97 results about "Secondary analysis" patented technology

The invention discloses an equipment preventive maintenance and diagnosis method based on multi-dimensional data verification, relates to the technical field of equipment preventive diagnosis, and solves the technical problems that fault reasons are difficult to comprehensively and deeply analyze, and maintenance measures are lack of pertinence due to the fact that the fault reasons are often misjudged or cannot be positioned. According to the method, the fault diagnosis model is constructed, the adaptation algorithm is adopted for different types of data, the diagnosis accuracy of the model to equipment faults and the adaptability of the model to complex working conditions are improved, the equipment fault type and the abnormal state can be rapidly and accurately recognized, and the fault diagnosis accuracy is improved through the methods of fault phenomenon matching, parameter correlation analysis, historical data deep backtracking and the like. According to the method, fault reasons can be accurately determined, the performance degradation trend and potential risks of the equipment can be effectively identified in combination with a hybrid similarity measurement method, correlation among data is further mined through a secondary analysis mechanism, the potential risks are accurately pre-judged in combination with historical data, and real preventive maintenance is achieved.

The invention relates to an anti-electricity-stealing monitoring method and device based on an intelligent universal meter, equipment and a medium. The method comprises the following steps: acquiring real-time electric sampling data of a universal meter, and preprocessing the data to obtain electric characteristic data; carrying out electricity stealing feature extraction on the electricity feature data by utilizing an edge electricity stealing detection model, and carrying out preliminary judgment on an electricity utilization type to obtain a preliminary judgment result; if the preliminary judgment result is at least one of an electricity larceny event and reverse feed, using a cloud electricity larceny detection model to perform secondary analysis on the electricity characteristic data to obtain an abnormal probability; and if the abnormal probability exceeds a preset threshold, generating a corresponding alarm work order, and pushing the alarm work order to a supervision platform. By adopting the method, the field acquisition capability of the intelligent multimeter can be fully combined, the local and cloud computing characteristics are combined, and the recognition and monitoring of electricity stealing behaviors such as low-current electricity stealing and reverse feed are effectively enhanced through a multi-source feature extraction and judgment mechanism.

The invention discloses a waistband type falling protection early warning device for old people living alone, and belongs to the technical field of intelligent wearable equipment. The problems that an existing device is single in early warning mode and cannot effectively guarantee the safety of old people living alone are solved, corresponding action results are matched for various data of the old people through the convolutional neural network and the lightweight decision tree model, and if a preliminary judgment result conforms to a normal mode, a judgment result is directly output; if not, triggering a secondary analysis mechanism to further judge whether the old people fall down or not; the GPS positioner is also used for analyzing whether falling behaviors occur at the same position for many times, and if a high-risk position is found, when the old people approach the high-risk position, the warning lamp and the alarm are used for reminding and paying attention to action behaviors; the fall detection accuracy is improved, the possibility of false alarm and missing alarm is reduced, the old people can be actively prevented from falling again in a high-risk area, and a more comprehensive safety guarantee is provided for the old people living alone.

The invention discloses an AI-based network log analysis processing method, which comprises the following steps of: firstly, collecting network equipment log information through a collection script supporting multiple protocol modes, and writing the collection script and deploying and starting after determining equipment and protocol types; thirdly, carrying out preliminary classification, data supplementation and formatting processing on the original logs; and then, sending the processed log data to an AI large model for semantic analysis, including deep understanding, basic classification, secondary analysis and providing of processing suggestions. An analysis result is stored in a data think tank for historical comparison, and an inconsistent result is manually confirmed and corrected; when the network equipment triggers a fault alarm, calling the data think tank to supplement alarm content; and meanwhile, equipment related data handbooks provided by manufacturers are uploaded regularly, the analysis accuracy of the AI model is corrected, verification and testing are carried out, it is ensured that the scheme can comprehensively and efficiently collect and process logs, accurately analyze faults and continuously optimize the model, and effective support is provided for network fault processing.

