19results about How to "Improve analyzability" patented technology

The invention discloses a thermal insulation layer defect detection method based on machine vision, relates to the technical field of defect detection, and solves the technical problem that single data matching cannot comprehensively judge defect reasons and causes errors to defect judgment. The method can automatically adjust the threshold value according to the gray feature distribution of different segmented areas in the whole image, is more suitable for the local difference and overall change conditions of the thermal insulation layer image, carries out the detailed analysis of the edge features through building a rectangular coordinate system for a target area with no gray feature matching result, and improves the accuracy of gray feature matching. According to the method, more clues about the defects can be mined from the edge information, and the distribution and formation mechanism of the defects in the thermal insulation layer can be more comprehensively understood by judging the integrity of the abnormal shape and combining and analyzing the associated region of the incomplete shape, so that the defect reasons can be more accurately determined.

The invention relates to an automatic business information collection method, system and device and a medium, and the method comprises the steps: determining a collection object of business information according to the demands of a user for the business information; controlling the automatic tool to capture business information from each information detailed page of the collection object; performing structured processing and data format conversion on the business information to obtain multi-field structured data of the business information; according to the multi-field structured data, iterative training is conducted on the selected base model, an SQL processing enhancement model is obtained, and the SQL processing enhancement model can push corresponding structured business information to a user side based on query requirements input by a user. According to the invention, the business information in the industry can be captured in a directional manner, and the dimension information of the business field desired by the user can be obtained in an inquiry manner, so that the business information can be automatically collected and sorted without a specially-assigned person, the cost is reduced, and the timeliness, comprehensiveness and accuracy of business information collection are improved.

The invention relates to the technical field of electric power regulation and control, in particular to an electric power regulation and control method and system based on a power characteristic matrix. The method comprises the following steps: obtaining distributed power plant equipment data, carrying out abnormal value replacement, generating complete equipment data, screening out standard operation parameters, carrying out equipment unit simulation processing, generating a simulation power plant equipment unit, and carrying out combined power generation simulation to obtain various simulation data; historical power output data are obtained, power demand analysis is carried out, power output data and power demand peak and valley data required by prediction are generated, based on the data, intensity adaptation screening is carried out on combined power generation simulation, an operation period is adjusted, and finally a distributed equipment scheduling instruction is generated, so that efficient regulation and control of the intelligent virtual power plant are realized. According to the invention, a more efficient and more reliable intelligent power regulation and control method is realized.

The invention discloses an artificial intelligence-driven burn wound assessment method and system, and relates to the technical field of medical information processing and intelligent diagnosis, and the method comprises the following steps: S001, employing a fixed imaging attitude to collect continuous short-sequence wound image frames, calculating a brightness change curve of adjacent image frames, generating a light and shade rhythm track, and drawing a beat frequency prompt band, the method is used for marking a light source flicker rule and establishing an initial reference baseline of brightness change. Through brightness breakpoint identification, error shooting parameter calculation, light source phase jitter and inverse rhythm optical shutter regulation and control, active separation and reverse coupling of illumination rhythm and sampling rhythm are realized, periodic flicker interference is effectively eliminated, the brightness stability and texture reduction degree of a wound image are improved, an artificial intelligence evaluation result is more accurate and reliable, and the artificial intelligence evaluation efficiency is improved. And the objectivity and safety of clinical diagnosis are improved.

The embodiment of the invention provides a dwell pressure adjusting method, which is applied to an upper computer and a servo driver, and comprises the following steps that: the upper computer configures mapping parameters of a pressure value and an analog quantity value and issues the mapping parameters to the servo driver, and the servo driver calculates a dwell pressure value based on a linear calibration model; a servo motor is controlled to execute self-learning to determine a contact point origin machine of the pressing process; the upper computer issues a force control instruction to the servo driver through the EtherCAT bus; the servo driver converts an analog quantity signal fed back by the pressure sensor based on a linear calibration model to obtain a real-time pressure value, adjusts the torque of the servo motor by taking the original point of the contact point as a reference, and feeds back a state to the upper computer through an EtherCAT bus; an upper computer reads a process data packet through a Modbus bus and analyzes the process data packet to obtain a pressure-time relation oscillogram, complete and synchronous acquisition and tracing of process data are achieved through double-bus cooperation based on built-in high-precision calibration and closed-loop force control of a driver, and the precision, stability and analyzability of a pressure maintaining process are improved.

