37 results about "Identifying problems" patented technology

The invention provides an automatic budget auditing method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: receiving a to-be-audited budget file and an auditing rule; based on the auditing rule and the file format and the professional attribute of the budget file, determining an analysis agent; performing structured analysis on the budget file based on the analysis agent to generate to-be-audited data; and calling the vertical domain large language model, and performing budget auditing on the to-be-audited data based on the auditing rule. According to the method and the system provided by the invention, structured analysis is performed on the budget file by using the analysis agent, so that the automation degree and the accuracy of auditing are improved; according to the budget auditing method, budget auditing is carried out by calling the vertical domain large language model subjected to vertical domain parameter fine adjustment, so that problems and abnormal conditions in the budget file can be identified more accurately, the budget auditing quality and efficiency are improved, and a more reliable auditing result is provided for a user; through automatic budget auditing, the budget auditing efficiency is remarkably improved.

The invention relates to the technical field of enterprise management and artificial intelligence, discloses a management method for cooperatively solving problems based on multiple roles, and aims to improve enterprise problem processing efficiency and cooperative capability. The management method for solving the problem based on multi-role cooperation comprises the following steps: collecting and cleaning front-line work details through an employee client of a scenarized template; the AI processing module calls a fusion model of NLP semantic analysis, computer vision identification and time series data comparison, identifies problems from work details and generates a report; the role matching engine screens matched experts and pushes related information to an expert client to input a solution; after receiving the scheme, the decision-making client synchronizes a decision-making instruction to the execution main body; and the server storage module associatively stores the full-process information through the unique identifier to form a reusable corpus packet. According to the method, multi-role efficient collaboration and knowledge precipitation are realized, and a management closed loop is optimized.

A system is provided.SOLUTION: A system comprising: means for collecting an operation log of a user in real time; means for transmitting the collected operation log to a server; means for analyzing the received operation log and identifying a problem that the user is facing; means for retrieving appropriate support information for the identified problem from a database; means for generating a solution statement using a generative AI model based on the retrieved support information; and means for displaying the generated solution statement on a user device.SELECTED DRAWING: Figure 1

The present invention disclosure provides a system for performing root cause analysis, comprising a processor and a memory, the processor is configured to at least one problem associated with running of an application by at least one user, wherein identifying problem includes determining a priority level of one or more services being impacted based on service level agreements, identify at least one root cause associated with the problem, identify one or more root cause corrective actions (RCCA) based on root cause and implement at least one RCCA for troubleshooting the identified problem. Further, the system generates a RCCA form for use by a user group for identifying and validating an additional RCCA and update the database to include the additional RCCA based on a quality score for the identified root cause corrective action. The system is configured to create a RCCA form, auto-fill the RCCA form, identify one or more RCCA implemented for the identified problem, and determine a quality score of the RCCA.

We provide the system. [Solution] Means of obtaining business data from users, A means of analyzing acquired business data and identifying problems, A means for generating specific instructions for artificial intelligence based on identified tasks, A means of presenting generated instructions to the user and executing them if selected, A means of monitoring the progress of work and preparing regular reports, A system that includes this.

This invention provides a control method and apparatus based on a lean manufacturing system, comprising: calculating the operational maturity value of a target lean manufacturing system to identify problems to be improved; constructing manufacturing strategic goals by comparing the target factory with business objectives based on pre-built quantitative indicators; streamlining the organizational structure based on pre-built lean processes, lean organizational structure, and lean departmental functions and responsibilities; constructing a multi-level key performance indicator system and a facilitating management meeting mechanism; and finally, constructing an implementation plan and controlling the target factory according to the implementation plan to achieve the optimization goals. This invention solves the problems of high deployment costs and poor application effects in existing technologies.

