2202results about How to "Reduce errors" patented technology

The invention discloses a photovoltaic cleaning robot based on automatic path planning and an operation method thereof, relates to the technical field of robots, and solves the problem of cleaning blind spots in an existing cleaning robot and the endless loop risk of a path planning algorithm. According to the invention, the surface information of the photovoltaic panel is accurately captured through the multispectral acquisition module, a high-resolution and high-definition comprehensive image is generated through the data fusion processing module, then dirt is accurately identified on different scales by using a multi-scale pyramid structure and an adaptive feature fusion mechanism, and an attention mechanism and environmental perception data are combined, so that the real-time performance of the system is improved. The recognition threshold is dynamically adjusted, and misrecognition and missing detection are reduced; and finally, enabling the robot to autonomously learn in a complex environment and optimize an obstacle avoidance strategy through a dynamic obstacle avoidance algorithm based on deep reinforcement learning. The intelligent level and the cleaning effect of an existing photovoltaic cleaning robot are greatly improved.

The invention discloses a multi-working-condition-oriented equipment fault diagnosis method based on unbalanced learning, and the method comprises the following steps: collecting the operation data of equipment under different working conditions through a plurality of sensors, carrying out the preprocessing, feature extraction and feature selection of the collected original operation data, and obtaining a feature set; processing the feature set by adopting an unbalanced learning technology and a cost-sensitive learning algorithm to obtain a balanced data set; constructing a multi-working-condition fault diagnosis model based on learning, and optimizing model parameters by adopting a method of combining cross validation and grid search according to a balanced data set in a model training process; deploying a multi-working-condition fault diagnosis model obtained through training, carrying out the online diagnosis of equipment faults, and continuously updating and optimizing the model through a continuous learning mechanism. According to the method, the unbalanced learning technology is applied to multi-working-condition fault diagnosis, the accuracy and robustness of diagnosis can be remarkably improved, and real-time monitoring and predictive maintenance of the equipment health state are achieved.

The embodiment of the invention discloses a speculation decoding method and device for a large language model and a medium, and relates to the technical field of large language models, and the method comprises the steps: obtaining the current task information of a target large language model; the method comprises the steps of inputting original text prompt information into a target large language model, determining initial token information, constructing a plurality of patch data of a specified patch level according to the initial token information and the original text prompt information, generating a plurality of candidate patch sequences in parallel according to each patch data and a draft model, mapping each candidate patch sequence, determining initial draft information, and outputting the initial draft information. The preliminary draft information comprises a token sequence corresponding to each candidate patch sequence; and performing parallel verification on the token sequence corresponding to each candidate patch sequence through the target large language model, screening the token sequences corresponding to the candidate patch sequences, determining the next round of input of the draft model, and performing speculative decoding.

The invention relates to the technical field of law enforcement intelligent alarm, in particular to a multi-mode intelligent analysis method and system based on law enforcement supervision. The method comprises the following steps: acquiring a law enforcement scene video file from a law enforcement supervision recorder platform, and performing audio and video segmentation and law enforcement behavior information identification analysis to obtain law enforcement scene audio behavior information data and law enforcement scene image behavior information data; performing timestamp and spatial position extraction processing on the law enforcement scene video file, performing multi-modal time-space synchronization association analysis, and performing law enforcement behavior sequence connection processing and event behavior intention recognition analysis at the same time to obtain law enforcement scene event behavior intention information data; and obtaining a preset law enforcement event behavior knowledge graph, and carrying out behavior normative score calculation and nonstandard behavior intelligent alarm optimization analysis to generate a law enforcement scene event nonstandard behavior optimization suggestion report. According to the invention, the accuracy of law enforcement nonstandard behavior supervision alarm can be improved.

The invention discloses a containerized resource dynamic allocation method for a power distribution network system and electronic equipment. The method comprises the following steps: judging that resource use data is greater than a preset resource threshold value by monitoring the resource use condition of each physical node in a power distribution network system; if yes, calculating a load balancing index of each physical node, and generating a container migration task list based on the load balancing index, the service priority and the service quality requirement information; packaging container data corresponding to the to-be-migrated container in the migration task list, and determining container state snapshot information and network connection information of the to-be-migrated container; establishing a secure channel between the source node and the target node based on the network connection information, and transmitting container data and container state snapshot information of the source node to the target node; reconstructing a container operation environment on the target node, and generating a target container; and suspending the to-be-migrated container on the source node, and activating the target container on the target node. And efficient migration of the container is realized.