The invention provides a welding spot cavity and bridging defect intelligent automatic test system, and relates to the technical field of defect detection, and the method comprises the steps: a data collection module is used for collecting image data of a to-be-detected welding spot, carrying out the standardization processing, and obtaining standard image data; the void defect detection module is used for identifying a low-density region in a standard image data welding spot, calculating an area proportion, and if the area proportion exceeds a preset area threshold value, judging that the welding spot is a void defect; the bridging defect detection module is used for calculating the minimum distance between standard image data welding spots, and if the minimum distance is smaller than a preset distance threshold value, a bridging defect is judged; the confidence coefficient analysis module is used for obtaining the detection confidence coefficient and re-collecting image data for secondary analysis of a detection result lower than a confidence coefficient threshold value; and the report generation module is used for generating a structured detection report comprising the defect type and the defect severity level. The technical problem that in the prior art, welding spot cavities and bridging defect detection accuracy is not high is solved.

The invention relates to the technical field of data reasoning, in particular to an intelligent dispute analysis system based on big data, and the system comprises an event collection module, a dispute analysis module, a scheme generation module, an emergency scheme module and an auxiliary decision generation module. Generating an original data set; extracting event key elements of the original data set to obtain a preliminary analysis report; in combination with the attribution feature data and the party background data, carrying out attribution secondary analysis on the preliminary analysis report to generate a personalized mediation scheme; when an emergency triggering condition is identified, rescue resource data are integrated based on an event geographic position, and an emergency disposal plan is automatically generated; and generating an auxiliary decision report based on the personalized mediation scheme and the emergency disposal plan. The dispute solving efficiency can be improved.

The invention discloses a slope anchor rod prestress monitoring system and method, and relates to the technical field of slope abnormity supervision. Comprising a data acquisition module, an acquisition and analysis module, a secondary analysis module and an anomaly analysis module, wherein the data acquisition module is used for acquiring multipoint stress data of a slope anchor rod, slope soil data and slope environment data and preprocessing the acquired data; according to the technical key points, prestressing forces at different positions of the side slope anchor rod can be collected, then the collected prestressing force data at different positions of the side slope anchor rod are evaluated, the attenuation of the prestressing force data is researched, whether the collected data are abnormal or not is further analyzed, and whether the data are abnormal or not can be found in time; therefore, the conditions of low efficiency and high cost caused by inaccurate analysis result, repeated acquisition and analysis due to abnormal acquired data can be effectively avoided, the use effect is good, and the method has a good use prospect.

The invention relates to the technical field of uranium mineralization prediction, in particular to a uranium ore positioning method for oil and gas dissipation channel control, which comprises the following steps: for a drilling point preliminarily meeting a uranium mineralization standard, determining whether a temperature range of a gas generation threshold meets a mineralization achievement condition or not, and transferring a preliminary drilling area according to a fluid activity path; the direction of moving the preliminary drilling area is determined, and the initial drilling parameters are adjusted; fluid property classification is carried out, and it is determined that the uranium metallogenic potential of the paleoenvironment where the sample is located meets expectation or secondary analysis of the uranium metallogenic potential is needed when the sample is formed; determining composition characteristic types of the samples, judging whether the causes of the samples are related to biological action or not according to the proportions of the samples in different composition characteristic types, and adjusting a judgment standard for determining uranium mineralization potential; and when the uranium mineralization potential meets the expectation or the cause of the sample is irrelevant to the biological action, the coexistence of the uranium ore and the hydrocarbon inclusion is verified through drilling. According to the invention, efficient uranium ore positioning is realized by identifying the oil-gas dissipation channel and the associated ore control elements.

The invention provides a traffic load monitoring management method and system for an electric power communication network, and the method comprises the steps: carrying out the initial multilayer analysis of a collected traffic data package based on a DPI probe, and obtaining the initial analysis data of the traffic; performing windowing processing on the flow initial analysis data based on the time sliding windows to obtain a flow load index and a service load index corresponding to each time sliding window, and associating the flow load indexes with the service load indexes to form structured flow feature data; inputting the structured traffic feature data into an anomaly detection model to obtain an anomaly recognition result output by the anomaly detection model; carrying out secondary analysis on an original abnormal data packet extracted from the traffic data packet based on an abnormal identification result, associating with the traffic primary analysis data, and constructing an abnormal traffic traceability chain; and determining a load regulation and control strategy based on the abnormal traffic traceability chain in combination with a pre-constructed traffic load regulation and control decision library. The fault recovery efficiency of the power communication network is improved.

