract detector can still learn transaction behavior knowledge in the absence of transaction data, fraudulent behavior detection is realized in advance, and the detection performance of the abnormal contract is improved by integrating data of different modalities.

The invention discloses an AI-based online homework correction method and system, and the method comprises the steps: carrying out the feature extraction of text content, logic structure and language expression through a multi-dimensional feature extraction model according to the homework data submitted by a student; according to the multi-dimensional feature vectors, a subject knowledge base and logical reasoning rules are combined, and error detection and correction are conducted through a logical reasoning network; according to the homework feature vector, in combination with a teacher scoring standard and a student ability evaluation index, performing scoring and ability analysis by using a dynamic scoring and ability evaluation model; and generating a personalized feedback report by using a generative adversarial network according to a scoring result and a capability evaluation result. According to the embodiment of the invention, various errors in the homework can be efficiently and accurately identified and corrected, personalized feedback is provided, and the quality and effect of online education are improved.

The invention discloses a task disassembling method based on a large model, and aims to automatically disassemble requirements input by a user into a series of independent and accurate minimum sub-tasks so as to support high efficiency and intelligence of task execution. Different from a traditional natural language processing method, the method adopts a large model technology to intelligently analyze and optimize input demand content, so that task description is clearer, and operability is achieved. The method comprises the following steps: firstly, deeply analyzing and adjusting a demand by utilizing the understanding ability of a large model to make the demand accord with a logic structure of task execution; then required core steps and logic levels are extracted through a multi-level task decomposition algorithm, and clear sub-task chains are generated through step-by-step decomposition; by means of the adaptability and dynamic reasoning ability of the large model technology, the decomposition efficiency and accuracy of complex tasks are remarkably improved, the burden of a user in the aspects of task planning and execution is relieved, and efficient and automatic development of intelligent task management is promoted.

The invention relates to a knowledge graph semantic enhanced embedding optimization method based on a dynamic memory network, and belongs to the technical field of knowledge graph logic query questions and answers. Explicit modeling and dynamic updating of a historical logic mode are realized by constructing a structured dynamic memory network; a nested structure and a long-term dependency relationship in complex logic query are effectively captured, the semantic understanding and generalization ability of a model to diversified structure combinations is remarkably improved, basic semantics, logic structures and memory features are dynamically fused, a gated memory updating strategy is introduced, a memory calling path is clear in the reasoning process, and the reasoning efficiency is improved. And the optimization behavior is traceable, so that the interpretability and robustness of the model are enhanced, and the embedding space optimization effect is remarkable and has interpretability. And finally, on the premise that an original upstream encoder does not need to be modified, reasoning enhancement is realized through an external dynamic memory network module, the proportion of updated parameter quantity is small, the calculation overhead is low, and the method is suitable for efficient deployment of various reasoning platforms.

The invention discloses an intelligent text calibration method and system based on a large language model, and is used for solving the technical problem that the accuracy and adaptability of text calibration are poor. According to the intelligent text calibration scheme based on the large language model, through preliminary calibration of parallel processing, the linear mode of a traditional calibration process is broken through, and the calibration efficiency is greatly improved. And the text is comprehensively and meticulously proofread from multiple dimensions such as semantic expression, logic structure and terminology by using the large language model, so that the quality of the text in the professional field can be remarkably improved, the text is ensured to meet the industrial standard and professional requirement, and the accuracy and adaptability of text calibration are improved.

The invention discloses a hydraulic machinery feasibility research report grading review method based on a large language model, comprising the following steps: collecting and analyzing an original hydraulic machinery feasibility research report to generate a logic structure tree and a structured text; based on the logic structure tree, hierarchical gating and strategy scheduling are executed, and gating scheduling data are generated; according to review strategy parameters in the gating scheduling data, executing three-constraint parallel partitioning on the structured text to obtain a sub-document set; utilizing the gating scheduling data to execute auditing adversarial compliance review on each sub-document of the sub-document set to form a preliminary review conclusion set; and aggregating the preliminary review conclusion set, executing cross-subdocument consistency judgment and result summarization, and generating a final review conclusion. According to the method, the compliance problem of the hydraulic machinery research-length document report can be completely and accurately identified.

