135 results about "Target analysis" patented technology

The invention discloses an analysis report generation method and device, equipment, a medium and a product. The method comprises the steps of determining a target report template in response to an analysis report generation request, and analyzing the target report template to determine a to-be-filled variable in the target report template; determining a corresponding data acquisition strategy according to the data type corresponding to the to-be-filled variable, and acquiring target data from at least two target systems based on a preset robot process automation technology and the data acquisition strategy; and according to a preset configuration file and the target data, determining a variable type and target filling information corresponding to the to-be-filled variable so as to execute a corresponding filling operation on the target report template, and generating a target analysis report. According to the technical scheme, the preset report template and the configuration file can be utilized to automatically perform data acquisition, processing and filling, so that the analysis report is quickly and accurately generated.

The invention discloses a content verification method and system based on LLM security protection, and the method comprises the steps: determining to-be-examined data from all data corresponding to LLM security protection, and carrying out the preliminary examination operation of the to-be-examined data based on a predetermined examination mechanism, and obtaining a preliminary examination result; and according to a predetermined target analysis algorithm and a data review strategy, executing a data verification operation on the preliminary review result to obtain a data verification result corresponding to the to-be-reviewed data. It can be seen that the data of the LLM safety protection system can be intelligently verified, the accuracy and reliability of data verification can be improved, and the operation safety of the LLM safety protection system can be further improved.

The invention relates to the technical field of network situation awareness, in particular to a network situation intelligent awareness security system based on multi-source data analysis, which accurately acquires a perception threat confidence vector, a service interruption risk vector, an attack chain complete vector and a user behavior deviation vector based on multi-source data fusion and targeted analysis. According to the method, network situation key information can be comprehensively and accurately captured, a reliable basis is provided for subsequent decision making, the comprehensiveness and real-time performance of threat perception are improved, dynamic balance of safety protection, service efficiency and operation and maintenance cost is achieved by relying on a multi-target game mechanism and a network space digital twinning technology, and the safety and reliability of threat perception are improved. A simulation deduction deviation value is introduced as a core index of strategy evaluation, a real network situation is simulated through a digital twin environment, the difference between a strategy execution effect and an expected target is quantified, and in combination with reproduction of an attack scene by the twin environment, deviation value analysis is ensured to be more fit with the real network environment.

The invention provides an air-ground cooperative target detection and feature analysis system and method, and the method comprises the steps: correspondingly obtaining an air sample database and a ground sample database through collection, data cleaning, enhancement, labeling, feature extraction and classification; the air feature sample data set and the ground feature sample data set are processed and screened through a sample processing module, the screened air sample data set and the screened ground feature sample data set are input into a model for training, and a trained air target recognition model and a trained ground target analysis model are obtained; and the two models are optimized respectively, and detection and feature analysis of the target are realized in combination with multi-modal feature fusion. Compared with the prior art, through mutual combination of the aerial target identification model and the ground target analysis model and multi-modal feature fusion, target detection and feature analysis are realized based on application scene training optimization, and target detection precision and feature analysis accuracy are improved.

The invention relates to the technical field of data processing, and discloses a method, device and equipment for data processing, a medium and a program product, the method comprises the following steps: in response to an analysis element determined by a user, obtaining analysis data corresponding to the analysis element and an associated factor corresponding to the analysis element; on the basis of the analysis data, contribution weights of the correlation factors to the target indexes are generated, an initial analysis result is obtained, and on the basis of a data correlation model, a mapping relation between the analysis elements and the target indexes is established; in response to the adjustment of the contribution weight, generating an updated analysis result based on the adjusted contribution weight and the analysis data; or in response to adjustment of the analysis elements by the user, second analysis data corresponding to the adjusted analysis elements are obtained, a target analysis result is generated based on the second analysis data and the contribution weight, and the analysis elements and the adjusted analysis elements have the same associated factors. Analysis element adjustment is supported, and the method can adapt to actual service scene change.

The invention discloses a report analysis method and device, electronic equipment and a storage medium, and belongs to the technical field of computers. The report analysis method comprises the following steps: receiving a target analysis task through a front-end interaction layer; calling a pre-training language model through an artificial intelligence body, and splitting the target analysis task into a plurality of sub-tasks; each subtask corresponds to one business requirement; respectively calling a query interface corresponding to each subtask through an artificial intelligence body based on a sequence relationship among the plurality of subtasks, querying the target report, and obtaining a query result corresponding to the subtask; and calling the pre-training language model through the artificial intelligence, analyzing the query result corresponding to each sub-task, and obtaining an analysis result for the target analysis task. According to the report analysis method and device, the electronic equipment and the storage medium provided by the invention, the pre-training language model is called through the artificial intelligence to gradually disassemble the complex analysis task, so that the accuracy of report analysis in a complex query scene can be improved.

