84 results about "Exception analysis" patented technology

The embodiment of the invention provides a code exception analysis method and device, a storage medium and a program product. In the embodiment of the invention, in the preset plug-in, the global knowledge graph is constructed through the logic syntax tree of the plurality of original business codes, so that intelligent anomaly analysis is carried out on the modified to-be-detected codes, multi-language and heterogeneous programming styles and complex dependency limitation are broken through, and cross-language and cross-file analysis is supported; change code snippets and associated influence code snippets thereof are accurately identified, and a data basis is tamped and analyzed; the analysis depth is deepened and the accuracy is improved through a multi-dimensional anomaly analysis large model and four-dimensional collaborative analysis in combination with an adaptive review rule and a knowledge graph; and finally, performing correction based on the generated repair scheme. Through the technical fusion of an MCP protocol, a multi-AI model, a syntax tree and a knowledge graph, the high efficiency, accuracy and real-time performance of code examination and repair are realized, and the service development quality and the system operation stability are remarkably improved.

The invention discloses an electric power communication analysis system and method based on big data, and the method comprises the steps: collecting multi-source heterogeneous data, carrying out the sensitivity grading, and generating labels; gathering the data to a big data platform, and completing storage, partitioning and index construction; an asynchronous main control chain mechanism is constructed, high-optimal data is dispatched for rapid anomaly judgment, and other data is processed in parallel; performing desensitization mapping on the high-sensitivity data to generate a short-time mapping bill and performing desensitization analysis; issuing a local task for the low-confidence exception, collecting backflow data, and verifying and determining a high-risk event; restoring the sensitive data in the authorization window, and destroying the bill and the secret key after abnormity analysis is completed; and triggering network regulation based on an analysis result, and recording the whole process to an audit log. By introducing an asynchronous scheduling and reversible desensitization mechanism, high-efficiency anomaly analysis and whole-process traceability of the electric power communication big data on the premise of ensuring safety and compliance are realized.

The embodiment of the invention provides an information processing method and device, and the method comprises the steps: obtaining an application exception index of a target application; extracting application exception information corresponding to the target application according to the application exception index, performing information processing on the application exception information in at least one exception analysis dimension, and determining an application exception type of the target application; creating an application repair strategy for the application exception type, and determining application code information corresponding to the target application; and inputting the application repair strategy and the application code information into a code repair model for processing to obtain an application repair code, and performing exception repair on the target application by using the application repair code.

The invention discloses an application debugging method and device, equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining debugging real-time streaming data corresponding to an application debugging process, and detecting whether the debugging real-time streaming data is abnormal or not; if yes, extracting real-time stream abnormal data in the debugging real-time stream data, and analyzing the real-time stream abnormal data according to a preset knowledge base to obtain an abnormal analysis prompt word; inputting the exception analysis cue word into a real-time data processing full-stack agent to obtain an exception problem summary, an exception analysis reason and an exception repair suggestion output by the real-time data processing full-stack agent; and debugging the application debugging process based on the exception problem summary, the exception analysis reason and the exception repair suggestion. According to the method, the development threshold is reduced through the intelligent agent, the knowledge base and the like, so that error checking and problem repairing in the application debugging stage are accelerated, meanwhile, dependence on experts is reduced, and the development efficiency of the real-time data processing application is improved.

The invention relates to the technical field of service management, in particular to a rule engine dynamic optimization method and system based on real-time service requirements, and the method comprises the steps: obtaining an initial service index in a service scene, constructing a first test parameter set according to the initial service index, operating a test, and collecting first operation data; in a preset time window, continuously monitoring the initial business indexes, fusing dynamic factors in the continuous monitoring process into the first test parameter set to generate a second test parameter set, running the test again, and collecting second running data; performing difference quantitative analysis on the first operation data and the second operation data to obtain a rule operation deviation vector; inputting the engine exception data into a preset rule engine exception analysis model to obtain an engine exception score; in response to the fact that the engine exception score exceeds a preset exception threshold value, the continuous operation duration of an existing rule engine is obtained, the continuous operation duration and the engine exception score are input into the rule engine optimization model, and a rule engine optimization strategy is obtained.