The invention discloses a warehouse level code problem solving system based on a large language model, and relates to the technical field of software engineering, a source code file is extracted from a code warehouse, a static analysis tool is utilized to analyze codes, a warehouse level code graph is constructed, and then code entities and dependency relationships thereof are analyzed; based on the warehouse-level code graph, combining historical problem solving data, and constructing a dynamic evolution knowledge graph through continuous learning; through a context retrieval module, according to the context information of the current problem, dynamically retrieving related solution strategies and generating corresponding code patches, complementing or reviewing suggestions; the validity of the generated patch is verified through static analysis, unit testing and integration testing, and a problem solving strategy is optimized according to feedback of a developer. The problem solving efficiency and accuracy can be improved, the development cost is reduced, the solving process is gradually optimized through an intelligent feedback mechanism, a closed-loop feedback mechanism is formed, and therefore the increasingly complex software development requirements are met.

The invention discloses a security data generation method and device, a storage medium and an electronic device.The method comprises the steps that description information of a target task is obtained, the description information at least comprises a first task attribute corresponding to an equipment type associated with the target task, a second task attribute corresponding to an operation type associated with the target task, and a third task attribute corresponding to an operation step associated with the target task; the description information is used for filling placeholder information in a target template, multiple structured cue words are obtained, and the target template is a cue word template which is retrieved from a pre-constructed template library and related to the target task; and screening out a target cue word from the plurality of structured cue words, and inputting the target cue word into a pre-trained large language model to obtain security data corresponding to the target cue word. The problem of how to improve the generation quality and the generation efficiency of the safety measure data corresponding to the operation ticket and the work ticket is solved.

The invention discloses a contract evaluation method, system and device based on a large model and a medium, and the method comprises the steps: obtaining a target contract, carrying out the data preprocessing, obtaining the preprocessed contract data, and inputting the preprocessed contract data into a preset contract large language model; the preset contract large language model stores a vector knowledge base including coastal bulk cargo transportation knowledge, legal clauses and industry regulations; in a preset contract big language model, performing contract classification and contract summary extraction on the current preprocessed contract data by using a first model agent to obtain contract summary information; performing contract risk assessment on the current preprocessed contract data to obtain risk assessment information and / or risk avoidance suggestion information; performing benefit measurement and calculation on the current preprocessed contract by using a third model agent to obtain benefit measurement and calculation information; according to the method, the examination and evaluation of the large model in the coastal bulk cargo transportation contract are realized, and the purposes of saving the labor cost and improving the business turnover rate are achieved.

The invention relates to the technical field of genomics, in particular to a gene detection data cleaning method and system based on artificial intelligence. The method comprises the following steps: acquiring gene detection data, and performing preliminary filtering on the gene detection data based on removal of low-quality reads to obtain preliminary filtering data; performing linker sequence identification and removal on the preliminarily filtered data, and performing sequencing error correction to generate gene sequence data; performing GC content analysis and repetitive sequence identification on the gene sequence data to obtain sequence feature data; performing dynamic quality threshold adjustment according to the sequence feature data, and performing secondary filtering on the gene sequence data to generate high-quality sequence data; and performing sequence pattern recognition on the high-quality sequence data to obtain sequence pattern feature data. According to the method, deep analysis is carried out by utilizing sequence characteristics such as GC content and nucleotide distribution, and the recognition capability on sequence complexity and variation modes is improved.

The invention relates to the technical field of production task decision making, in particular to a furniture production task automatic matching method and system based on intelligent manufacturing. And extracting personalized demand information corresponding to the production task, converting the personalized demand information into standard design parameters, and generating a customized task. The production task is disassembled into a plurality of sub-tasks, and each sub-task has independent attributes including process requirements, resource requirements and time requirements; and performing one-to-one mapping on the customized tasks and the subtasks to generate an execution plan. Performing resource matching by using a constraint algorithm based on the execution plan and the existing production resource information to obtain a production plan; and obtaining an optimal scheduling plan by using a constraint algorithm according to the production plan. And based on the real-time production data and the burst information, adjusting the optimal scheduling plan through the data analysis model to obtain a final scheduling plan. The method can cope with emergencies or real-time data changes, and manual decisions are reduced.

