105 results about "Information field" patented technology

The invention discloses an AI-based large-model-driven contract review and regulation interpretation method and system, and the method comprises the steps: S1, collecting a regulation and institute document, and carrying out the text extraction and semantic disassembly, and obtaining term information; s2, based on a LawCheckLM + BERT-CRF named entity recognition model, performing entity recognition and classification labeling on clause information, and storing recognized key information fields into a knowledge base; s3, encoding each piece of clause information into a semantic vector through an embedded model, and storing the semantic vector into a knowledge base; and S4, performing text extraction and semantic disassembly on the uploaded contract document to obtain clause information, repeating the steps S2-S3, retrieving similar semantic vectors of laws and regulations or institutional documents similar to the contract from the knowledge base as references, if the similar semantic vectors are not retrieved, taking Top-N laws and regulations or institutional documents with similar semantics as outputs, and marking the Top-N laws and regulations or institutional documents as required to be examined. The problems that an existing management system is difficult to adapt to regulation changes, complex contract review and cross-scene deployment are achieved, and the overall iteration period is long are solved.

The invention relates to the technical field of data reasoning, and discloses a ludisia discolor harvest time prediction method and system fused with multi-source data, and the method comprises the steps: converging meteorological elements of ludisia discolor, soil profile physicochemical indexes and plant body physiological signals, and obtaining a time-space synchronization multi-dimensional information field; identifying a critical point of fundamental transformation of a growth mode in ludisia discolor, and dividing a complete growth cycle into multiple phenological stages; dimensionality reduction is carried out on the multi-dimensional data of the multi-phenological stage, tensor synthesis is carried out on the situation characteristics of the result after dimensionality reduction, and a growth situation vector is obtained; establishing a contribution degree quantification system, and endowing the growth situation vector with a contribution degree weight; correcting the growth situation vector, arranging corrected results according to a time sequence, and regarding the corrected results as a full life cycle development trajectory to deduce a physiological maturity path; when the physiological maturity path reaches a historical optimal quality convergence interval of ludisia discolor, determining an optimal harvesting window; the method can improve the prediction accuracy of the ludisia discolor harvesting time.

The invention provides a data privacy protection method and system for a large model knowledge base, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining original privacy data of each participant, carrying out the cleaning and feature extraction of the original privacy data, and recognizing sensitive information fields; performing desensitization processing on the fields containing the sensitive information by utilizing a generative adversarial network to obtain desensitized data; and performing k-anonymization processing on the desensitized data, dividing the data into a plurality of equivalence classes based on the quasi-identifier, and performing generalization processing on the classes with the record number less than k to obtain an anonymized data set. According to the method, the privacy leakage problem of multi-participant data collaboration in large model training is solved.

The invention discloses an oil pipeline monitoring method and system based on spatio-temporal modeling and multi-dimensional analysis, and belongs to the technical field of oil and gas pipeline safety monitoring, data processing and intelligent prediction.The method comprises the steps that multi-source spatio-temporal data is collected to construct a probability generation model; performing inversion on the model by using the observation value to reconstruct four-dimensional posterior probability distribution; performing causal inference on the posterior probability distribution to generate a dynamic causal information flow map; and analyzing topological evolution of the atlas to generate a stability monitoring report. According to the method, a technical path of combining probability modeling based on an information field theory and causal dynamics inversion is adopted, and accurate prediction of a systematic risk critical transition precursor can be realized by reconstructing a pipeline holographic state field and analyzing topological evolution of a causal network of the pipeline holographic state field; and the operation safety and the intelligent monitoring level of the long-distance oil pipeline are obviously improved.