The invention discloses a cloud platform network equipment strategy management method, which comprises the following steps: acquiring demand data of a current monitoring time node and a network equipment strategy, performing association analysis on multiple pieces of demand data, and determining multiple associated demand data sets according to an analysis result; matching the network equipment strategies in each associated demand data set, judging whether an exception exists or not according to a matching relationship, if so, determining an exception type and an exception fragment, constructing an exception fragment set, and determining a plurality of optimization strategies of the exception fragment according to a preset exception analysis model; obtaining a plurality of simulation network equipment strategies based on the plurality of optimization strategies, generating a risk assessment value according to a preset risk assessment model, and selecting an optimal simulation network equipment strategy and an optimal optimization strategy; and according to the optimal optimization strategy, generating an actual network equipment strategy and issuing a management instruction, thereby effectively solving conflicts between network equipment strategies, providing security equipment strategy optimization suggestions, and ensuring security and stability of a network environment.

The invention discloses an AI-based micro-service system exception handling method and system and a storage medium, and belongs to the technical field of software exception monitoring. The method comprises the following steps: in an exception real-time capturing stage, deploying a global exception intercepting component at a micro-service gateway or each service framework layer, and generating an exception report; in the AI anomaly analysis stage, the anomaly report is analyzed, and a solution thought or a code repair suggestion is generated; an active alarm and notification stage: notifying development, operation and maintenance personnel according to an AI analysis result; meanwhile, all abnormal information is pushed to a monitoring panel; in the automatic repairing and deploying stage, exception handling is carried out, and dynamic deploying and system self-healing of exceptional patches are achieved; in the feedback learning and iterative optimization stage, exception processing results are collected, and the diagnosis accuracy and the repair suggestion quality are improved by continuously learning new exception cases and processing modes. According to the invention, abnormal information from different services is collected in a unified manner through a global interception mechanism, and the omission risk caused by decentralized processing is eliminated.

The invention discloses a log processing method and device, equipment and a medium. The method comprises the following steps: acquiring a log buffer area corresponding to each application program in a vehicle; wherein the log buffer area comprises a main buffer area and a backup buffer area; if the abnormal event of any application program is detected, executing abnormal response logic on the log buffer areas of all the application programs based on the abnormal event to obtain global log data of the abnormal event and storing the global log data; and when detecting that an exception analysis condition is met, performing exception analysis according to the stored global log data. According to the technical scheme, the log data among the application programs can be comprehensively captured when any application program is abnormal, so that the global log data is obtained, the real-time performance and integrity of log data capturing are improved, and abnormity positioning and fault analysis are facilitated.

The invention discloses a fault self-check recovery method and system based on a cloud deployment system, and the method comprises the steps: carrying out the multi-dimensional deep detection of the operation states of an operation system layer, a database layer and an application layer of a cloud platform through constructing an all-dimensional real-time monitoring system, and automatically triggering an adaptive recovery mechanism once an abnormality is found, and continuous and stable operation of the system is ensured. The matching tool integrates core modules of state acquisition, anomaly analysis, recovery execution, log recording and the like, collaboratively realizes real-time acquisition of operation data, accurate anomaly identification through an intelligent algorithm, rapid matching and implementation of a recovery scheme, and records logs in the whole process for troubleshooting and system optimization. According to the tool, server nodes, database states, service accessibility and webpage availability are checked in sequence, emergency processing is started immediately when abnormity is found, the stability and reliability of a cloud platform are remarkably improved, and the manual intervention cost is reduced.