The invention relates to the field of intelligent auditing data, in particular to a standard intelligent auditing and compliance checking method and system, a terminal and a medium. Dividing the to-be-audited document into a plurality of document elements based on the to-be-audited document and a preset classification rule; analyzing the to-be-audited document based on the plurality of document elements and a preset auditing direction corresponding to each document element; and generating an auditing report and an auditing manuscript based on the auditing result of each document element. According to the method, the document auditing efficiency and accuracy are improved.

The invention provides a method and a system for intelligently generating a complete dispatch report for financial unfavorable assets, and relates to the technical field of data investigation and arrangement, comprising Sp1, complete dispatch demand acquisition, Sp2, intelligent reasoning planning, Sp3, data acquisition and processing, Sp4, public opinion retrieval and analysis, Sp5, legal information extraction and verification, Sp6, data integration and report generation, and Sp7, report modification and output, and the method comprises the steps of Sp1, complete dispatch demand acquisition, Sp2, intelligent reasoning planning, Sp3, data acquisition and processing, Sp4, public opinion retrieval and analysis, Sp5, legal information extraction and verification, Sp6, data integration and report generation, and Sp7, report modification and output. By integrating a large model, an online retrieval tool, a data table tool and a key point extraction tool, automation and intellectualization of a complete dispatching process are realized. The system can automatically acquire, process and integrate data, greatly improves the efficiency of data acquisition, analysis and report generation, and reduces the probability of manual intervention and errors.

The invention discloses an intelligent dynamic optimization method and system for the battery temperature of a liquid cooling energy storage cabinet, and particularly relates to the technical field of dynamic optimization of the battery temperature, and the method comprises the steps: obtaining a temperature data set in a battery monitoring region in real time; obtaining a battery operation evaluation coefficient in real time, analyzing the battery operation evaluation coefficient, and determining the operation state of the battery; the operation state of the battery comprises a discharging state and a charging state, and a discharging normal instruction or a charging normal instruction is generated respectively; according to the method, the temperature data set and the battery operation evaluation coefficient are input into the pre-constructed neural network model, the future temperature change can be predicted, the temperature change in the discharging and charging processes is analyzed according to the generated discharging or charging optimization instruction, and the targeted temperature optimization strategy is obtained, so that the battery can be effectively optimized when the battery is discharged or charged. A cooling or current control strategy can be dynamically adjusted according to specific conditions, and the problem of battery overheating or low efficiency is prevented.

The invention relates to the technical field of parking management, in particular to an intelligent parking order tracing and auditing method and system, and the method comprises the steps: receiving order data from a plurality of parking platforms, carrying out the preprocessing of the order data, and inputting the preprocessed order data into a block chain platform for storage and management; performing automatic processing and auditing on the order data by using an intelligent contract, and forming an auditing log; a time-space Transform model is established, intelligent analysis is carried out on data in an audit log, finally encryption tracing processing is carried out on the audit log, a user carries out order query, data audit and report generation through a user interaction module, data loss, tampering and malicious destruction are effectively prevented, order processing efficiency and accuracy are improved, and user experience is improved. Manual intervention and errors are reduced, an administrator can conveniently check and verify the access history and operation record of order data at any time, and the safety and traceability of the data are ensured.

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention relates to the technical field of electric energy metering, in particular to an insulation performance evaluation system and method for an insulation voltage transformer, and the system comprises an insulation monitoring and sensing optimization module, a central storage unit, a data processing and abnormity analysis module, and an equipment performance evaluation module. The insulation monitoring and sensing optimization module builds an intelligent sensor network and a data acquisition and processing terminal, and realizes real-time monitoring of the insulation voltage transformer; the data processing and anomaly analysis module extracts key features and analyzes the key features in real time by using a local anomaly factor algorithm, so that the abnormal change of the insulation performance can be found in time; and the equipment performance evaluation module calculates a comprehensive gain value index to carry out detailed performance evaluation on equipment with problems, so that operation and maintenance personnel can know the state of the equipment and formulate a reasonable maintenance, replacement or optimization strategy. The method is used for solving the technical problems of incomplete monitoring and insufficient evaluation of the insulation performance of the insulation voltage transformer.