The invention relates to a test central control method and system for a test station of a transformer manufacturer, and belongs to the technical field of test control. Control demand information of current test equipment is acquired, control equipment is initially selected for control according to the control demand information of the current test equipment, and an initialization control result is generated; the method comprises the following steps: initializing a control result of each piece of control equipment, acquiring real-time state data information of each piece of control equipment, performing secondary analysis on the initialized control result according to the real-time state data information of each piece of control equipment to generate a secondary control result, and finally performing control interference analysis on the secondary analysis control result to generate a final control result. And the test equipment is controlled according to the final control result. According to the condition of the control equipment, the phenomenon of misoperation when the test equipment needing to be controlled in the central control network system of the test station of the transformer manufacturing plant is controlled is avoided, so that the control equipment can be in order.

The present invention discloses a method and system for intrusion analysis based on web logs. The analysis method includes: cutting the original log into fields according to the default delimiter and the default quote character; automatically identifying the field format, performing rapid matching of the field format, parsing and storing in a database; reading the stored logs in batches and performing log matching rule detection; updating the logs and writing them back to the database; aggregating the logs to generate web attack events and determine whether the intruder's attack was successful; generating and submitting a protection and processing report based on the web attack time and the analysis results and the impact range of the intrusion confirmed manually. The present invention realizes intrusion analysis of the attacker's IP address by cutting the web logs, uniformly parsing, rule matching detection and log aggregation. The present invention adopts a method combining automatic detection and manual confirmation, which has the advantages of high efficiency, high result accuracy, high log parsing strength and convenience for secondary analysis, thereby greatly improving the efficiency of web analysis.

The application discloses a quantitative analysis method of tobacco medium-polarity VOCs, which comprises the following steps: S1, inert gas is used to purge tobacco, and meanwhile, the tobacco is heated and sampled, so that the medium-polarity VOCs in the tobacco are collected; and S2, the medium-polarity VOCs in the tobacco are enriched by using MWCNTs-COOH / rGO, then, the medium-polarity VOCs are subjected to thermal desorption, and then, the medium-polarity VOCs are subjected to secondary enrichment and secondary analysis by using a cold trap, and finally, the medium-polarity VOCs are subjected to quantitative analysis by using GC-MS. When the MWCNTs-COOH / rGO is used as the adsorption medium of the thermal desorption of the purge and trap method, the flow rate, time and secondary enrichment temperature of the inert gas purging during the enrichment of the medium-polarity VOCs in the tobacco are simultaneously controlled, so that the quantitative analysis method of the medium-polarity VOCs in the tobacco is established. The enrichment effect of the medium-polarity VOCs in the tobacco is improved, and the accuracy of the quantitative analysis of the medium-polarity VOCs in the tobacco is also improved.

The present application relates to the technical field of flow monitoring, and discloses a method and system for real-time monitoring of flow in an At-211 column separation process, the method comprising: collecting the conductivity of eluent in the outlet pipeline of the At-211 chromatographic column in real time, continuously analyzing the conductivity, and generating a state flag; wherein when it is detected that the eluent is switched to anhydrous ethanol phase, the state flag is valid; otherwise, the state flag is invalid; by collecting the conductivity and generating the state flag, the timing of anhydrous ethanol phase switching is accurately determined, the collected pressure time series data is analyzed to generate a steady-state pressure value, then secondary analysis is performed to obtain a pressure memory value, the stable state of pressure and the continuous influence of flow are comprehensively captured, and finally a flow stability index is generated, which can evaluate the flow state of the whole alcohol phase elution process. The present application does not need to rely on the continuity of the conductivity signal, effectively filters transient interference, and improves the accuracy of flow monitoring.

A determination system includes: a log obtainer that obtains log information; a preprocessor that generates preprocessed log information from the log information; a primary analyzer that generates primary determination result information by performing primary analysis on the preprocessed log information; a prompt generator that generates a prompt for generative artificial intelligence (AI) based on the preprocessed log information; a secondary analyzer that performs, as secondary analysis, a process of obtaining secondary determination result information by inputting the prompt to the generative AI; an overall determiner that generates overall determination result information based on the primary determination result information and the secondary determination result information; and an outputter that outputs a determination result report that includes a determination result indicated by the overall determination result information.