The application provides a power line icing simulation and prediction method based on data assimilation and artificial intelligence, comprising the following steps: step 1, meteorological elements affecting power line icing generation are predicted; step 2, the initial field of the meteorological mode prediction is adjusted, and the result of the numerical mode prediction in step 1 is optimized; step 3, the result of the numerical mode prediction after the optimization in step 2 is subjected to bias correction processing; step 4, whether icing is generated is determined, and the geographical position where power line icing is likely to occur is marked to form icing spatial distribution information field of the concerned area; and step 5, the warning result of the regional icing thickness is output. The application uses an artificial intelligence integrated constraint model to correct the meteorological prediction data field, obtains corrected meteorological information, calculates the icing spatial distribution field by using a mathematical method, and outputs the icing thickness prediction result, thereby assisting in solving the power line icing warning problem.

The invention relates to a data-in-channel-based cross-source data joint query method, which comprises the following steps of: S1, constructing a data-in-channel access strategy model, and automatically generating a most suitable access mode; s2, constructing a power data knowledge graph, and analyzing a dependency relationship, a traceability path and a blood relationship among the data by using a graph neural network; s3, seamless access is achieved through natural language understanding, natural language query translation is adopted, and the natural language query of the user is converted into a corresponding SQL statement; s4, according to the SQL statements, similarity is calculated through the embedded vectors, user problems and data models are matched, and according to historical query modes and service requirements, a virtual data view is generated; s5, based on the generated virtual data view, sensitive information fields possibly contained in the data set are recognized through a natural language model and regular pattern recognition, and automatic labeling and classification are carried out. According to the method, the technical threshold of data fusion and sharing is remarkably reduced, and the intelligence of a data platform system in the power industry is improved.

The invention discloses an automobile seat motor intelligent sliding rail adjusting system based on AI voice interaction, and the system comprises the following modules: a local voice wake-up module which is used for monitoring the voice input of a user, and activating a voice recognition module after detecting a preset wake-up keyword; the voice recognition module is used for generating a standardized text instruction; the semantic modeling module is used for executing word vector modeling processing on the standardized text instruction; the control parameter mapping module is used for inputting the semantic feature vector into a trained neural network model; the slide rail state detection module is used for collecting slide rail state information in real time; the voice synthesis module is used for converting the content in the prompt information field into a voice output content template; the vehicle-mounted audio output module is used for generating broadcast content; and the voice interaction log module is used for recording information involved in the voice interaction process. Semantic modeling and control mapping are fused, and the intelligent voice-driven seat adjusting system is constructed.

The invention provides a multi-modal sensitive information processing method and system for science and technology intelligence, and relates to the technical field of science and technology intelligence processing, and the method comprises the steps: obtaining a multi-modal information set of texts, images, audios and the like in the field of science and technology intelligence, carrying out the cross-modal sensitive clue symbiotic modeling operation on the multi-modal information set, and forming a sensitive clue symbiotic network. The method comprises the following steps: obtaining a cross-modal sensitive clue symbiotic set, constructing a dynamic self-optimization processing rule based on the cross-modal sensitive clue symbiotic set in combination with scene requirements and historical processing effect data, executing multi-modal cooperative processing operation on an information unit according to the self-optimization processing rule, recording processing process data, and performing multi-modal cooperative processing on the information unit. And finally, the co-processed information set, the processing process record data and a rule updating log are stored in an associated mode, the updating log comprises rule updating time, basis and content, and efficient and accurate processing of the science and technology intelligence multi-mode sensitive information is achieved.

The invention is applicable to the technical field of artificial intelligence, and provides an artificial intelligence-based voucher attachment processing method, which comprises the following steps of: acquiring voucher attachments and corresponding context information, and performing preprocessing operation according to the quality and the type of the voucher attachments; inputting the preprocessed voucher attachment and the context information into a preset attachment information fusion model, and outputting a structured understanding result; generating an information extraction instruction set according to the structured understanding result, and extracting a voucher information field according to the information extraction instruction set; based on a preset enterprise knowledge graph, performing intelligent auditing on the voucher information field to generate an auditing result; and analyzing the audit result, and generating a voucher attachment processing report in combination with context information. According to the invention, intelligent information identification and analysis of the voucher attachment are realized, so that financial management of an enterprise is facilitated.