The invention belongs to the technical field of artificial intelligence and data management, and particularly relates to a method for discovering and generating problems through AI, which comprises the following steps: S1, receiving a natural language text of a service system as a work content, and distributing a global unique request identifier; s2, performing context analysis, standard comparative analysis and historical comparative analysis by adopting an AI problem discovery model; s3, fusing and sorting the content of the problem clue list based on the global unique request identifier, and generating a structured problem clue list; s4, querying a solution library according to clue attributes in the problem clue list, generating corresponding solution suggestions, and outputting the solution suggestions; and S5, according to metadata in the question clue list, a rule engine of the business system pushes the natural language question list and the solving suggestions to a corresponding terminal or system. The problem that problem grabbing is low in real-time performance and accuracy is solved.

A method and system for course assessment. The method including: receiving assessments from a plurality of assessors for at least one learner; reviewing the assessments for any issues by, for example, an AI agent; if issues are found, returning the assessments for additional review by, for example, an AI agent, if not, continuing; aggregating the assessments by, for example, an AI agent; reviewing the aggregated assessment for any aggregated issues by, for example, an AI agent; if aggregated issues are found, returning the aggregated assessments for additional review by, for example, an AI agent, if not, continuing; and providing the aggregated assessment to the learner. The system makes use of processor and memory to execute instructions to implement the method.

The method includes receiving input describing marine equipment and at least one issue associated with the marine equipment. The method includes determining an identification of the marine equipment. Additionally, the method includes applying the input and the identification of the marine equipment to one or more machine learning algorithms. The one or more machine learning algorithms implement one or more rules that classify and identify problems in the marine equipment. The one or more machine learning algorithms are trained based on metadata for the marine equipment and components of the marine equipment. The method includes outputting at least one solution to the at least one issue.

The invention provides a KPI comprehensive evaluation and test optimization method of an ADAS system. The method comprises the steps of obtaining a work log in an ADAS test process; based on the work log, calculating a KPI index used for evaluating the ADAS system function; evaluating the KPI index according to a preset judgment rule so as to identify a security attention event and a performance weakness event in the ADAS system; for each identified security attention event and performance weakness event, automatically intercepting data in a preset time window before and after occurrence of the events, and marking the data as attention events; and performing fault judgment on the concerned event, and generating a test case optimization suggestion. The technical problems that in the prior art, troubleshooting and test case optimization are disjointed, only single fault positioning can be carried out on recognized problems, and association logic among fault sources, scene elements and test cases is not established, so that quick tracing is difficult when sensing data exceptions occur in the test process are solved.

This invention relates to the field of application development technology and provides a method for identifying duplicate change orders in engineering projects. First, engineering information is correlated and integrated to obtain an intermediate dataset with a logical order of project implementation. Text extraction and data cleaning are then performed on the intermediate dataset to form change order text data. Next, the change order text data are paired based on instruction keywords to form an instruction control group. Then, a dual-thread similarity framework is used to calculate the similarity between two change order text data in the instruction control group to obtain first and second similarity data. If the first and second similarity data meet the duplication condition, the instruction control group is considered as a duplicate change order. In this way, duplicate change orders can be automatically identified, allowing for timely detection of problems and mitigation of company losses.

The invention provides a real-time fault judgment method and system based on an ADAS hardware-in-the-loop simulation platform. The real-time fault judgment method comprises the steps that an anomaly detection unit is connected into a test bench; when the test bench is started, the abnormity detection unit is controlled to carry out real-time detection on the test bench according to a preset time sequence so as to acquire real-time detection data; comparing the real-time detection data with preset operation data in real time; if the real-time detection data is different from the preset operation data, determining that the test bench has a fault point, and giving a fault alarm; and carrying out troubleshooting on the test bench according to the fault alarm. The invention solves the technical problems that an HIL test bench is usually adopted in the traditional automatic test, the HIL test bench cannot immediately identify component or link faults in the test process, and the problem needs to be found through log analysis after the test is finished, so that the troubleshooting lags.

