249 results about "GiST" patented technology

The invention discloses an intelligent bid evaluation method and system based on a large model, and a related product, relates to the technical field of purchase bid evaluation systems, and solves the problems that an existing intelligent bid evaluation system is difficult to understand a complex logical relationship and semantic connotation and cannot provide a comprehensive and accurate scoring result. According to the technical scheme, the method comprises the steps that S1, bidding and tendering files are obtained; s2, performing disassembly processing based on the bidding and tendering file to obtain a plurality of bidding and tendering data pairs; s3, performing instruction construction on the bidding and tendering data pair based on a historical bidding and tendering database to obtain a prompt instruction of the bidding and tendering data pair; s4, processing the prompt instruction of the bidding and tendering data pair based on the large model after training and fine tuning to obtain the score of the bidding and tendering data pair, and accumulating the scores to obtain the score of the bidding file; through the method based on the large model, the scoring effect is effectively improved in the intelligent bid evaluation work, the efficiency is improved, manpower and material resources are saved, and meanwhile interference caused by human factors is avoided.

The invention discloses a corrugated carton production management system and method, and relates to the technical field of corrugated carton production, the system comprises a production scheduling module, a material tracing module, an equipment cooperation module, a multi-mode detection module and a cost control module, and solves the problem that supply and demand relationships, production efficiency and quality management and control are not coordinated; according to the technical key points, an order ID is coded into an integer chromosome, sequential crossover and reverse mutation operation are applied, a fuzzy comprehensive evaluation model is constructed by combining Hash chain table and local hill climbing method optimization, and factors are quantified through a trapezoidal membership function, so that the order delivery punctuality rate and the equipment utilization rate are improved, and the mold replacement cost is reduced; the real-time production cost is collected and calculated through Kafka and Flink, an operation cost method model is constructed to maintain a standard cost database, abnormity is detected through a CEP engine, the cost hyper-branched risk is predicted through an LSTM-Transform hybrid neural network, a thermodynamic diagram is generated through a cache result to assist decision making, the cost accounting delay time is shortened, and the hyper-branched processing efficiency is improved.

The invention discloses a method and system for independent application of multi-modal data after fusion and archiving, and relates to the technical field of archive management. The technical key points are as follows: establishing a service management platform, including a user group and an archive group, managing the user group and the archive group, defining an archive as a node by adopting a chain network structure, starting archiving management, generating an archiving package, and performing independent application between nodes, so that a user can quickly retrieve and position the archive; effective interaction between data is realized to a certain extent; state data of an archiving packet is processed through a target decision network, an archiving score is calculated, a corresponding archiving interval is matched according to the archiving score, different calling levels are correspondingly set, different users are endowed with corresponding permissions for management, and the whole system judges the management quality by designing evaluation factors, so that the management efficiency is improved. And the management efficiency is further improved.

The invention relates to a data lake-based industry templated modeling and dynamic access control method, which comprises the following steps of: acquiring multi-source heterogeneous data of a data center in real time, and performing data verification, key field extraction and metadata extraction through an analyzer; according to the data classification and grading key points, grading protection is carried out on the currently obtained data matching industry grading and classification template, and the protection grade is dynamically adjusted according to the data dynamic access control rule, the sensitivity and the service importance; performing threat detection and risk prediction on the abnormal behavior data by using a machine learning algorithm; constructing a distributed intelligent data lake storage architecture, and storing the currently acquired data into a data lake in a layered manner according to a classification result; and displaying the security situation and the early warning information through a visual interface. The invention also relates to a corresponding system. By adopting the industry templated modeling and dynamic access control method and system based on the data lake, the limitation of traditional data lake modeling is effectively solved.

The invention provides a self-adaptive data extraction method and device based on multi-level dynamic sampling, and relates to the technical field of data extraction analysis, and the key points of the technical scheme are that the method comprises the following steps: obtaining operation parameters and system resource use state information of a plurality of blast furnaces; the blast furnace monitoring parameters are divided into a high-frequency sampling layer, a conventional sampling layer and a low-frequency sampling layer according to the operation parameters; calculating a blast furnace abnormal state index and a resource utilization rate based on the operation parameters; executing cross-furnace data association analysis, and calculating a cross-furnace association degree; dynamically adjusting the sampling frequency of each sampling layer according to the abnormal state index, the resource utilization rate and the cross-furnace correlation degree; based on the resource use state information and the data importance, carrying out adaptive compression processing on the collected data; and converting the compressed heterogeneous data into a uniform data format. The adaptive data extraction method and device based on multi-level dynamic sampling provided by the invention have the advantage of improving the extraction efficiency and quality.