The invention discloses a method for seamlessly handling business in an interactive interface, a medium and equipment. The method comprises the following steps: receiving a user business request and loading a business rule containing a process state machine; guiding a user to input information according to the current process stage, and dynamically generating a structured confirmation component after real-time verification; monitoring user confirmation operation to form a confirmed information unit; inquiring a process state machine based on the confirmed information unit to judge a stage transition condition, and executing interface reconstruction operation when the condition is met; and when the final stage is reached and all necessary information fields are confirmed, automatically packaging and submitting a complete data request packet, and displaying a handling result on the same interface. According to the method, the problem of flow interruption caused by multi-interface jump in traditional business handling is solved, the continuity of user operation and the interface consistency are ensured through state machine driving and dynamic interface reconstruction, and the business handling efficiency and the user experience are remarkably improved.

The invention relates to the technical field of artificial intelligence, and discloses an information auditing method and device, equipment and a medium, and the method comprises the steps: obtaining inquiry sheet information of a user, and carrying out the entity recognition of the inquiry sheet information through a natural language model, and obtaining an information field set; verifying the information field combination through a preset attribution rule and a preset logic verification condition to obtain a field compliance verification result; wherein the preset attribution rule is a preset rule based on business difference; the preset logic verification condition is a condition preset based on a field consistency relationship; if the field compliance verification result is that verification fails, performing inference analysis on the information field combination through a large model, and generating corrected inquiry sheet information; and analyzing the corrected inquiry sheet information through a risk assessment model to generate an audit result list. The information auditing method and device can be applied to a financial science and technology business program system, and the information auditing efficiency and accuracy can be improved.

The invention relates to the technical field of artificial intelligence, in particular to a multi-modal data knowledge extraction method based on an intelligent traffic large model, which comprises the following steps of: comprehensively collecting and marking multi-modal traffic data to provide a rich information basis for subsequent analysis; multi-modal data are converted into high-dimensional vectors by using a super-dimensional calculation method, potential features among the data are effectively mined, and fusion of the multi-modal traffic data is promoted; a multi-modal knowledge entity space is constructed based on an information field theory, and effective fusion of different modal traffic data is realized; a risk behavior mode is identified by constructing a risk potential function, so that the risk prediction capability of traffic management is improved; personalized factors of a driver and a vehicle are analyzed by using a fractal geometry method, and a basis is provided for formulating a traffic management strategy; and according to the associated risk behavior mode and the personalized factors, performing intensity grading processing so as to take prevention measures. The technical problem that the traffic management effect is poor is solved.

The application relates to an inventory determination method and device, computer equipment and a storage medium. The method comprises the following steps: determining an inventory parameter corresponding to a target bill, and converting the target bill into an inventory model object comprising a plurality of information fields when the inventory parameter represents that inventory updating is started; determining an initial master table and an initial slave table corresponding to the inventory model object, and then performing inventory updating on the initial master table according to the inventory parameter to obtain a target master table, so that inventory updating can be performed on the initial slave table according to the target master table and the plurality of information fields to obtain a target slave table. The method can improve the efficiency of inventory determination.

The invention discloses a configuration determination method, a capability reporting method and a period configuration method, and relates to the field of communication. The method comprises: receiving a first DCI, the first DCI comprising a first information domain and a second information domain, the first information domain and the second information domain being used for determining a first period configuration; wherein the UE is configured with N sets of period configurations, the N sets of period configurations comprise the first period configuration, and N is an integer greater than 1. And the first period configuration is determined through the first information domain and the second information domain of the first DCI. Compared with a method that only one information domain is used for determining the first period configuration, the method has the advantages that due to the fact that the two information domains comprise more bits, determination of more sets of period configuration can be accurately and efficiently achieved, and higher flexibility is achieved when the period configuration is determined.