The invention relates to the technical field of model design, in particular to a model design method and system for a long-distance steam supply pipeline. The method comprises the following steps: acquiring the positions of a pipeline starting point and a pipeline target point; performing mid-distance landform analysis based on the pipeline starting point and the pipeline target point to generate mid-distance landform division data, the mid-distance landform division data including cross-road landform data and cross-river landform data; performing basic pipeline modeling according to the positions of the pipeline starting point and the pipeline target point, and generating basic pipeline model design data; and secondary internal stress analysis of the pipeline sleeve is carried out on the basic pipeline model design data through the cross-road landform data, and pipeline cross-road internal stress data are generated. According to the method, the problems that in the prior art, under the complex terrain, the pipeline design precision is insufficient, stress analysis is limited, and comprehensive optimization is insufficient are solved by introducing an optimization design method combining middle-distance landform analysis, pipeline stress secondary analysis and natural vibration analysis.

The application provides a data processing method, device, equipment and medium. Data of multiple heterogeneous systems is collected multiple times, and the data of the multiple heterogeneous systems collected each time is transmitted to an analysis system respectively. Each analysis system runs different unsupervised learning algorithms and outputs corresponding analysis results. Each analysis result includes a first interworking heterogeneous system matched by each heterogeneous system. Then, each analysis result is integrated into a classification matrix. Rows of the classification matrix include matching results of each heterogeneous system under different analysis systems, and columns of the classification matrix include matching results of each heterogeneous system under each analysis system. Secondary analysis is performed on data in each row of the classification matrix to analyze analysis results of each heterogeneous system under different analysis systems, and a second interworking heterogeneous system matched by each heterogeneous system is obtained, so that an interworking heterogeneous system can be effectively obtained.

This invention relates to a method and system for disaster overlay analysis in nuclear power plants, comprising the following steps: acquiring standard specifications and experience feedback data of the nuclear power plant; conducting preliminary screening analysis based on the standard specifications, experience feedback data, and screening criteria to obtain a preliminary screening list of disaster overlays; and conducting secondary analysis based on the preliminary screening list of disaster overlays and in conjunction with a list of overlay disaster analysis scopes to obtain a disaster overlay list. This invention, through preliminary screening analysis, obtains a preliminary screening list of disaster overlays, achieving a comprehensive and effective review of possible disaster overlay types and avoiding omissions; simultaneously, through secondary analysis, it achieves a comprehensive and effective review and determination of the disaster overlay types that need to be considered, further ensuring the comprehensiveness and effectiveness of the disaster overlay analysis and avoiding omissions.

The invention relates to the technical field of data processing in an automatic recruitment system (ATS), in particular to a double-stage asynchronous processing-based resume analysis optimization method in the ATS, which comprises the following steps: S1, a primary analysis stage: quickly extracting key fields in a resume by adopting a lightweight analysis module formed on the basis of regular rules, entity recognition and other technologies, and carrying out secondary analysis on the key fields in the resume; comprising name, gender, contact information, graduation colleges, educational background and professional information; the module has high real-time performance and can return an analysis result within a second level; s2, user response and business promotion: returning a primary analysis result to a user interface in real time and storing the primary analysis result into a system, and supporting the user to carry out subsequent operation without delay, the user experience is remarkably improved, the user does not need to wait for a long-time analysis process, and non-inductive import of'completion once submission 'is realized; the analysis quality is greatly improved; the accurate extraction of deep and complex fields is realized through a multi-modal large model, and the data basis of the subsequent man-post matching and screening process is improved.

The present invention discloses a somatosensory interactive display system based on a depth camera, which relates to the field of somatosensory interaction technology; the system includes a data retrieval module, a parameter analysis module, a secondary analysis module, an image processing module and a verification and display module: the data retrieval module: extracts the user's most recent N historical somatosensory interaction data from a database based on a data retrieval algorithm, and preprocesses the data; the parameter analysis module: analyzes the preprocessed data, obtains a dimming strategy, sequentially collects and analyzes the user's distance data and infrared image data, and marks the interaction area; its technical key points are: a cross-dimensional analysis method is constructed for multimodal data such as the fusion of infrared images, depth data, user habits and the user's own conditions, which can accurately grasp the user's intentions and construct somatosensory interaction display parameters exclusive to the user, thereby improving the interaction effect and greatly improving the display effect, and has good usage prospects.

The invention discloses an automobile part information construction method and device based on export requirements and a storage medium, and relates to the field of automobile part information analysis. The method comprises the steps that after market characteristics of each market needing to be exported are determined, automobile parts corresponding to the market characteristics are obtained; associating the automobile part corresponding to each market feature with the market feature to form a market feature module; defining corresponding label information for each market feature module; and forming the market feature module corresponding to the label information required by the market needing to be exported into the automobile part information of the market needing to be exported. According to the method, the operation process is remarkably simplified, the working efficiency is improved, only one-time analysis is carried out when the automobile part corresponding to the market feature is initially determined, secondary analysis is not needed subsequently, the error probability is further reduced, and the working precision is improved.