The invention belongs to the field of nuclear power, and particularly relates to a nuclear power plant key information infrastructure asset management method and system, and the method comprises the steps: 1, designing a nuclear power plant key information infrastructure asset data field list; 2, intelligently drawing a network topological graph according to the nuclear power plant key information infrastructure asset data; 3, off-line acquisition, processing and storage are carried out on nuclear power plant key information infrastructure asset data; and 4, performing preventive maintenance analysis on the nuclear power plant key information infrastructure asset data. According to the invention, comprehensive, efficient and safe management of nuclear power plant key information infrastructure assets can be realized, and emergency purchase and equipment replacement frequency can be reduced by identifying problems in advance and taking measures.

According to the big data operation supervision platform based on intelligent government affairs, a semantic vector set capable of expressing a policy goal is established, and a unified government affair behavior life cycle diagram is constructed, so that structured mapping between the policy goal and an operation behavior is realized; through fusion of semantic similarity and flow structure consistency calculation and in combination with a deviation punishment mechanism, a deviation path which does not conform to policy intention, flow specifications or compliance requirements is accurately identified, and structured labeling is carried out; for the identified deviation path, introducing a causal analysis method of laws and regulations priority, cross-department interaction strength and policy association constraint, constructing a causal chain of deviation propagation and positioning an initial responsibility node, and ensuring that the responsibility chain has interpretability and reproducibility; and finally, integrating the causal chain and responsibility node information into a unified abnormal event object, calculating a risk priority, and generating a supervision action which can be directly executed in combination with a compliance feasibility condition, thereby realizing closed-loop management from problem discovery and cause analysis to execution and disposal.

The invention provides a scribing process improvement method and system, and the method comprises the following steps: S100, obtaining a difference value between a target mobility and a current mobility according to the production data of a scribing machine; s200: through process time proportion analysis, identifying problem points causing a mobility difference value, and performing hierarchical processing on the problem points; s300, determining an improvement target value in combination with the problem point and the difference value; and S400, determining an improvement method according to the improvement target value, and verifying whether the mobility reaches the improvement target value or not after implementation of improvement measures. According to the scribing improvement method, the PDCA circulation theory is fused, it is ensured that each problem can be comprehensively analyzed, the root cause is found out to avoid reoccurrence, and therefore the stable improvement of the scribing process production process, the ship building quality and the building efficiency is achieved.

The invention discloses a method for optimizing a memory tool. The method comprises a development stage, a test stage for preventing a memory problem from being introduced, and a test stage, wherein the memory problem missed in the development stage is found; in the construction and deployment stage, the memory problem of the production environment is monitored and quickly responded; establishing a problem checking process and a knowledge base; and accurately positioning and radically treating the problem. According to the method, a problem finding stage is advanced to a development and test stage as far as possible, the problem finding stage is solidified into a research and development process through an automatic tool chain, and meanwhile, a powerful monitoring and diagnosis tool is provided for a production environment, so that a complete closed loop from'prevention '-gt, 'discovery'-gt, 'monitoring '-gt and'radical treatment' is formed.

We provide the system. [Solution] An analysis means installed on the user's terminal and used to analyze visual information displayed on the screen, A means for identifying problems faced by users using data obtained by the said analysis means, A means of presenting solutions to the user based on the problem identified by the specified means, A system that includes this.

The invention provides a model reasoning ability optimization method and system and a computer readable storage medium, in the method, a mixed training data set is generated based on multiple historical dialogue logs, fine-tuning training is performed on partial parameters of recall knowledge data in the mixed training data set, a loss function of a recall knowledge part is not calculated, and the optimization efficiency of the model reasoning ability is improved. The model can focus on reasoning logic optimization instead of external knowledge memory, and has the ability of self-adaptively identifying problem difficulty. Besides, a dialogue data backflow mechanism in a preset period continuously optimizes the mixed training data set, so that the reasoning ability of the model can be optimized in real time, the adaptation accuracy of computing resources is further improved, efficient utilization of the reasoning resources and parallel improvement of the accuracy of reasoning results are finally realized, and the reasoning efficiency is improved. The problems of reasoning resource waste and poor reasoning accuracy caused by static resource control in related technologies are effectively solved.