A medical image processing method, program product, readable storage medium, and computer system are disclosed. The medical image processing method processes a medical image at a medical image device, characterized in that the method includes the following steps: an operation extraction step, which performs a hash operation on medical image data obtained using an imaging system to obtain a hash value and extracts a data packet included in the medical image data; a generation step, which generates the hash value and the data packet obtained in the operation extraction step as request data; a transmission step, which transmits the request data generated in the generation step to an authentication server for time stamp authentication; a reception step, which receives data authenticated using the time stamp authentication from the authentication server; and a writing step, which writes the authenticated data received in the reception step to a designated information field of the medical image.

The invention provides a defect report completion and optimization method and system based on multi-agent cooperation, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining an original defect report; the completion and optimization task of the original defect report is decoupled into three sequentially executed sub-tasks of defect analysis, report completion and quality evaluation; analyzing the input original defect report through an analysis agent, identifying missing key information fields in the original defect report, and generating a complementation suggestion based on the retrieved external knowledge; a completion suggestion output by defect analysis is received through a completion agent, and missing content in the original defect report is generated and completed based on the completion suggestion to obtain a completed report; and evaluating the quality of the completed report through the evaluation agent. A defect report processing flow is divided into three specialized stages of analysis, completion and evaluation through task decoupling, and high-quality and automatic completion and optimization of the defect report are finally realized by adopting a multi-agent cooperation and dynamic iterative optimization mechanism.

FIELD: computing technology.SUBSTANCE: invention can be used for hardware implementation of the evaluation of random number generators (RNG) based on repeating codes in the output sequence from the RNG. A random number generator quality analyser includes a shift register, a decoder, a comparison unit, a counter, a logarithm calculator, a divider, and a square root calculator, wherein the first input of the device is connected to the input of the shift register, the output of which is connected to the first input of the comparison unit, the second input of the device is connected to the input of the decoder, the output of which is connected to the second input of the comparison unit, the output of which is connected to the input of the counter, the output of which is connected to the input of the logarithm calculator and to the input of the divider, built on the basis of the CORDIC algorithm, the output of which is connected to the input of the square root calculator, the output of which is connected to the output of the device, wherein the output of the logarithm calculator is connected to the input of the divider.EFFECT: expanding the information field for assessing the quality of the RNG operation during hardware implementation.2 cl, 5 dwg

The application discloses a CRC hardware computing system and a chip, the CRC hardware computing system comprises i selected processing arrays; each selected processing array comprises m selected control modules, each bit of information value of the information field has a corresponding selected processing array in the CRC hardware computing system; in the generating polynomial, except the coefficient of the highest power of the generating polynomial, each power term has a corresponding selected control module in each selected processing array; each selected control module is used for selecting the exclusive or result of the information value of the corresponding bit in the information field and the associated value or the CRC initial value associated with the corresponding power according to the coefficient of the corresponding power in the generating polynomial under the triggering of a clock signal, and transmitting the result to the associated selected control module except the selected processing array where the selected control module is located, so as to output the CRC code in parallel after several clock periods.

The invention discloses an internet of things data intelligent acquisition and analysis method and system applying edge computing, and relates to the technical field of intelligent processing. The method comprises the following steps: taking an edge node as an execution main body, extracting a task meta-information field when an upper layer task request instruction is received, and then constructing a cognitive driving data set; and a collection intention perception index CGZ is constructed to perform interval determination, and corresponding sampling configuration switching is generated. After sampling configuration switching is completed, the edge node analyzes disturbance intensity of temperature and humidity in a second sliding time window, a comprehensive disturbance trend index ENV is formed after synthesis, and the comprehensive disturbance trend index ENV and a collection intention perception index are fitted to construct an edge response index BXY for comprehensive matching degree evaluation. According to the method, joint analysis of task characteristics, environment disturbance and acquisition requirements is completed at edge nodes, a closed-loop acquisition regulation and evaluation mechanism is formed, and the method is suitable for data acquisition management in various application scenes of the Internet of Things.