The invention relates to the technical field of metering loop monitoring, in particular to a low-voltage transformer metering loop state monitoring system and method, which analyzes the same analysis signal, determines reasons to be analyzed, and generates specific reason information and secondary analysis signals based on the number of different reasons to be analyzed. Meanwhile, specific reason information is generated according to the periodic change condition of the reason to be analyzed and is transmitted to the monitoring information output unit; and the data processing unit is used for analyzing different signals, matching the periodic change condition of the abnormal parameters with historical data to obtain pre-selected data, generating specific reason information according to the change of the characteristics corresponding to the pre-selected data, and transmitting the specific reason information to the monitoring information output unit. According to the method, the loop state can be monitored in real time, abnormity is analyzed in multiple dimensions, a fault source is accurately positioned by combining periodic change and historical data, and the stability of a power system is guaranteed.

The invention discloses an ignition charge-free electronic detonator and a quality prediction and control method thereof. The detonator structurally comprises a wire clamp, an injection molding plug, an electronic control module and a basic detonator, a leg wire for connecting the electric ignition head and the exploder is arranged in the injection molding plug; an elastic piece is arranged on the surface of the electronic control module. The method comprises the following steps: S1, collecting production raw material data of the non-ignition charge electronic detonator; s2, cleaning and standardizing the collected data; s3, constructing a feature extraction model and a special prediction model, and outputting a sensitivity index prediction result and quality risk early warning; and S4, according to a large model output result, executing a subsequent production process on a qualified batch, and carrying out secondary analysis on a risk batch. Complete support is provided by collecting production whole process quality related data, the abnormal value risk weight is marked in combination with historical fault reworking data to improve the effectiveness of the model, risks can be solved in advance, waste is reduced, and the quality stability and production efficiency of the ignition charge-free electronic detonator are improved.

The invention discloses an acetaldehyde rectification process based on remote supervision of Internet of Things and a residual liquid recovery method, relates to the technical field of acetaldehyde rectification, and aims to solve the problems that the existing acetaldehyde rectification process is incomplete and the residual liquid recovery effect is poor. By monitoring the residual capacity of the channel in real time, it is ensured that the selected channel can bear the data transmission quantity, transmission can be completed at the fastest speed, data congestion and transmission delay are avoided, the continuity and integrity of production data are ensured through a timing acquisition mechanism, key node data can be accurately captured through an event triggering mechanism, and the data transmission efficiency is improved. The two acquisition mechanisms are complementary, data omission and delay are avoided, preliminary and secondary analysis results and standard data are compared and evaluated, a scientific and unified quality judgment standard is established, subjectivity of manual judgment is avoided, and it is ensured that each batch of acetaldehyde meets the quality requirement.

The present invention discloses a screening method and a quantification method for 5-HT receptor modulator-like active molecules in water bodies. The screening method comprises the following steps: S1. Solid-phase extraction is carried out on the water body, and the water body concentrate is obtained through concentration; S2. The water body concentrate and a hydroxy synthetic peptide solution with a concentration of 20-50 μM / L are analyzed by LC-MS, a volcano plot is made by using the LC-MS spectrum, targeted secondary analysis is carried out on the suspicious signals with up-regulated signals, and the signals are matched with a mass spectrometry database to identify the types of 5-HT receptor modulator-like active molecules in the water body; the hydroxy synthetic peptide in step S2 is a hydroxy cyclic peptide or a hydroxy linear peptide; the hydroxy cyclic peptide is the hydroxy linear peptide. The present invention utilizes the interaction between the hydroxy synthetic peptide and the 5-HT receptor modulator-like active molecule to form a complex, thereby realizing the screening and quantitative detection of the 5-HT receptor modulator-like active molecule in a complex matrix water body.

This invention relates to a robustness analysis method and system for accident operation procedures, comprising the following steps: acquiring all information used by the accident operation procedures in handling accident conditions; performing the following operations on each piece of information: determining whether the information to be analyzed is reliable; if reliable, determining that the information to be analyzed is robust; if unreliable, performing a secondary analysis on the information to be analyzed. This invention achieves full-range robustness analysis of the accident operation procedures by extracting and robustly analyzing all information used by the accident operation procedures in handling accident conditions, avoiding problems caused by information loss or failure, ensuring the fault tolerance of the reliability of the accident operation procedures, and further improving the safety and stability of nuclear power plant reactors.