The invention discloses an intelligent chart generation method and system suitable for multi-modal data and a storage medium, and the method comprises the steps: receiving and preprocessing the multi-modal data, and completing user intention type recognition and task routing; selecting an adaptive model according to a routing result, and constructing and generating a cue word; standardizing an initial graph code output by the model into an intermediate representation format containing a metadata field, converting the intermediate representation format into a graph code compatible with a target platform, and reserving node definition, a connection relation, layout constraint and metadata information; the method comprises the following steps: respectively completing chart type identification and layout strategy determination, node format size adjustment, overall layout alignment correction and partition adjustment, and connection line identifier optimization through four optimization components, and rendering and outputting a chart. The problem that due to the fact that an existing model lacks a special optimizing and processing mechanism for the structured chart, the effect is remarkably poor when a professional schematic chart needing an accurate logic structure and geometric constraints is generated is solved.

The embodiment of the invention provides an MFT system automatic configuration method and system based on an intelligent algorithm, and belongs to the technical field of automatic control. The method comprises the following steps: preprocessing data, and executing value feature and mode extraction; constructing an MFT domain knowledge graph based on the extracted value features and modes, and optimizing a logic structure of an MFT system by using a genetic algorithm based on the MFT domain knowledge graph so as to generate an optimal logic structure by defining a fitness function; based on a reinforcement learning technology and the optimal logic structure, constructing an intelligent decision model by learning historical operation data; and creating a digital twinborn model of the target MFT system based on the intelligent decision model, verifying the configuration of the MFT system based on the digital twinborn model of the target MFT system, and importing the configuration of the MFT system passing the verification into a practical project. According to the scheme, the manual workload and the error probability are remarkably reduced, and high efficiency, intelligence and automation of the MFT system configuration process are achieved.

The invention relates to the technical field of document intelligent review, in particular to a multi-mode digital publishing intelligent review system and method based on a large model, and the system comprises a sample construction module, a multi-mode analysis module, a structure recognition module, a term verification module and an annotation output module. According to the method, a model configuration data set is generated by analyzing a subject-object combination relationship in a text and jointly screening part-of-speech, sentence pattern and semantic structure, the accuracy of semantic recognition and structure judgment is improved, and local features of semantic offset and image-text expression separation are recognized by combining a comparison relationship between an image action path and a text behavior object; a paragraph logic structure and a theme connection mode are analyzed based on semantic offset information, the problems of content dislocation and theme jump between paragraphs are effectively revealed, matching change tracks and part-of-speech continuation fluctuation in term cross-paragraph contexts are recognized, label overlapping and coverage redundancy conditions are analyzed from sentence group hierarchy, and the term cross-paragraph contexts are obtained. And forming a label combination suggestion and constructing an annotation structure record.

The invention belongs to the technical field of software development, and relates to a code generation method and system based on a time sequence driving flow chart. The method comprises the steps that a user side starts a code generator process, generates request information and sends the request information to a code generator; the data server configures each node of the flow chart and the relationship among the nodes, reads the configuration of the flow chart, analyzes the configuration into a syntax tree, and performs association mapping on the syntax tree and the flow chart; the data server generates configuration data; and the code generator reads the request information and the configuration data on the data server, and calls the configuration data to generate a code file. According to the method, the time sequence information and the flow chart are combined, the time sequence relation and the logic structure in the system can be more accurately reflected through the automatically generated codes, the problems that the extraction and search efficiency of the program flow chart is low, time sequence control is lacked, and the semantics of the generated codes are inconsistent are solved, the code generation efficiency and stability are effectively improved, and the method is suitable for popularization and application. And the development requirements of complex systems with high time sequence requirements are met.

The invention discloses an electrical drawing security collaborative management method, system and device based on a cloud computing technology and a medium. The method comprises the steps that an initial key is generated through a quantum key distribution device, the key is divided into a plurality of sub-blocks, and a dynamic session key is generated; encrypting data blocks divided by the electrical drawing file according to the logic structure through the dynamic session key, and transmitting the encrypted data blocks to a cloud computing platform for storage; generating a temporary key to encrypt the modified content, adding a digital signature and position information, and combining the modified content after the cloud verifies the signature to generate a new electrical drawing; synchronizing the new electrical drawing full-text security operation credential update record to the block chain, and verifying the consistency of the data on the chain and the cloud drawing version; and splitting the dynamic session key into a plurality of fragments and storing the fragments in different cloud nodes. According to the invention, safe transmission, efficient collaborative management and accurate data tracing of the electrical drawings are realized, and the safety, reliability and efficiency of full-life-cycle management of the electrical drawings are remarkably improved.