The invention belongs to the field of intelligent monitoring, and discloses an active and passive fusion clean room environment intelligent monitoring method, which constructs an active and passive fusion monitoring system based on covariable statistics. A two-parameter variation function is established by introducing real-time wind field difference as a key covariable, and the defect that a traditional model ignores flow field dynamics is overcome; a comprehensive blind area guiding index is constructed by using a deviation between a basic information field generated by a fixed sensor and a correction information field formed by robot fusion data and combining an inherent coverage risk and a joint space disparity degree, and an absolute monitoring blind area is accurately identified; therefore, the control mode of fixed route inspection to blind area driving type active detection is converted. According to the method, on the premise that the hardware cost is not increased, the full-domain monitoring coverage rate, precision and sudden pollution response speed of the clean room are remarkably improved.

This application discloses a voice control method, device, and storage medium for smart homes, relating to the field of smart home technology. The method includes: upon receiving control voice information, extracting device information fields and control logic fields from the control voice information; determining the device identifier of the target device based on the device information fields, and determining the execution action information of the target device based on the control logic fields; generating a device control command for the target device based on the device identifier and execution action information, and sending the device control command to the target device to cause the target device to execute the device control command. Through the above technical means, the intent of the control voice command can be accurately identified using the device information fields and control logic fields to generate the corresponding device control command, solving the problem of fixed input formats and easy misidentification of control voice in existing technologies, and ensuring the flexibility and accuracy of voice control.

The invention relates to a method for loading a sample device (3). In this method, an information field (20) associated with an object (2, 90, 51) is made available to a control unit (7) connected to the sample device (3). The object (2, 90, 51) is positioned so that it is accessible for processing in the sample device (3).

The application discloses a method, medium and device for seamlessly handling a service in an interactive interface, the method comprising: receiving a user service request and loading service rules containing a process state machine; guiding the user to input information according to a current process stage and dynamically generating a structured confirmation component after real-time verification; listening to user confirmation operations to constitute a confirmed information unit; querying the process state machine based on the confirmed information unit to determine a stage transition condition, and performing an interface reconstruction operation when the condition is met; when a final stage is reached and all required information fields are confirmed, automatically packaging and submitting a complete data request package, and displaying a handling result on the same interface. The application overcomes the process interruption problem caused by multi-interface jumping in traditional service handling, ensures the coherence of user operations and the consistency of the interface through state machine driving and dynamic interface reconstruction, and significantly improves the service handling efficiency and user experience.

The application provides a data updating method and device, wherein the method comprises the following steps: obtaining change data of target data; based on the change data, storing field updating information in an updating information field of the target data and storing data change type information in an operation type field of the target data; based on the updating information field and the operation type field, determining an updating mode of a field to be updated; based on the updating mode and the change data, updating historical data corresponding to the target data stored in a database, and performing column storage on the updated historical data. The data updating method and device provided by the application expand the fields of the target data in the Hudi architecture, are used for assisting the updating process of the change data in the target data, realize the storage of necessary information of field updating, enable the accurate updating of the fields in the Hudi architecture based on the updating information stored in the expanded fields, and improve the accuracy of data updating.

This invention discloses a method for drone swarm inspection under budget constraints in large-scale traffic scenarios, belonging to the field of intelligent transportation and unmanned system collaborative control technology. The method first models the traffic environment as a discrete latent information field using information field theory to complete the initial embedding of drones and inspection nodes. Then, it utilizes the multi-directional attention mechanism of graph neural networks to achieve environmental feature fusion and generate an initial node-drone allocation strategy. Subsequently, it satisfies the endurance budget constraint through dual-criteria heuristic pruning and recovers high-value unvisited nodes using field gradient re-insertion. Finally, it outputs an optimized inspection path and completes model reinforcement learning training and cross-scenario transfer. This invention also discloses the corresponding inspection system, storage medium, and computer equipment. This invention can generate highly collaborative and high-coverage inspection paths in seconds under strict endurance constraints, solving the problems of slow solution, low coverage, poor collaboration, and weak generalization ability of traditional algorithms.