The invention discloses an AI-based competition teaching quality evaluation method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the feature matching of a competition teaching video through taking the knowledge field with the least score of a student during competition as a feature, and determining whether the competition teaching video of the knowledge field with the least score exists or not; and performing secondary analysis on the competition teaching video to determine the competition teaching quality. The method comprises the following steps: firstly, determining the knowledge field with the least scores of students during competition, then, determining competition teaching contents by analyzing competition teaching videos for multiple times, and finally, comprehensively analyzing the knowledge field with the least scores of the students during competition and the competition teaching contents to determine whether the competition teaching quality reaches the standard or not. According to the method, the problem that teachers are only required to improve the competition teaching quality is solved, reasons for low scores of some knowledge points are determined, the corresponding teaching schemes are designed for the knowledge points, and rationalization of competition teaching is achieved.

Methods, systems, and apparatuses, including computer programs, for performing incremental secondary analysis of nucleic acid sequence reads. The method can include (i) obtaining first data describing a plurality of first reads generated by a nucleic acid sequencing device during a first read interval, (ii) obtaining second data describing a plurality of second reads generated by the nucleic acid sequencing device during a second read interval that is performed after the first read interval, wherein while the second data is being obtained: (a) providing, by the nucleic acid sequencing device, the first data as an input to a mapping and alignment unit, (b) receiving, from the mapping and alignment unit, alignment results, and (c) storing the received alignment results, and, thereafter (iii) instructing the mapping and alignment unit to begin alignment of the second data representing the second plurality of reads to the reference sequence.

The invention provides a Markov chain-based data analysis method and device, and the method comprises the steps: obtaining to-be-analyzed data, and carrying out the basic analysis of the to-be-analyzed data, so as to obtain a plaintext database and an encrypted database; the plaintext database comprises unencrypted plaintext data in the data to be analyzed and an analysis result of the unencrypted plaintext data; calling a pre-stored secondary analysis program, and performing secondary analysis on the encrypted file in the encrypted database to obtain an analysis result of the encrypted file; and performing data summarization on the analysis result of the unencrypted plaintext data and the analysis result of the encrypted file to obtain a summarized result. The device can perform effective data analysis on common data and encrypted data, thereby providing effective data support for intranet data security.

The present invention discloses a screening method and a quantification method for dopamine-like active molecules in water bodies. The screening method comprises the following steps: S1. Solid-phase extraction is performed on the water body, and a concentrated water body solution is obtained by concentration; S2. The concentrated water body solution and a synthetic peptide solution with a concentration of 20-50 μM / L are analyzed by LC-MS, and a volcano plot is made using the LC-MS spectrum. Targeted secondary analysis is performed on the suspicious signals with up-regulated signals and matched with a mass spectrometry database to identify the types of dopamine-like active molecules in the water body; the synthetic peptide in step S2 is one of cyclic peptide 1, cyclic peptide 2 or linear peptide; cyclic peptide 1 is #imgabs0# cyclic peptide 2 is #imgabs1# linear peptide is #imgabs2# The present invention utilizes the cavity size selectivity of the synthetic peptide and the hydrogen bond interaction between the synthetic peptide and the dopamine-like active molecules, enabling it to selectively interact with the dopamine-like active molecules to form a complex, thereby realizing the screening and quantitative detection of dopamine-like active molecules in a water body with a complex matrix.

The present application relates to the field of data reasoning technology, and in particular to a dispute intelligent analysis system based on big data. The system includes an event collection module, a dispute analysis module, a solution generation module, an emergency solution module, and an auxiliary decision generation module. The system collects dispute event description data, territorial feature data, and party background data to generate an original data set; extracts key event elements from the original data set to obtain a preliminary analysis report; combines the territorial feature data and party background data to perform a localized secondary analysis on the preliminary analysis report to generate a personalized mediation solution; when an emergency trigger condition is identified, the system integrates rescue resource data based on the event's geographic location to automatically generate an emergency response plan; and generates an auxiliary decision report based on the personalized mediation solution and the emergency response plan. The present invention can improve the efficiency of dispute resolution.