The invention provides a credential platform data migration verification method and system, and relates to the technical field of computers.The method comprises the steps that all to-be-migrated source data in a credential platform database are read, basic information of the source data is obtained, and a data label is set for each piece of data; reading fields and contents in the migration data, and constructing a data similarity verification model; selecting a migration path and a target database according to the migration demand, and dynamically evaluating the similarity between the source data and the target data through a data similarity verification model; verifying the migrated source data based on the target database, and performing incremental verification on data of different fields in the table; the data table of the to-be-migrated source data is verified in real time among different migration nodes, data changes on each node are verified step by step through an increment verification mechanism, if data missing or verification inconsistency occurs in the verification process, an alarm mechanism is triggered, and the problem of data missing or inconsistency can be automatically recognized and corrected.

The invention belongs to but is not limited to the technical field of software development, and particularly relates to a multi-round reasoning and feedback optimization method and system for industrial software codes, and the method comprises the steps: S1, vector code library establishment: the establishment of a vector code library is composed of three parts of feedback establishment, vector database establishment and format summarization; s2, code reasoning optimization: the code reasoning optimization mainly comprises four aspects: control flow graph analysis, multi-query generation and reciprocal ranking fusion retrieval, reasoning generation subtask and code chain submodule generation, and code combination completion; and S3, feedback optimization: the feedback optimization is composed of score feedback optimization and log feedback optimization. According to the method, an automatic verification mechanism is introduced, logic consistency check and performance evaluation are carried out on the generated and optimized codes, and the correctness and execution efficiency of the codes are ensured. The verification mechanism can find and correct errors in real time in each stage of generation, so that the cost of manual verification is reduced, and the development efficiency is improved.

The invention discloses a rural house structure optimization design method and system based on building information modeling, and relates to the technical field of building structure analysis design, and the method comprises the steps: obtaining geographical climate data, building user demand data and construction condition data of a to-be-built rural house; determining a house design variable set according to the acquired data; randomly generating an initial solution according to the value range of each variable parameter in the house design variables to construct an initial population; performing individual optimization on the initial population by using a genetic algorithm, screening individuals according to fitness, performing iterative genetic evolution operation including crossover and variation, and finally determining an optimal individual; and inputting target values of various variable parameters indicated by the optimal individual into a BIM construction module to determine a target BIM model for the rural house. Therefore, genetic algorithm optimization and a BIM modeling technology are organically fused, and the structural safety, the economical efficiency, the construction efficiency and the intelligent level of rural house design are improved.

The invention belongs to the technical field of information communication, and discloses a twinborn technology-based intelligent substation optical fiber link 3D visualization method, which is characterized by comprising the following steps of 1, constructing an optical fiber path 3D visualization model, 2, carrying out twinborn simulation and intelligent auxiliary optical fiber alignment, and 3, carrying out twinborn simulation and intelligent auxiliary optical fiber alignment. And 3, constructing an optical fiber logic link intelligent identification and early warning system. The method has the beneficial technical effects that the efficiency is improved, errors are reduced, the safety management is enhanced, the fault response speed and accuracy are enhanced, the intelligent level of electric power capital construction is improved, the engineering safety is guaranteed, and the industrial technical progress is promoted.

The invention provides an energy management system based on a cloud and edge integrated optical storage system. The energy management system comprises a cloud module and an edge module, the EMS controller is used for collecting information of the optical storage equipment module and the load module and uniformly sending the collected data to the cloud module; the cloud module predicts future photovoltaic power generation power / electric quantity through a photovoltaic power generation prediction model by receiving data acquired by the EMS controller; predicting a future load through the load prediction model; analyzing peak and valley time periods of the electricity price through the electricity price management model, and sending prediction data to the edge module; and the edge module carries out energy management through the control logic of energy management according to the battery SOC, the chargeable amount, the photovoltaic predicted power and the generating capacity, and superposition peak-valley arbitrage and safe anti-countercurrent logic. Through the arrangement, the whole energy management system has high intelligence and automation levels, energy distribution and use are optimized, and the energy utilization efficiency is improved.