The invention provides a response information generation method and device and related equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a to-be-processed user question of a target user; performing statement analysis on the user question, and determining a service scene to which the user question belongs and a response template associated with the service scene; generating personalized response logic corresponding to the target user based on the historical session information of the target user and the response template; querying corresponding user service information from a pre-constructed user information base according to an information field required by the response template; and splicing the user question, the user service information, the personalized response logic and the historical session information into an input prompt, inputting the input prompt into a pre-trained response information generation model, and outputting response information for the user question. The accuracy of response information generation can be improved, and model illusion can be reduced.

Methods, apparatuses, and computer readable media for initial control frames with block acknowledgement request, where a STA comprises processing circuitry configured to: decode, from an access point (AP), an ultra-high reliability (UHR) buffer status report poll (BSRP) trigger frame, the BSRP trigger frame including a user information field, the user information field comprising an association identification (AID) field, the AID field indicating an AID of the STA, and the BSRP trigger frame including a common information field, the common information field comprising a field, the field indicating a format of a response from the STA, in response to the field indicating the format of the response from the STA is a non-HT duplicate PPDU, encode, for transmission to the AP, the non-HT duplicate PPDU, and in response to the field indicating the format of the response from the STA is a PPDU, encode, for transmission to the AP, the PPDU.

The embodiment of the invention provides a vehicle interaction control method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a target anchor point type corresponding to a vehicle interaction instruction in response to the received vehicle interaction instruction; obtaining a preset semantic anchor point, wherein the semantic anchor point is used for representing a mapping relationship between the anchor point type and the meta-information field; based on the target anchor point type and the semantic anchor point, determining a target meta-information field corresponding to the target anchor point type; and performing interaction control on the vehicle based on the interaction type indicated by the target meta-information field, thereby reducing the technical problem that the interaction control of the vehicle is not accurate enough because the semantic definition of different functional systems (such as a cabin environment and a seat) of the vehicle lacks a unified standard and the situation of'synonym 'exists. Therefore, the technical effect of improving the accuracy of interaction control of the vehicle is achieved.

The invention relates to a bridge structure toughness state regulation and early warning method and system, and solves the problems of splitting and response passive lag of each link in bridge operation and maintenance, and the method comprises the steps: collecting the internal sensing data of the bridge structure state and material performance, synchronously obtaining the external multi-dimensional data of weather, traffic and geology, and carrying out the early warning of the bridge structure toughness state. A global sensing dynamic information field is generated through fusion processing; based on the information field, driving the digital twin to carry out multi-scene coupling deduction, and when a response exceeds a threshold value, deciding and outputting a graded early warning signal and a corresponding pre-intervention strategy according to a toughness evaluation system; according to the early warning signal and the strategy, if an automatic execution condition is satisfied, a control instruction is issued to the distributed network to execute active adjustment; otherwise, generating a digital plan and pushing the plan to a specified terminal. The method has the following effects that fundamental transformation of bridge operation and maintenance from passive lag to active look-ahead is achieved, and the self-adaptive capacity and the overall toughness of the system are remarkably enhanced through intelligent closed-loop linkage.

The embodiment of the invention provides a method for determining a suspected user of a target event, and the method comprises the steps: obtaining a plurality of result tables which are obtained through querying different types of user behavior log tables related to the target event; and for any first result table, determining the respective field abstract of each first field according to the field value of each first field in the first result table. Inputting each first field and the field abstract thereof into a first large model, so that the first large model extracts a plurality of key fields from each first field to form a first compression table; and according to the target field value of the identity information field, reading each first data row from the first compression table to form a first sub-table of the target user identified by the target field value. And utilizing the second large model to generate behavior chain information of the target user based on a plurality of sub-tables, corresponding to the plurality of result tables, of the target user. And determining a suspected user from the plurality of users according to the behavior chain information of the plurality of users in the plurality of result tables.