A method and system for identifying a problem graph in an information technology infrastructure network includes selecting a set of nodes in a topology, where the nodes of the topology represent resources in the information technology infrastructure network, querying historical time series data for the selected nodes, where the time series data records changes in state of the resources represented by the nodes, analyzing the time series data for the selected nodes over a problem period to develop a set of historical directionality rules that define one or more historical problem graphs, and searching the historical problem graph for currently problem state nodes to determine nodes that may be causing and / or affected by the current problem.

This invention discloses a method and apparatus for automatically generating PLC program variable monitoring information, comprising at least the following steps: Step S1, collecting and preprocessing historical time-series variable data packets to obtain a historical dataset; Step S2, feeding the historical dataset to a feature extraction module for feature extraction calculation to obtain a feature set; Step S3, calculating feature importance scores for all features in the feature set; Step S4, based on the feature importance scores, the isolated forest algorithm, and expert knowledge, calculating and analyzing highly correlated variables and adding them to a monitoring variable dictionary as monitoring information, and using the variables in this variable dictionary for real-time monitoring on industrial platform software. Based on unsupervised machine learning results and expert knowledge, this invention can automatically generate a list of variables to be monitored for PLC programs on industrial platform software, helping development monitoring personnel to identify problems more quickly during testing, detect more subtle anomalies, and improve safety.

The invention discloses a financial service-oriented test behavior analysis method and device, and aims at realizing accurate evaluation of the execution condition of testers and the test coverage rate of a system by automatically collecting and analyzing test data. Through an innovative automatic acquisition and test behavior analysis method, the execution condition of a tester is effectively evaluated, meanwhile, the test coverage rate of the system is accurately measured, and the evaluation accuracy is improved; big data analysis and machine learning technologies are utilized to quickly identify problems and potential defects in the test process, test cases and test strategies are optimized, and the test efficiency is improved; the test coverage rate is comprehensively and systematically evaluated in combination with a system architecture diagram and a test case, and analysis is performed from multiple dimensions such as the code coverage rate, the system coverage rate and the transaction coverage rate; critical paths and potential defects are ensured to be fully tested, and the stability and the safety of the system are improved.

The invention discloses a multi-dimensional weight-based teaching evaluation method and system, and the method comprises the steps: collecting the original score of a student on a multi-dimensional index, carrying out the standardization processing of the original score, and unifying the dimension of each index; after the standardized score is obtained, calculating the weight of each index by adopting an analytic hierarchy process, and calculating a course comprehensive absolute score according to the weight; calculating the minimum sample size and the maximum comparison question number of independent comparison among the courses, and adjusting the comparison question number according to the score uncertainty; detecting and rejecting abnormal scores by using a Z-Score method, determining an abnormal threshold value, calculating sentiment analysis scores of the courses, and fusing the sentiment analysis scores with the comprehensive scores; and predicting the future scoring trend of the course by adopting a weighted moving average model. The teaching effect can be evaluated more comprehensively, accurately and dynamically, problems can be found in time, and the teaching quality can be improved.

The application discloses a clinical test subject intelligent follow-up method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a clinical test scheme; generating a subject follow-up table according to the clinical test scheme; sending and updating the subject follow-up table according to the clinical test scheme; and detecting and warning the updated subject follow-up table. The method of the application can optimize the research process, reduce the operation cost, improve the clinical research quality, enhance the internal communication efficiency, track the test progress in real time, quickly identify problems, and thus improve the overall efficiency and quality.