To provide a system that extracts useful information from text data and efficiently performs translation and information retrieval between multiple languages.SOLUTION: A system according to the embodiment comprises an analysis unit, an extraction unit, a translation unit, an information search unit, and a provision unit. The analysis unit extracts information from text data, and performs topic modeling and emotion analysis. The extraction unit summarizes the information extracted by the analysis unit, and extracts main points. The translation unit translates the text data extracted by the extraction unit between multiple languages. The information search unit searches for and acquires the text data translated by the translation unit in response to input from a user. The provision unit provides the information acquired by the information search unit.SELECTED DRAWING: Figure 1

The invention discloses an artificial intelligence model traceability and tamper-proofing method and system based on block chain enhancement, and relates to the technical field of artificial intelligence model traceability and tamper-proofing. According to the technical key points, the method comprises the following steps: carrying out simulation attack by utilizing penetration testing to obtain multi-type data containing security vulnerability data; preprocessing the multi-type data; constructing an anomaly detection and attack recognition model based on a variable parameter neural network, and training the anomaly detection and attack recognition model based on the preprocessed data; performing Merkle tree encryption on the preprocessed data and model parameters obtained by training, encoding model prediction output, embedding the encoded model prediction output into a Merkle tree structure, and completing recording on a block chain through an intelligent contract; and for a to-be-evaluated artificial intelligence model, calling the global root hash value on the block chain for verification. According to the invention, the whole process of the artificial intelligence model from data acquisition to reasoning output is verifiable, traceable and tamper-proof.

The invention provides an electronic medical record connotation quality control method and system based on a large language model, and the method comprises the steps: carrying out the modal classification of a whole-process medical record of a patient, and uniformly converting the whole-process medical record into a corresponding text modal; performing hierarchical division on the whole-process medical record of the text mode to form a medical record content tree; according to different nodes of the medical record content tree, retrieving a quality control rule set corresponding to the nodes of the medical record content tree, and retrieving a corresponding diagnosis and treatment knowledge set; for each quality control rule in the quality control rule set, if a plurality of medical record content tree nodes are needed, establishing a corresponding context set, constructing a quality control cue word list, inputting cue words into the connotation quality control big language model, judging whether a quality control problem exists in the cue words or not by the connotation quality control big language model, and proposing a modification suggestion; and checking and revising the output result to obtain a final quality control result. According to the method, key point missing, description conflicts and deep diagnosis and treatment logic contradictions in medical records can be recognized and corrected, and the accuracy and stability of quality control results are improved.

The invention discloses a safe evacuation path planning method under a strong wind condition of island engineering. According to the technical scheme, the method is characterized by comprising the steps that firstly, the physical space of an engineering site is discretized into a plurality of grid units, and a computable graph structure is constructed; then, acquiring multi-source dangerous area information generated in real time, and quantifying the dangerous area information into a dynamic risk value of each grid unit; then, acquiring the real-time position of the constructor as a starting point, and presetting an emergency exit as an ending point; and finally, on the constructed risk grid map, a heuristic search algorithm such as A * is adopted, and the geometric distance and the dynamic risk value between grid units are fused by a cost function of the heuristic search algorithm, so that an optimal evacuation path considering safety and efficiency is quickly searched. According to the method, the safety risk is quantified and fused into the path optimization process, so that the quick response to the dynamic environment and the real-time re-planning of the path are realized, and the efficiency and safety of personnel evacuation under the emergency condition are remarkably improved.