The invention relates to a computing power anomaly detection method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring abnormal heterogeneous computing power task data and heterogeneous computing power task detection data; determining abnormal computing power container information and abnormal hardware node information from the abnormal heterogeneous computing power task data; performing software exception analysis processing on the basis of the exception computing power container information to obtain software dimension exception information, performing hardware exception analysis processing on the basis of the exception hardware node information to obtain hardware dimension exception information, and comparing the heterogeneous computing power task detection data to obtain first exception detection information and second exception detection information; therefore, the calculation power anomaly detection rate is determined. According to the method, the detection rate of the heterogeneous computing power task detection data in the heterogeneous computing power task execution process can be determined, so that the stability of the computing power service is effectively improved through detection rate analysis.

The invention discloses an enterprise business application operation and maintenance situation awareness system, and belongs to the technical field of business operation and maintenance, and the system specifically comprises a business topology construction module which is used for collecting inter-service call logs in real time through a data collection agent disposed on a business application server; the exception propagation analysis module is used for receiving the real-time dependency relationship graph generated by the service topology construction module, and the dependency relationship graph is stored in a graph database in a digraph structure; the visual display module is used for reading the current topological state and the anomaly analysis result from the graph database, nodes and edges are rendered by adopting a force-oriented layout algorithm, the node radius is in direct proportion to the resource occupancy rate, and the edge width is in inverse proportion to the calling success rate; according to the invention, efficient perception and accurate presentation of the operation and maintenance situation of the enterprise business application are realized, and the operation and maintenance efficiency and decision accuracy are improved.

The invention discloses an information security detection method and device, equipment, a medium and a program product. The method comprises the following steps: acquiring user access information and data access abnormal information in a to-be-detected data access period; performing anomaly analysis on the user access information to obtain a user access information analysis result; performing exception analysis on the data access exception information to obtain a data access exception information analysis result; and based on the user access information analysis result and the data access abnormal information analysis result, performing information security detection on the to-be-detected data access time period to obtain a target information security detection result. According to the method and the device, the abnormal access behavior of the user and the abnormal condition of data access can be effectively detected, so that the information security in the data access process is comprehensively detected.

The application belongs to the technical field of photovoltaic power generation equipment fault monitoring, and discloses a kind of distributed photovoltaic power generation equipment intelligent monitoring system, including light intensity equipment exception monitoring module, control equipment exception monitoring module, drive equipment exception monitoring module, tracking system exception analysis module, support structure data acquisition module, support structure exception analysis module and fault cause pointing identification module.The application analyzes the abnormal conditions of tracking system and support structure, and then comprehensively evaluates the health status of each automatic tracking photovoltaic power generation device.This analysis method takes into account the tracking system and the support structure, covering the key aspects of device operation and support, which greatly improves the accuracy of evaluation, accurately grasps the real situation of the equipment, discovers potential problems in time, formulates more targeted maintenance strategies, effectively ensures the stable operation of photovoltaic power generation devices, improves power generation efficiency and reduces equipment failure risk.

The invention relates to the technical field of computers, in particular to an application exception handling method, system and equipment based on agent arrangement, which can efficiently handle application exception problems. The application exception handling method based on agent arrangement comprises the steps that by means of agent arrangement, an exception handling workflow comprising a plurality of agent units capable of being arranged is formed in a visual mode for an application exception condition, and a flow engine of the exception handling workflow comprises a control node and a task node; for the captured application exception information, exception information features are extracted through exception analysis logic by using an exception recognition agent unit, and the influence range of the application exception is delimited through an entity relationship graph to form an exception analysis result to be output to a front-end visual interface or pushed to a collaborative agent unit; and establishing an agent co-processing system comprising a co-processing agent unit based on the exception analysis result, matching a processing scheme for the application exception information according to a co-processing strategy, and processing the exception condition.

The invention relates to the technical field of software running exception analysis, and discloses an AI-based software running exception analysis method and system, performance information and text information during software running are collected and matched, a judgment value P is calculated according to the performance information, and when the judgment value P is 0 or a negative number, the software running exception is analyzed. The duration data SJ and the occurrence frequency data CS are extracted for judgment, when a judgment value P is a positive number and the judgment value P is larger than or equal to a fault threshold GY, a detection instruction is sent, when the instruction is sent, the fault problem is analyzed, the fault position is positioned, a repair strategy is called, and fault isolation and repair are carried out; according to the method, the performance information and the text information during software operation are acquired, so that when the software operation has a problem, the fault can be known, and the fault can be found and processed in time in the early stage, and the situation that the software is directly and abnormally broken is avoided.