The invention discloses an error log supervision method, device and system and a storage medium. The error log supervision method comprises the steps of obtaining error log information of a target business system; analyzing the error log information, and determining target analysis information; a code line of a target code is positioned according to the target analysis information, submission information of the code line is obtained, and the submission information comprises a code submission object; adding comment information in the code line, wherein the comment information comprises part or all of the target analysis information; in response to the adding operation of the comment information, a prompt message is sent to the code submission object, and the prompt message comprises part or all of the comment information. Therefore, the corresponding code line can be automatically positioned, the analyzed error log information is added into the comment, and the code submission object can be notified in time, so that the convenience of code maintenance is improved.

The invention discloses a high-risk operation identification method based on access behavior frequency, and particularly relates to the field of port behavior chain analysis, and the method comprises the steps: recording a starting port, a response port, trigger time and an execution sequence of an access request in a target system, and constructing an access behavior chain according to an access conduction path; and counting the access frequency of each port in a preset time window, setting an interval range formed by an access frequency upper limit value and an access frequency lower limit value, and defining the ports with the access frequencies in the interval range as a target analysis port set. By constructing a chain response mapping structure of port access behaviors and combining a path truncation test and structural independence index calculation, a latent high-risk port which is in a silent state but has a system core linkage function is identified, so that the problems that a passive activation port is difficult to identify and an induced chain attack path lacks perception are solved.

The invention relates to the technical field of artificial intelligence, provides an enterprise portrait construction method and device based on a large language model, equipment and a medium, can collect associated data of a target enterprise from a plurality of data sources, performs feature extraction on the associated data to obtain to-be-processed data, and realizes integration of data of the plurality of data sources; the to-be-processed data is input into the multiple large language models for multi-model analysis, analysis data of each large language model is obtained, and misjudgment caused by limitation of a single model can be effectively prevented; according to the method, a multi-dimensional evaluation strategy is constructed, target analysis data is selected from analysis data of each large language model by using the multi-dimensional evaluation strategy, and the enterprise portrait of the target enterprise is constructed according to the target analysis data, so that the enterprise portrait can be automatically generated in combination with an artificial intelligence means, and the reliability of the enterprise portrait is improved; and meanwhile, the construction cost of the enterprise portrait is reduced.

The invention provides a chart generation method and device, electronic equipment and a storage medium, and relates to the technical field of data analys.The chart generation method comprises the steps that in response to a data analysis instruction for a target data source, at least one initial analysis intention is displayed; in response to the intention selection instruction, determining a target analysis intention from the at least one initial analysis intention based on the intention selection instruction; displaying a question template corresponding to the target analysis intention; receiving an input field aiming at each first slot position in the question template, and combining the input field with a first fixed statement in the question template to generate a question sentence pattern; and performing chart generation processing on the target data source based on the question sentence pattern to obtain a target chart. By introducing the structured input mode, the user is restrained from asking questions too divergently, the quality of the question sentence pattern is improved, the efficiency and accuracy of chart generation are improved, the generated chart better conforms to the expectation of the user, and the satisfaction degree of the user is improved.

The invention discloses a data analysis method and device, equipment and a storage medium, and relates to the technical field of data processing.The method comprises the steps that in response to a received target file, at least one set of worksheets is determined based on the target file; an interactive interface is displayed according to the at least one set of worksheets, and the interactive interface comprises a thumbnail area and an actual file area; in response to a received operation instruction of a user on the thumbnail area and the actual file area, determining a target analysis rule according to the operation instruction; analyzing the data content in the at least one group of worksheets based on a target analysis rule to obtain target structured data, and displaying an interactive interface through the at least one group of worksheets determined according to the target file, therefore, the user can define the target analysis rule by performing simple operation on the thumbnail region and the actual file region in the interactive interface, and then the target structured data is generated according to the target analysis rule, so that the efficiency and accuracy of data analysis are improved.