The invention provides a joint retrieval method and system based on knowledge enhancement, a medium and a terminal, and ensures that a retrieval result is not limited to text segments with similar literal surfaces through a structured knowledge base, a domain label knowledge base and a multi-source heterogeneous knowledge graph. And instead, an organic knowledge whole integrating direct clauses, related law articles, judgment key items and internal rules is formed, so that the generated reply has a rigorous legal basis and a complete business context, and claim settlement disputes and legal risks caused by lack of key knowledge association are reduced. And the compliance control is changed from lagging manual inspection to real-time beforehand system built-in, so that the compliance vacuum period caused by policy update lagging is reduced, and the supervision punishment and reputation risk of an enterprise is reduced. The historical versions are reserved, and the version replacement chain is established, so that explanation based on historical contexts is provided for insurance policy life cycle query crossing different time points, and the credibility and accuracy of customer services are enhanced.

The invention discloses a similarity and distance calculation system and method based on an R language, and relates to the technical field of data processing, and the key point of the technical scheme is that the system comprises the following modules: a data reading module, a data standardization module, a similarity calculation module and an error checking module. Through automatic data inspection, standardized processing and efficient similarity calculation, the user can easily perform complex similarity analysis. The method has a wide prospect in the application of big data analysis, machine learning and the like, a more convenient and more accurate similarity calculation scheme can be provided for a user, and the data processing and analysis efficiency is greatly improved.

The invention discloses a book data processing and intelligent service system based on artificial intelligence, and relates to the technical field of artificial intelligence and digital library crossing, and the technical scheme is characterized in that a multi-format document intelligent conversion and regular cleaning mechanism is adopted, a multi-level metadata extraction algorithm is combined, and a structured knowledge base is accurately constructed; vector semantic retrieval, BM25 keyword retrieval and a cross encoder reordering model are creatively fused, and high-precision context retrieval is achieved through dynamic weight configuration and locality sensitive hash de-duplication. A parallel data processing architecture supporting GPU acceleration is constructed based on a Chroma vector database, the knowledge response capability of a local large model is enhanced in combination with an RAG technology, and verifiable standardized content is generated. The system is compatible with a Linux / Windows platform and containerized deployment, has hundred million-level data throughput efficiency, can be widely applied to the fields of intelligent libraries, knowledge questions and answers and personalized recommendation, and remarkably improves the retrieval accuracy of book data and the intellectualization level of knowledge services.

The invention discloses a sintering batching optimization scheme, and relates to the technical field of sintering ore batching control, and the technical key points are as follows: a random forest proxy model is used to predict the performance of finished ore, and a nonlinear mapping relationship between an independent variable and a dependent variable is used as a target function; carrying out Pareto optimal solution set search through non-dominated sorting and crowding distance calculation by adopting an NSGA-II (Non-dominated Sorting Genetic Algorithm-II) algorithm; calculating the weight of each target index by using an entropy weight method based on a Pareto solution set; weight is determined from a Pareto solution set generated by an NSGA-II algorithm, an optimal batching scheme closest to an ideal solution and far away from a negative ideal solution is screened out through a TOPSIS method, and multi-target comprehensive weighing is achieved; according to the method, sintering batching optimization based on finished ore performance feedback is realized, dynamic optimization of a batching plan can be effectively guided, the sinter quality control level is improved, the production cost is reduced, and technical support is provided for efficient and stable operation of a blast furnace ironmaking process.

The invention discloses an overlapping community detection method, system and device and a medium, and particularly relates to the technical field of community detection, and the technical key points are as follows: extracting node information data from a pre-constructed adjacent matrix of an overlapping community, and inputting the node information data into a point mutual information function to calculate and obtain point mutual information; obtaining a superpoint mutual information matrix by combining the point mutual information with the hypergraph structure; constructing a target function by using the super-point mutual information matrix and a pre-constructed three-factor illegal matrix decomposition optimization model based on graph regularization; decomposing the super-point mutual information matrix in the objective function to obtain an indication matrix, and solving the indication matrix by using an alternating iteration method to obtain an optimal solution of the indication matrix; and detecting the overlapping community based on the optimal solution of the indication matrix to obtain an overlapping community detection result.

The embodiment of the invention provides a language processing model training method and device and a question processing method and device.The language processing model training method comprises the steps that a target text is determined, and a text question corresponding to the target text is generated; generating a prompt text from the target text, the text question corresponding to the target text and the text key point, and inputting the prompt text into an initial language processing model to obtain the text key point corresponding to the text question; according to the target text, the text question corresponding to the target text and the text key point corresponding to the text question, constructing text training data; and training the initial language processing model according to the text training data to obtain a target language processing model. Under the guidance of the text problem, the text key points strongly related to the text problem are generated through the large language model, and model fine tuning iteration is performed, so that the efficiency and accuracy of subsequent search of the large language model according to the input problem are enhanced.