The invention relates to the field of big data, and provides an anomaly detection and repair method and system for a big data task and a medium. The big data task anomaly detection and repair method comprises the steps that task information of a big data task with an abnormal task state is obtained, wherein the task information comprises a task log; obtaining an execution code of the big data task through a decompilation tool, and analyzing the execution code and the task log through an exception analysis module to identify an exception problem; in response to the fact that the exception problems are data source exception and code exception, exception code snippets, data source information and exception types are analyzed through a conjoint analysis module to determine exception root causes, the exception code snippets are recognized through an exception analysis module, the data source information is determined by executing codes, and the exception types are determined according to task logs; and triggering abnormal code repair and / or data processing optimization according to the abnormal root cause.

The invention provides an exception analysis method and system and a storage medium, and the method comprises the steps: constructing an exception large model and an exception knowledge base in a cloud in advance, receiving exception data uploaded by a vehicle terminal in real time, and when exception type information exists in the exception data, matching the exception data according to the exception knowledge base, obtaining a final abnormal conclusion; when the abnormal type information does not exist, inputting the abnormal data into an abnormal large model for reasoning, and matching the abnormal data by adopting the abnormal knowledge base based on a reasoning result to obtain a final abnormal conclusion; and issuing the final abnormal conclusion to the vehicle terminal. According to the method provided by the invention, the technical problems of slow system operation, large resource occupation and dead halt caused by abnormal data of the vehicle-mounted terminal are effectively solved, and the safety and reliability of the vehicle-mounted terminal system are effectively improved.

The invention provides a transportation strategy optimization method and system applied to cold-chain transportation, and the method comprises the steps: firstly obtaining a transportation data set composed of equipment operation parameters and transportation environment data of transportation equipment in a transportation period in a cold-chain transportation process, and then carrying out the feature extraction of the transportation data set; the equipment feature set and the environment feature set are input into a preset exception analysis model for joint exception analysis, an exception analysis result containing an equipment exception type and an environment exception type is generated, and the equipment exception type and the environment exception type are generated according to the exception analysis result and a preset report generation rule. According to the method, a transportation abnormality analysis report including abnormal condition description, occurrence time periods and influence evaluation is generated, and finally, a transportation optimization strategy for transportation equipment maintenance and transportation environment regulation and control is generated based on the report and historical transportation data and is fed back to a cold chain transportation management system, so that the cold chain transportation quality and efficiency can be improved, and the cargo safety is guaranteed.

The embodiment of the invention provides an anomaly detection method and device, equipment, a storage medium and a program product. The method comprises the steps of obtaining function call data corresponding to target equipment; under the condition that the target detection instruction is detected, determining target abnormal example information corresponding to the target detection instruction according to the target knowledge base; the target knowledge base comprises a plurality of historical abnormal examples; the target exception example information comprises information of at least one historical exception example associated with the target detection instruction; and according to the target detection instruction, performing matching analysis on the target exception example information and the function call data to obtain target exception information corresponding to the function call data. Therefore, the electronic equipment can realize automatic anomaly analysis of the function call data based on the target knowledge base, can identify potential anomaly risks, improves the instantaneity and comprehensiveness of anomaly detection, and can ensure the stability and reliability of system operation.

The invention provides an exception analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: responding to an exception alarm event of an independent station, and determining a time window of the occurrence of the exception alarm event and an exception service corresponding to the exception alarm event; obtaining service data of the abnormal service in the time window, wherein the service data indicates a change trend of a working condition of the abnormal service in the time window; acquiring a log and a topological structure of the abnormal service; performing structured processing on the service data based on the topological structure and the log to obtain a knowledge graph corresponding to the abnormal alarm event; and outputting root cause information of the abnormal alarm event according to a preset generative model based on a preset prompt word and the knowledge graph. According to the invention, the accuracy of analyzing the fault root cause of the independent station can be improved.