The invention relates to the field of news event analysis and visualization, in particular to a multi-target dynamic composition intelligent guiding system and method for sudden news events, and the system comprises a news event monitoring analysis subsystem which is used for monitoring and analyzing existing news events, mining important news entities and obtaining event dynamic chains, and a target analysis subsystem which is used for receiving the information and sending the information to a target analysis subsystem; the method comprises the following steps of: performing clustering analysis on news keywords and entity objects, identifying related important news events and main bodies, receiving the events and main body information by a composition subsystem, performing composition modeling to obtain a news relation graph, receiving the news relation graph by a multi-target composition intelligent guide subsystem, constructing an event topology spectrum tensor and generating a dynamic characteristic matrix, and performing multi-target composition intelligent guide on the news relation graph. According to the method, a multi-target optimization guide vector field is generated, finally, the news relation graph is dynamically guided, comprehensive monitoring, mining and traceability of sudden news events are achieved by establishing a complete news event monitoring and analysis system, and the comprehensiveness and accuracy of event discovery are effectively improved.

The invention discloses a target feature acquisition method and device, a camera and a storage device. The method comprises the steps that video frames are collected in real time, and when the number of moving targets contained in a first video frame collected at the current moment is larger than a first preset number threshold value, a to-be-analyzed area in the first video frame is obtained; acquiring a second video frame acquired at a previous moment and / or a next moment, and determining a movement track of the moving target according to the first video frame and the second video frame; determining a to-be-analyzed target in the second video frame according to the movement track of the moving target, and extracting a target area where the to-be-analyzed target is located from the second video frame; and splicing the target region into the to-be-analyzed region to generate a target analysis region, and analyzing the target analysis region to obtain feature information of the moving target contained in the target analysis region. According to the scheme, the feature information of the moving targets in the at least two video pictures can be analyzed at the same time, and the target feature recognition efficiency is effectively improved.

Embodiments of the present application provide a method, medium and electronic device for automatic data analysis, the method comprising: obtaining an original data file and a current analysis target; obtaining a target data table according to initial data characteristics of the original data file; obtaining updated data characteristics corresponding to the original data file according to the target data table; inputting the updated data characteristics and the current analysis target into a pre-constructed analysis method recommendation knowledge base to obtain a candidate analysis method set; performing effect simulation pre-evaluation on at least part of the analysis methods in the candidate analysis method set according to the target data table to obtain real-time performance evaluation indexes of each method; obtaining a target analysis method selected for the current analysis target based on a reinforcement learning decision model; and analyzing the target data table using the target analysis method to generate an analysis result.

The embodiment of the invention discloses a data link fault detection method and device, electronic equipment, a medium and a product. The method comprises the steps of reading link connection information recorded in target detection equipment under the condition of establishing communication connection with the target detection equipment in a ship digital platform; wherein the target detection equipment comprises a firewall and / or a switch; the link connection information is used for reflecting a connection state between an equipment interface of the target detection equipment and ship equipment in at least one ship digital platform; determining a target device attribute of the target detection device, and determining a target analysis mode corresponding to the target device attribute based on a preset corresponding relationship between the device attribute and the analysis mode; and analyzing the link connection information according to the target analysis mode, and determining a fault link in target data links associated with the target detection equipment based on the analyzed link connection information and a preset corresponding relationship between the equipment interface and the data links.

The application discloses a kind of software evaluation method, device, equipment and storage medium, and specifically discloses: receiving the software requirement document uploaded by user, and the software requirement document is parsed, and target analysis data is extracted;Target analysis data includes function item description, data element type and file reference type;Based on function item description and interface image associated with function item description, a multi-modal fusion analysis technique is used to classify the function items, resulting in a classification result;The function items are checked for duplicates, resulting in a first inspection result, and the data element types and file reference types are checked for form, resulting in a second inspection result;Form checking includes illegal character checking and character duplication checking;According to the classification result, the first inspection result and the second inspection result, a function point analysis table is generated, and a software evaluation report is generated based on the function point analysis table.

This invention provides a bitstream analysis method, apparatus, storage medium, and electronic device. The method includes: acquiring the raw bitstream reported by a target camera device accessing a server, wherein the server has an analysis function to analyze the raw bitstream, and the analysis function is configured in the server through an acquired configuration file, which is pre-acquired from camera devices that have historically accessed the server; determining, based on the capabilities of the target camera device, whether the target camera device has performed target analysis on target bitstreams included in the raw bitstream; extracting the target bitstream from the raw bitstream and performing target analysis on the target bitstream. This invention solves the problem of poor intelligent analysis capabilities of camera devices in related technologies, achieving the goal of enhancing the intelligent analysis capabilities of camera devices and improving the efficiency of intelligent analysis.