The invention relates to the technical field of network transmission, in particular to a video data transmission method, which comprises the following steps of: based on a video transmission data packet, analyzing a sending time point of the video data packet, recording a sending moment and a serial number, checking a time stamp at a plurality of transmission nodes, and generating a time stamp data packet. According to the invention, by matching the timestamps and the serial numbers, marking the data packets and checking the transmission nodes, the security and reliability of data transmission are improved, errors and loss of the data packets in the transmission process are reduced, and the video quality is optimized by analyzing the video data, identifying abnormal image frames and adjusting transmission parameters. Compression parameters and server resource allocation are dynamically adjusted according to video contents and in combination with real-time user requirements, so that video quality is maintained under the condition that the bandwidth is limited, the size of a buffer area and the capacity of a data packet are adjusted according to network conditions, and the fluency and continuity of video playing are improved.

The invention provides a fabricated building intelligent management method and system based on a BIM model, and the method comprises the steps: installing a sensor at a collection point, and collecting the position, angle, size and other sensing data in real time; preprocessing the collected sensing data, and carrying out cross validation on the preprocessed sensing data; calculating an actual error of each acquisition point of the preprocessed sensing data according to a cross validation result and a target error range, and generating an error analysis report; the result of the error analysis report is compared with the BIM model, and the difference between the actual component and the design model is displayed; and according to a comparison result, a correction or adjustment measure is formulated for the acquisition points of which the errors of each error analysis report exceed an acceptable range. The system comprises an equipment layout module, an error analysis module and an adjustment and correction module. The method plays an important role in improving the construction efficiency, quality and safety; and a closed loop is formed through data acquisition, analysis and feedback.

The invention discloses an RISC-V-based thread bundle scheduling method and device and a medium, belongs to the technical field of general graphics processors, and aims to solve the technical problem that the execution efficiency of instructions is affected by the fact that an existing thread bundle scheduling module is affected by a synchronous fence mechanism and a thread bundle scheduling strategy, and the thread bundle scheduling efficiency is easily reduced. The method comprises the following steps: performing instruction configuration on a current thread bundle state to obtain a real-time thread bundle state instruction; performing state control on the thread bundle queue to obtain a state change control strategy; performing instruction fetching sequence control on the thread beam queue, and determining a thread beam instruction fetching control strategy; performing address fetch control on the thread bundle queue, and determining an address type control strategy; and performing thread beam scheduling processing based on a thread beam scheduling system architecture on the thread beam queue through the real-time thread beam state instruction and the thread beam scheduler after the strategy configuration is completed to obtain a thread beam scheduling result.

The invention relates to the technical field of communication interaction, in particular to a data interaction method based on an intelligent control platform. The method comprises the following steps: acquiring multi-dimensional data of production equipment, performing anomaly marking and format unification processing, generating a production line data stream, performing long and short term dependency analysis on the data stream, and constructing a time-space association network, thereby realizing prediction of an anomaly situation, generating an anomaly intelligent analysis model by using a multi-modal fusion modeling technology, and performing data analysis on the anomaly intelligent analysis model. And through the model, abnormity traceability is carried out, and abnormity reasons are clarified. According to the method, a corresponding correction strategy is constructed based on an abnormal reason, tree-shaped interaction sharing is performed through an intelligent control platform, a sharing correction instruction is formed, abnormal correction processing is performed on a production line according to the sharing instruction, feedback is collected through the intelligent control platform, an effective data interaction mechanism is formed, and the reliability and efficiency of the production line are improved. The data interaction method based on the intelligent control platform is more accurate and more comprehensive.