The embodiment of the invention provides a database abnormal root cause positioning method and device, equipment, a medium and a program product, and relates to the field of financial science and technology or other related fields. The method comprises the steps of collecting performance data of at least one dimension of a database according to a set period; for multiple items of data of the same index in the performance data, determining alternative abnormal data based on values of the multiple items of data; clustering the alternative performance data according to at least one dimension, and determining candidate performance data based on a clustering result; determining abnormal performance data from the candidate performance data through threshold comparison and / or mode matching, and determining an abnormal dimension according to the abnormal performance data; and generating and feeding back an exception analysis result of the database based on the exception performance data and the exception dimension thereof. By analyzing the performance data of at least one dimension of the database, automatic database exception analysis and exception positioning are realized, and the efficiency and accuracy of exception analysis are improved.

The invention provides an exception analysis method applied to programming and a related device, and the exception analysis method applied to programming comprises the steps: analyzing a currently written code, and determining whether the code is abnormal or not; and in response to the exception, analyzing the exception code, and explaining an exception reason of the exception code by utilizing a target language. According to the abnormality analysis method applied to programming, the encoding abnormality can be analyzed in real time in the programming process, and the timeliness is high; exception codes are explained and analyzed through the target language, high-precision answers aiming at the exceptions are generated, and understanding is easy.

An E-commerce intelligent cloud-based information distribution system includes a distribution request unit, a request monitoring unit, a request identification unit, an information distribution unit, a cloud server unit, an exception analysis unit, an exception recording unit, an exception processing unit, an exception feedback unit, a cloud-based information receiving unit, and a central control processing unit. The request identification unit includes a data receiving module, a data element extraction module, a data queue sending module, a task requirement extraction module, a task adaptive processing module, and a data sending module. The present disclosure sends the could-based information into the corresponding sending queue based on the characteristics of the received could-based information and the requirements of different platforms; and then the could-based information is adaptively tailored according to the link status and network bandwidth, and the adaptive distribution of the could-based information is realized under the constraints of the task scenario.

The embodiment of the application provides a kind of based on digital model's converter station unmanned plane cruise route collaborative processing method and system, obtain network knowledge learning data sequence including multiple template collaborative control data and each prior abnormality mark corresponding to multiple template collaborative control data;Load basic exception label diagnostic network, and the basic exception label diagnostic network is the exception label diagnostic network generated by knowledge learning long short-term memory network model based on initialization weight parameter;Based on knowledge domain self-adaptability training, the prediction unit of the basic exception label diagnostic network is learned by network knowledge learning data sequence, and the exception analysis network is obtained;Prediction unit includes one or more multilayer perceptron;According to exception analysis network, abnormal node positioning is carried out, and the high-performance exception analysis network is generated using the technical solution, so that subsequent abnormal node positioning accurate, fast can be realized.

The invention discloses a fault root cause positioning method and device for certificate management, equipment, a medium and a product. The method can be applied to financial science. The method comprises the following steps: acquiring server state data and certificate operation related data of a certificate management server, acquiring certificate transmission related data of certificate transmission link network equipment, and acquiring certificate calling related data of certificate access application equipment in a current detection time period; performing data exception analysis on the server state data, the certificate operation related data, the certificate transmission related data and the certificate calling related data, and determining a certificate exception node, a certificate exception index and exception associated data; determining a node exception propagation path of the certificate exception node; the node exception propagation path comprises a plurality of exception nodes influenced by the certificate exception node; and generating a fault root cause and a disposal scheme in the certificate management process according to the certificate exception index, the exception associated data and each exception node in the exception propagation path.