The invention provides a confidence evaluation method and device, electronic equipment and a storage medium. The method comprises the steps that key information and semantic features of a query instruction are accurately captured by query features; the search result features comprehensively represent the core key points and the text features of the document; semantic difference features are determined based on the semantic difference between the query instruction and the search result, text difference features are determined based on the text difference between the query instruction and the search result, and the internal relation between the query instruction and the search result in the semantic and text level is deeply mined; the query features, the search result features, the semantic difference features and the text difference features can comprehensively reflect the matching degree and quality information of the query instruction and the search result, so that confidence coefficient prediction is performed based on the query features, the search result features, the semantic difference features and the text difference features to obtain a confidence coefficient score result; the performance of the RAG retrieval module can be efficiently evaluated, and dependence on external reference data and a complex large language model is got rid of.

The invention provides a text information correction method and device, equipment and a medium. A specific implementation mode of the method comprises the steps of obtaining original text information to be processed; generating a query statement based on the original text information; the query statement is used for searching for retrieval key points involved in the original text information; searching from specified data based on the query statement to obtain reference information related to the retrieval key point; evaluating the consistency of the reference information and the retrieval key points; and correcting the original text information based on an evaluation result. According to the implementation mode, the original text information machine does not need to be manually debugged, so that the content which may have errors in the original text information can be quickly and accurately checked out, convenience is provided for a user, and the user experience is improved.

The invention relates to the technical field of document management, and relates to a legal document key point automatic extraction and association method and system.The new legal document data of a target case is obtained, a preset document fingerprint algorithm is used for automatically comparing the new legal document data with a historical reference document, differential text data fragments are extracted, and the text data fragments are extracted; the method comprises the following steps of: performing deep semantic analysis on different text data fragments to generate candidate triple data containing entities and relationships, intelligently mapping the candidate triple data into a pre-constructed case knowledge graph, quickly positioning graph anchor nodes with data change, and then, performing data change on the basis of change types of the different text data fragments. And executing atomic updating operation on the map anchor node, including updating the dynamic mark of the node state attribute, and finally generating the change source node data with the latest state identifier. The problems that the current legal case data updating depends on manpower, is low in efficiency and is easy to make mistakes are effectively solved.

The invention discloses an electric power data service-oriented multi-source data tracing method, which is characterized by comprising the following steps of automatic analysis, acquisition of electric power data tracing information, system tracking, mark tracking of various electric power data, machine learning and improvement of the analysis processing capability of the electric power data. Therefore, the related power traceability information can be accurately obtained by analyzing various power basic data, and then the identifier corresponding to the traceability information of the data is added to the data by adding the corresponding log or annotation in the data processing program, so that the tracking of the data flow direction is realized; and a machine can quickly identify the data and the traceability information thereof in subsequent machine learning, and the similarity and dependency relationship among the data are calculated according to the identifiers of the data, so that the traceability speed and accuracy of various power data can be continuously improved.

The invention discloses an Internet of Things intrusion detection method based on a Transform and GNN hybrid model, a model, a training method of the model and electronic equipment, belongs to the technical field of deep learning, and aims at solving the problem that statistical characteristics, time sequence characteristics and topological characteristics of traffic are learned at the same time to utilize network space characteristics for Internet of Things intrusion detection. The method is characterized by comprising the following steps of: carrying out position coding on network flow data in the Internet of Things, inputting the network flow data into an encoder of a Transform model, and outputting a first embedding embedding vector; the network flow is converted into a first graph, the host is a node of the first graph, and the network flow is an edge of the first graph; the first graph is converted into a second graph through a Line Graph model, the network flow is a node of the second graph, and the relation between the host pairs is an edge of the second graph; inputting the second graph into the GNN model, and outputting a second embedding embedding vector; and splicing the first embedding embedding vector and the second embedding embedding vector to obtain a spliced vector, inputting the spliced vector into a classifier, and outputting an Internet of Things intrusion detection result by the classifier, so that topological information can be captured, and relevance between different flows can be captured.