The invention provides a vehicle operation data analysis method and device, equipment, a medium and a product, and relates to the technical field of vehicle data management. The method comprises the following steps: acquiring a data analysis demand text, and identifying a data analysis scheme corresponding to at least one target vehicle from the data analysis demand text; determining a corresponding to-be-analyzed data identifier and a target data analysis interface according to the target analysis dimension; according to the target vehicle identifier, the to-be-analyzed data identifier of the target analysis dimension and the analysis time range of the target analysis dimension, extracting corresponding to-be-analyzed data of the target vehicle on the target analysis dimension from pre-collected vehicle operation data; and inputting the to-be-analyzed data of the target analysis dimension into a target data analysis interface of the target analysis dimension for analysis to obtain a data analysis result of the target analysis dimension. According to the method, the vehicle operation data of the vehicle on the target analysis dimension is analyzed in a customized manner according to the actual demand of the user, and the data analysis efficiency is improved.

The invention relates to an intelligent electric meter fault detection system. The system comprises a target analysis mechanism and a target analysis mechanism, the AI analysis module is used for introducing an AI analysis model according to a preset time length and various configuration information of a target intelligent electric meter; intelligently analyzing a fault type identifier of the target intelligent electric meter at the current moment according to the remote meter reading of the target intelligent electric meter at the current moment and each remote meter reading corresponding to each previous moment before the current moment; and the type mapping mechanism is used for determining the type name of the fault type corresponding to the fault type identifier as the current fault type name. Through the system, the AI analysis model can be used to intelligently analyze the fault type identifier of the target intelligent electric meter at the current moment, and then the current fault type name is determined, and the current fault type name is wirelessly sent to the handheld terminal of the nearest worker, so that the intelligent level and the automation level of intelligent electric meter management are improved.

The invention provides a corpus cleaning method and system, a medium and a terminal. The method comprises the following steps: obtaining an original corpus to be cleaned, carrying out pre-annotation processing on the original corpus to generate a pre-annotated corpus, and analyzing the pre-annotated corpus to generate first analysis information; corpus optimization is conducted on the original corpus to obtain optimized corpus, and the optimized corpus is analyzed to generate second analysis information; performing enhancement processing on the original corpus to obtain an enhanced corpus, and analyzing the enhanced corpus to generate third analysis information; generating target analysis information according to the first analysis information, the second analysis information and the third analysis information, and generating a corresponding synthetic corpus according to the target analysis information; performing desensitization processing on the synthetic corpus according to a desensitization library to generate a corresponding desensitization corpus, and performing standardization processing on the desensitization corpus to generate a corresponding target corpus. According to the method, the corpus cleaning efficiency and quality are effectively improved.

The invention discloses a visual A / B test data analysis method and device based on a large model, and the method comprises the steps: displaying A / B test data index information of a to-be-analyzed object under different analysis dimensions on a data analysis page, and carrying out the associated display of an analysis function entry used for triggering the large model to analyze the A / B test data index information for each analysis dimension; and in response to a trigger operation on the analysis function entry associated with the target analysis dimension, displaying a data analysis result of the A / B test data index information under the target analysis dimension. Therefore, the analysis function entry can be triggered in a visual mode, and the analysis efficiency and the analysis accuracy can be improved by automatically analyzing the A / B test data index information through a large model. Besides, each analysis dimension displays an analysis function entry in an associated manner, so that the analysis function entry associated with the corresponding analysis dimension can be triggered based on user requirements, targeted A / B test data index information analysis is realized, and the user experience is improved.

The invention provides an active network diagram automatic generation method, system and device, and relates to the technical field of network diagram automatic generation. The method comprises the following steps: firstly, obtaining to-be-processed project data; secondly, performing feature mining on the to-be-processed project data by utilizing a semantic feature mining model included in the target analysis network, and outputting target project semantic features corresponding to the to-be-processed project data; then, analyzing semantic features of the target project by utilizing a semantic feature analysis model included in the target analysis network, and outputting a plurality of monitoring activities and a relationship among the plurality of monitoring activities; and finally, based on the plurality of monitoring activities and the relationship among the plurality of monitoring activities, generating a corresponding target activity network graph. Based on the above content, the problem of low reliability of active network graph generation in the prior art can be improved.

The embodiment of the invention discloses a taximeter state analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the metering error values of a plurality of qualified taximeters in the same batch, the plurality of qualified taximeters in the same batch being a plurality of taximeters which are submitted for inspection in the same batch and are verified to be qualified; and on the basis of the log error value and the out-of-tolerance early warning threshold value, analyzing and determining function states corresponding to the plurality of qualified taximeters in the same batch from a target analysis dimension, wherein the target analysis dimension comprises an operation company dimension. According to the embodiment of the invention, the detailed information of the quality state of the same batch of taximeters under the target analysis dimension including the operation company dimension can be analyzed and determined.