The invention provides a USB (Universal Serial Bus) equipment exception handling method and electronic equipment. The USB equipment exception handling method comprises the following steps: creating a storage space to store USB equipment information; the method comprises the following steps: reading USB equipment information to create an equipment linked list during startup; judging whether the USB equipment is successfully connected or not according to the equipment linked list; if the connection is successful, entering a standby state, monitoring the USB equipment, and performing recovery operation on the USB equipment when the USB equipment is abnormal; and if the connection is unsuccessful, uploading the abnormal log to a system server, and generating a pop-up box to prompt the user. According to the method, automatic recovery, exception log storage, exception analysis and evaluation can be carried out after the USB equipment is abnormal from a user to a technology development end. In an environment which is not affected by a network and is poor in anti-interference capability, automation is realized from a bottom layer to background service, and the product can be continuously optimized while manpower and material resource investments are reduced.

The invention discloses an exception analysis method and device, equipment, a storage medium and a program product, and relates to the technical field of computers. The method comprises the following steps: acquiring account log data corresponding to a first account; extracting a sequence semantic feature representation corresponding to the account log data, and obtaining a directed graph network corresponding to the account log data; obtaining graph network semantic feature representation corresponding to the directed graph network; based on the sequence semantic feature representation and the graph network semantic feature representation, account semantic feature representation corresponding to the first account is obtained, and the account semantic feature representation is used for analyzing the abnormal condition of the first account. According to the method, the sequence semantic feature representation and the graph network semantic feature representation can be combined, the link information among the multiple execution events is combined under the condition that the time sequence information is not ignored, more accurate account semantic feature representation is obtained, and the analysis accuracy of the abnormal condition of the first account can be improved. The method and the device can be applied to various scenes such as user management scenes and security detection scenes.

The application discloses an FTTR network data exception analysis method, system and equipment, which is applied to an FTTR-B network and comprises the following steps: acquiring local area network history behaviors and Internet history behaviors of a target terminal device in a target FTTR network; obtaining a target terminal device portrait according to the local area network history behaviors and the Internet history behaviors; analyzing real-time data in the target FTTR network to obtain a target behavior of the target terminal device; and judging whether the target behavior is abnormal according to the target behavior and the target terminal device portrait. At least, the problem that many enterprises access the Internet through FTTR-B while carrying out local area network networking, and it is difficult to discover and locate data exceptions across networks in time and to flexibly adjust monitoring strategies to adapt to business dynamic changes if only relying on traditional monitoring mechanisms is solved.

The invention relates to an aircraft component test report analysis system based on an anomaly inference model, and relates to the technical field of component testing, and the aircraft component test report analysis system comprises a data analysis module which is configured with a file format analysis strategy to perform file format feature extraction on a test file, carrying out aircraft part test information analysis on the test file by matching a corresponding analysis step in the format analysis database so as to generate a test report; the file caching module is configured with a multi-stage data caching strategy, reads, writes and pre-caches the test file through a pre-constructed memory, file and database caching architecture, and keeps the data read-write efficiency and the system response speed within a preset good threshold range; and the exception analysis module is configured with an exception report identification model and is used for identifying and analyzing the test report through similar fault identification logic and a fault analysis engine so as to determine exception test information in the test report. The method has the effect of improving the analysis efficiency and accuracy of the test report of the aircraft component.

The embodiment of the application belongs to the technical field of process optimization, is applied to the field of intelligent reporting of supervision data, and relates to a supervision data pushing and abnormal self-checking method, device and equipment and a storage medium thereof, and comprises receiving supervision request data pushed and reported by each supervised party. Through repeated abnormal self-checking and abnormal automatic repairing, supervision request data examination is performed, the normativity of supervision data reporting is further ensured, abnormal data is avoided from being transmitted to a supervision department, meanwhile, an automatic mode is adopted, abnormality can be automatically detected and repaired, manual abnormality analysis and repair are not needed, the workload of manual abnormality screening is reduced, manual consumption is saved, and supervision reporting efficiency and accuracy are improved.