The invention discloses a cost data management system based on electric power construction, and relates to the field of data management, and the key points of the technical scheme are that a data acquisition and preprocessing module is used for acquiring comprehensive cost data in a cycle time, and preprocessing the comprehensive cost data by using a rule map to obtain standard cost data; the data combination and reconstruction module is used for carrying out combination and reconstruction on the standard cost data to obtain a time-class data packet; the curve fitting module uses a curve fitting model to carry out curve expression on the time class data packet, a standard curve set is obtained, trend analysis is carried out on the standard curve set, and comprehensive evaluation data is obtained based on the comprehensive set; the cost analysis and decision-making module constructs a cost function based on the comprehensive evaluation data, and determines distribution funds of each data category; and the visual output module carries out visual display based on the distribution fund of each data category, so that high-quality management of the cost data in the electric power construction process is realized.

The invention discloses a regional load prediction method, system, equipment and medium, and particularly relates to the technical field of power load prediction, and the technical key points are as follows: a plurality of load nodes are clustered in sequence according to weather data, population flow data and urban power consumption characteristics by using a third-order clustering analysis method to obtain a tree-type clustering cluster topological structure; a representative load node is selected from each cluster subset, average correlation coefficients between influence features in weather data of each representative load node and load data are calculated, and the influence features of the first three maximum average correlation coefficients are selected as influence input features of the representative load node; performing modal decomposition on the load data representing the load nodes by using an EMD decomposition method to obtain a plurality of connotation modal components and residual terms; and inputting the influence input feature of each representative load node and the plurality of decomposed connotation mode components into a load prediction model to obtain a load prediction result corresponding to each representative load node.

1. The name of the design product: A search input bar, an option bar and a display portion of a graphical user interface for search input and display of an electronic device. 2. Purpose of the product of this design: an electronic device. 3. The key design features of this design product are the contents requiring protection in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of Graphical User Interface: The overall graphical user interface is an interface that combines the central display area with the upper and lower input areas to facilitate users to search and select more content. The local part of the interface is the search input bar, option bar and display part of the graphical user interface. The user enters the search content in the runway-shaped search bar at the upper part of the interface. The user clicks the option bar with pointed corners under the upper runway-shaped search bar to select the search type. The search results are displayed in the central approximately rectangular area. The pointed runway-shaped search bar on the bottom left side of the dot matrix area in the middle of the interface can be used by the user for additional search input. 6. Other situations that need to be explained Other explanations: The dotted part in the figure is the content that is not requested to be protected, and the specific meaning of the text in the interface is not requested to be protected; the solid line content and the dot matrix area are the content that is requested to be protected in the interface.

1. Name of the product of this design: A search dialog box and display unit of a graphical user interface for searching information of an electronic device. 2. Purpose of the product of this design: an electronic device. 3. The key design features of this design product are the part of the graphical user interface for which protection is requested. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of the graphical user interface: The interface is divided into three areas, which are used to provide users with a search input bar and display search results. When users want to further search for a certain content, they can enter the search question through the search dialog in the interface, or click to select the commonly used questions in the middle of the interface to search. Users can also click the function buttons at the bottom of the interface to reserve or purchase related products that users searched for. Local uses of the interface: the runway-shaped box with pointed corners at the top of the interface is a search dialog box, and the text in the dialog box is the content entered and searched by the user; the runway-shaped box with pointed corners in the middle of the interface is common search questions generated by artificial intelligence, and the user can click on one of the dialog boxes to select the content they want to search from these listed questions and start further search; the picture box in the middle of the interface displays product content related to the user's search, and the user can browse related content by clicking on the picture box; the runway-shaped box with a right arrow icon at the bottom of the interface is the "Book Now" function button, and the user clicks this button to book or purchase the related products the user searched for. 6. Other situations that need to be explained Other explanations: The dotted part in the figure is the content that is not requested for protection, and the solid line part and dot matrix area in the interface are the content that the interface is requested to protect.