The invention discloses a high-frequency data remote transmission method and system, and the method comprises the steps: dynamically adjusting the collection frequency and mode according to environment conditions, and obtaining high-frequency data in real time; based on the data type and the transmission network state, a compression algorithm, a filtering mode and a coding strategy are automatically selected; the congestion condition of the transmission network is predicted through a built-in machine learning model, and a packaging strategy and transmission parameters are dynamically adjusted according to network conditions; in the data receiving process, the bit error rate in the transmission process is monitored in real time, abnormity in transmission is automatically detected, repair is carried out through an error correction algorithm, and if repair fails, the system automatically requests the data packet again; and the recovered high-frequency data is classified and stored according to the importance, real-time performance and storage cost of the data, and automatic storage strategy adjustment is realized in a remote database. According to the technical scheme, the high efficiency, reliability and safety of remote transmission of high-frequency data are improved.

The invention relates to a long context knowledge reasoning method based on big language model knowledge extraction and self-consistent thinking chain prompt, which extracts high-quality abstract knowledge from a context in a segmentation pre-filling process, enhances the understanding ability of a big language model for a complex context, and improves the understanding ability of the big language model for the complex context in a reasoning stage. Through constructing a thinking chain reasoning prompt, a logically strict transparent reasoning process is gradually generated by using the extracted high-quality abstract knowledge, and the reasoning ability and interpretability of a large language model in the aspect of complex reasoning problems are enhanced. In order to comprehensively cover various aspects of the question, the method encourages to generate a plurality of thinking chains, different thinking chains can perform reasoning through different paths so as to provide diversified visual angles and answers, and then all generated reasoning processes are reflected and verified through self-consistent prompt, so that the model identifies and corrects wrong reasoning paths, and the reasoning efficiency is improved. Therefore, the accuracy of final output is improved.

The invention relates to the technical field of wet cleaning in a semiconductor manufacturing process, and discloses a semiconductor wet cleaning process optimization method based on PLC programming, and the method specifically comprises the following operation steps: constructing a PLC programming dissolution rate matching system, designing and integrating a set of PLC-based dissolution rate matching system, and optimizing the PLC-based dissolution rate matching system. The system needs to have the functions of data acquisition, processing and feedback, a dissolution rate model is established according to cleaning liquid components and wafer material characteristics, an algorithm is preset to be matched with the actual dissolution process, and sensors are deployed in cleaning equipment and used for monitoring key parameters such as the temperature and concentration of cleaning liquid and the dissolution rate of the surface of a wafer in real time. According to the semiconductor wet cleaning process optimization method based on PLC programming, the rotating speed and cleaning liquid distribution in the cleaning process are accurately controlled, the problem of flowing particle defects caused by the poor dissolving speed in traditional wet cleaning is effectively solved, and the cleanliness and the yield of semiconductor wafers are improved.

The embodiment of the invention relates to the technical field of semiconductors, and discloses a data management method, system and device for semiconductor process formula parameters and a medium, and the method comprises the steps: carrying out the data analysis of a collected process formula of one or more data formats, converting the data into a target data format, and storing the data in a database; and in response to a data request transmitted through the data interface, returning the corresponding process formula data in the database through the data interface in a data request format based on the configured mapping relationship. Through the scheme of the invention, standardized semiconductor process formula parameter related data can be provided and output to other systems in a standard data structure, and at least the technical problems of low efficiency of checking different equipment parameters, low production management efficiency, frequent errors, high management cost and the like in the prior art are solved.

The invention discloses a construction method, system and equipment of a power dispatching knowledge question-answering system and a storage medium. The construction method comprises the steps of obtaining a power dispatching semantic document needing to be processed by the power dispatching knowledge question-answering system; sequentially carrying out character-based segmentation, proposition conversion and proposition combination on the power dispatching semantic document on the basis of the large language model and the related cue words to obtain a plurality of text blocks; based on the large language model and the related prompt words, identifying and extracting entities related to power dispatching and relationships among the entities from each text block; constructing a local graph for each text block on the basis of the large language model and the related prompt words, the entities extracted from each text block and the relationship among the entities; traversing each text block, and combining all the local graphs into a global graph; and on the basis of the large language model and the related prompt words, according to the question type queried by the user, a reply text is correspondingly generated by matching a minimum local graph which is most related to the global graph in the global graph.