Embodiments of the invention provide a test data analysis method and apparatus, an electronic device and a storage medium, and can execute at least one analysis operation while obtaining test data for a target server in real time: the first analysis operation can generate to-be-input content based on unanalyzed data; in each subsequent analysis operation, to-be-input content can be generated based on the unanalyzed data and the summary of the analysis result obtained by the previous analysis operation, the to-be-input content is input into the large language model for analysis, and the analysis result corresponding to the Nth analysis operation is obtained; and combining the analysis results corresponding to each analysis operation to obtain a target analysis result. By means of the method, manual operation is not needed, the automatic analysis process of the test data generated in the heat dissipation test process of the server can be achieved, the analysis efficiency of the test data is improved, and the relevance of contexts during analysis of the test data is improved.

This application relates to a substation monitoring system and method. The system includes: a sensor module, at least one local condition analysis module, and a substation data center module; wherein, one local condition analysis module corresponds to one equipment bay and is connected to the sensor module within the equipment bay; the sensor module is used to send target monitoring data to the local condition analysis module using a standardized interface; the local condition analysis module is used to provide standardized power to the sensor module, receive the target monitoring data, and perform conversion, alignment, and analysis processing on the target monitoring data to obtain preliminary analysis results, and send the preliminary analysis results to the substation data center module; the substation data center module is used to receive at least one preliminary analysis result and determine the target analysis result based on at least one preliminary analysis result. This method can improve the availability and reliability of the substation monitoring system.

The invention discloses a forest fire spreading trend prediction method, system and device and a medium. The method comprises the steps of obtaining multi-source environment data related to a plurality of target analysis items; based on the common environment data and the special environment data, constructing a standard prediction template for multi-dimensional forest fire spreading trend analysis, based on the standard prediction template, constructing a standard prediction model, and constructing a corresponding prediction sub-process for each target analysis item, the standard prediction model is integrated with sub-prediction models corresponding to the target analysis items, and the prediction sub-processes are configured to call the corresponding sub-prediction models; and the prediction sub-processes corresponding to the target analysis items are executed in parallel to generate forest fire spreading trend prediction results of the target analysis items, so that the forest fire spreading trend prediction efficiency can be improved through implementation of the forest fire spreading trend prediction method and device.

Embodiments of the present application provide an indoor environment data analysis method and related device, belonging to the technical field of data analysis. The method comprises: obtaining first monitoring data of a target object at a first time and second monitoring data of the target object at a second time under monitoring of a plurality of Lora sensors; obtaining a first correlation relationship between any two Lora sensors of the plurality of Lora sensors according to the first monitoring data, and obtaining a second correlation relationship between any two Lora sensors of the plurality of Lora sensors according to the second monitoring data; determining a first analysis result of the target object according to the first correlation relationship and the second correlation relationship; determining a first data change according to the first monitoring data and the second monitoring data, and determining a second analysis result of the target object according to the first data change and a data threshold; and determining a target analysis result by fusing the first analysis result and the second analysis result. The problem that the correlation between Lora sensors is not utilized in related technologies, thereby resulting in poor analysis effect, is solved.

The invention discloses a large language model information detection method and system based on reverse thinking. The method comprises the following steps: step 1, performing problem modeling and target analysis; step 2, carrying out structured reverse condition enumeration; step 3, condition availability verification is carried out; 4, carrying out missing information quantitative judgment; and step 5, carrying out confidence coefficient calibration and output. According to the method, information integrity detection is converted into a systematized'target-condition 'verification process, and the limitation of a traditional forward reasoning method on information missing recognition is broken through.

The invention provides an analysis model training data generation method and electronic equipment. The analysis model training data generation method comprises the steps that basic training data of a target analysis model is acquired through a first data acquisition instruction, the basic training data comprises a first analysis data table, and the first analysis data table comprises texts and numbers; acquiring data features of the basic training data; forming a training data set of a target data generation model according to the first data acquisition instruction, the basic training data and the data features of the basic training data, and training the target data generation model through the training data set; a second data acquisition instruction and a first data feature combination are input into the trained target data generation model to form derived training data, the derived training data comprises a second analysis data table, and the second analysis data table comprises texts and numbers; and forming model training data of the target analysis model according to the basic training data and the derived training data. According to the embodiment of the invention, the capability of the artificial intelligence model for analysis can be improved.