The invention discloses an engineering document generation method and system based on a logic structure tree and LLM and a medium. The method comprises the steps that original data are analyzed to form an initial text segment set X; calling LLM to generate an initial technical draft based on X, extracting a logic structure, and constructing an initial logic structure tree T; maintaining a search queue, for leaf nodes in the queue, acquiring context information related to semantics from X through a retrieval enhancement mechanism, after same-level brother node deduplication and global deduplication judgment, calling LLM to expand the nodes to generate child nodes, optimizing text description, and recursively enriching a tree structure; and finally, based on the X and the optimized tree, calling LLM to generate a title, an abstract and a background, generating content, details and key point chapters through traversal, and combining into a complete engineering document. The system comprises a document analysis module, a knowledge base module, a retrieval enhancement module, a logic structure tree maintenance module and a document generation module. The method is high in automation degree, and the generated document is clear in structure, complete in content and high in specialty.

The invention discloses a ground monitoring data identification and association method, system and device, and a storage medium, and the key points of the technical scheme are that the method comprises the steps: receiving the current monitoring data of a current object and the identification data of a to-be-associated object; encoding the current object according to a preset encoding scheme and the current monitoring data to obtain an identifier of the current object; determining an identifier of the to-be-associated object according to the identification data of the to-be-associated object; and according to the identifier of the current object and the identifier of the to-be-associated object, establishing an association relationship between the current object and the to-be-associated object. Unification and association of the same objects in different monitoring tasks are ensured, and dynamic monitoring of the objects is facilitated.

The invention discloses a document generation method and device based on multi-agent collaboration and a medium, and relates to the technical field of artificial intelligence. The method comprises the steps of receiving a natural language research theme input by a user; inputting the research theme into a preset planning agent to generate a keyword set for executing network search according to the research theme; inputting the keyword set into a preset search agent, and executing a plurality of times of network search by utilizing a network search tool to obtain a plurality of key point type abstracts; and inputting the research theme and the plurality of key point type abstracts into a writing agent to generate a structured research report, and outputting the structured research report to a user interface.

The invention discloses a power grid basic data knowledge graph construction method, and the key points of the technical scheme are that data collection is used for obtaining various types of required power basic data, data cleaning is used for carrying out the preprocessing and knowledge extraction of the collected data, and the knowledge graph is obtained; and the data processing module is used for identifying concepts, entities, attributes and relationships in the power field from the preprocessed data and converting the concepts, entities, attributes and relationships into triads or knowledge representations in other standard formats, so that various power basic data can be cleaned, and then knowledge extraction and fusion can be performed on the preprocessed and cleaned data to obtain the data. According to the method, optimized data can be extracted to the greatest extent, the data capacity is reduced, the data redundancy is reduced, and the consistency and reliability of the data are improved, so that the formed knowledge graph has extremely high practicability and reliability, and various power basic data can be fully and effectively processed; and therefore, the value of various electric power basic data can be completely exerted.

The invention provides a full-life-cycle digital asset management system. According to the technical scheme, the full-life-cycle digital asset management system is characterized by comprising a meta-model management module, a data source management module, a metadata management module, a data architecture design module, a data management module, a data product management module and a data asset management module; wherein the data management module comprises a data standard management module and a data quality management module; wherein the meta-model management module is connected with the metadata management module; the data source management module is interactively connected with the metadata management module, and the data source management module is also interactively connected with an external data source; the data management module is in interactive connection with the metadata management module, the data architecture design module, the data product management module and the data asset management module. According to the application, a layered modular architecture is adopted, and an automatic process from data modeling to capitalized operation is realized through a full-life-cycle management mechanism driven by a meta-model.

The invention relates to the field of park power management, and discloses a park power intelligent management method and system, and the key points of the technical scheme are that S1, a full-dimensional collection network is constructed, and data collection is carried out; s2, carrying out preprocessing and tagging processing on the collected data, and constructing a data association network; s3, based on the data association network, screening key data objects, integrating historical power data, environmental data and associated data, and training an intelligent prediction model group by adopting a machine learning algorithm; s4, performing real-time monitoring on a data object by using the intelligent prediction model group, and identifying power operation abnormity through dynamic threshold setting, real-time data comparison and abnormity type judgment; s5, performing graded early warning according to the abnormal type and severity; s6, performing intelligent fault diagnosis on the abnormal data object, generating a disposal scheme and tracking a disposal process; and S7, optimizing the data association network, the prediction model and the early warning response flow according to the application result of the intelligent prediction model group.