The system according to this embodiment aims to automatically identify problems in the office environment and propose improvements. [Solution] The system according to the embodiment comprises a collection unit, an acquisition unit, an analysis unit, a proposal unit, and an execution support unit. The collection unit collects sensing data from various sensors in the office. The acquisition unit acquires the calendar registration details of employees. The analysis unit analyzes the data collected by the collection unit and the acquisition unit to identify problems in the office environment. The proposal unit makes improvement proposals for the problems identified by the analysis unit. The execution support unit provides specific procedures for implementing the improvement measures proposed by the proposal unit.

The invention relates to the technical field of problem processing, and discloses a problem solving-based machine learning method, which comprises the steps of event input, problem identification, scheme matching and output, empirical corpus precipitation and updating and iterative optimization. After event phenomenon corpora are collected through an event input port, a user initiative question and AI intelligent mining double-path identification problem is adopted; the AI intelligent agent outputs implicit questions and priorities through corpus preprocessing, feature extraction and question recognition model analysis; matching an identification problem and an experience library problem with a solution corpus, judging a matching result through a semantic similarity algorithm and a dynamic threshold value, and pushing an unmatched problem to an expert for processing; the expert scheme and the problem are bound and stored in the experience library, the process is repeated to realize experience library iteration and AI optimization, and the problem processing efficiency and the experience reuse rate are improved.

The invention discloses a green residential building design scheme feasibility evaluation method based on AI, and relates to the field of data evaluation, and the method comprises the following steps: 1, pre-defining one or more design targets of each region in a current to-be-designed residential target, and setting a value range allowed to be received for each design target; 2, obtaining a to-be-evaluated design scheme, and extracting corresponding data from the design scheme based on a design target; 3, comparing the extracted data with a preset numerical range, defining the design targets in the preset range as hit targets, and defining the design targets not in the preset range as missed targets; automatic analysis of the design scheme is realized, low efficiency and subjective deviation of traditional manual evaluation are avoided, a designer can quickly identify problems by utilizing a preset numerical value range and gain and benefit reduction trend quantification, human errors are reduced, evaluation precision and efficiency are improved, and thus the design period is shortened and the trial and error cost is reduced.

The invention provides a weak spot diagnosis and path planning method for an English knowledge graph, relates to the technical field of natural language processing, and aims to provide a weak spot diagnosis and path planning method for an English knowledge graph by constructing a dynamic assessment model of cognitive uncertainty, a cause and attribution diagnosis mechanism of cognitive friction and a diagnosis and repair integrated closed-loop path planning method. And efficient and accurate diagnosis and self-adaptive repair of the weak points of the learner in the English knowledge graph are realized. The robustness and accuracy of weak spot diagnosis are improved, and misjudgment caused by instantaneous behavior disturbance is effectively avoided; through an accurate probe strategy of cause formation and attribution, interference to a learner is reduced, and meanwhile, the efficiency and depth of active diagnosis are improved; according to the method, automatic closed loop from problem discovery to problem solving is realized, and a structured cognitive repair path can be dynamically generated and executed according to a diagnosis result, so that the overall efficiency of personalized learning is improved.

The invention belongs to the technical field of customer service seat service, particularly relates to a novel customer service queuing method based on joint participation of AI and manpower, and aims to solve the problems that the existing AI can only process simple problems and complex problems and needs to transfer human seats, and the number of AI seats can be adjusted in real time based on system load (such as elastic expansion of cloud resources). In order to solve the problems that in the prior art, the number of human seats is relatively fixed, the following scheme is proposed and comprises the following steps: S1, preparing a queuing system and receiving a request; s2, classifying incoming requests, and identifying problem complexity; s3, distributing the requests to queues with different priorities according to a classification result, and determining a routing strategy; s4, processing the request according to the strategy; s5, the system state is monitored in real time, and the number of the AI seats is adjusted in real time, the waiting time can be shortened during peak load (dynamic AI capacity expansion), and the cost can be reduced during low peak load (dynamic capacity reduction).