The present invention relates to an animation dialogue difficulty adaptation method based on user cognitive level, and specifically to the field of intelligent education. According to the user's score in an animation dialogue test, the user cognitive level score is mapped and the user cognitive level is judged, so as to improve the accuracy and effectiveness of the test, and the animation dialogue text is preprocessed, which is helpful to reduce noise and variants, improve the clarity and analyzability of the text, and comprehensively evaluate the animation dialogue difficulty level through different word frequencies, word lengths, root complexity, text lengths, and dependency relationships between main clauses and subordinate clauses, and the animation dialogue difficulty level based on the user cognitive level is obtained by weighted average, and the animation dialogue difficulty level based on the user cognitive level is divided into simple difficulty, medium difficulty and difficult difficulty, and the animation dialogue difficulty is adapted based on different difficulty levels, so that users can better understand animation content at different difficulty levels, and enhance the user's attraction and satisfaction with the animation content.

The invention discloses a multi-file data processing method and a related device, and the method comprises the steps: obtaining a file list and n file blocks from m original files, merging the n file blocks according to the file list, and obtaining the m original files. And respectively processing each piece of sub-data in the target original file according to a bank data quality rule to obtain standard data, and respectively taking the m original files as the target original files to obtain standard data respectively corresponding to the m original files. And obtaining a data demand table for satisfying the plurality of data demands, obtaining a target data demand, and processing the standard data according to the data demand table and the target data demand to obtain a data report satisfying the target data demand. Therefore, the efficiency and accuracy of processing the original file to obtain the standard data are improved, the intuition and analyzability of the standard data are ensured to be improved, and the efficiency and accuracy in the process of applying the standard data are improved.

The invention relates to the field of deep learning, and discloses a drainage monitoring analysis system based on big data, which comprises the following steps: collecting pipe network element information including pipe network node information, pipe section information, underground engineering point information and monitoring data information; obtaining first two-dimensional structure data from the collected pipe network element information, wherein the first two-dimensional structure data comprises a data matrix and a relation matrix; sorting the first two-dimensional structure data to obtain first one-dimensional structure data, wherein the first one-dimensional structure data comprises n data items sorted according to time; the first one-dimensional structure data are input into the monitoring model, an equipment distribution strategy is output, and the equipment distribution strategy comprises the types of flowmeters needing to be configured on all the pipe network nodes and the types of valves needing to be configured on all the pipe network nodes. According to the invention, monitoring of pipe network drainage can be realized, and leakage information of pipe network nodes can be analyzed according to drainage flow data.

The application discloses an abnormality detection method for long-time and large-capacity recording of a digital oscilloscope, and the method comprises the following steps: acquiring a parallel sampling data stream through high-speed ADC sampling of a front end of the digital oscilloscope; performing trigger alignment processing on the parallel sampling data stream through FPGA; performing multi-dimensional feature extraction on waveform data segments after the trigger alignment; obtaining a fusion feature value through normalization and weighted fusion of the features; and further performing classification and statistics on the fusion feature value through an online incremental clustering mode, identifying abnormal waveforms according to probabilities of various features, and outputting an abnormal category and statistical information, so that stable and sustainable operation of the abnormality detection in a long-time and large-capacity recording scene is realized.

The invention relates to a JavaScript code anti-obfuscation method based on an AST abstract syntax tree, and belongs to the technical field of software security, program analysis and code reverse engineering. Compared with the prior art, the method has the advantages that simple text matching is exceeded, and the'intention 'of codes can be understood through semantic analysis of AST, so that complex confusion transformation is accurately restored.

The invention discloses a transparent bottle curved surface printed graphic text detection system based on AI vision, which relates to the field of machine vision detection technology. The main scheme is: pre-processing the collected images, including denoising and enhancement, and being able to calculate the position deviation mean P according to the position accuracy data based on the characteristics of the transparent bottle curved surface, and evaluate whether the position accuracy meets the standard according to the position deviation mean P, and collect images with high unit pixel density and high frame rate to ensure that every subtle detail of the graphic text can be clearly recorded; from image acquisition to result output, the entire system realizes automatic operation without manual intervention, greatly improves the detection speed, and can quickly process a large number of transparent bottles to meet the needs of large-scale production. Each module of the system has strong adaptability and flexibility and can process different types of transparent bottles, graphic text and printing processes.

This application relates to a method for predicting the evolution of online public opinion under the intervention of AI agents and online trolls. The method includes: acquiring social media user data; constructing a weighted directed social network containing ordinary netizens, online trolls, and commentary-type AI agents and identifying node types; mapping text content to opinion values, setting the opinion values ​​of online trolls to fixed values, and setting the commentary-type AI agents to generate targeted comment opinion values ​​for different target users; calculating the individual confidence threshold of ordinary netizen nodes, and performing opinion updates based on the extended Deffuant-Weisbuch dynamics equation; iteratively updating until convergence, and outputting the final opinion distribution as the prediction result. This invention, by introducing multi-agent heterogeneous interaction and human intervention, solves the problem of existing models' inadequate characterization of complex public opinion environments, significantly improving the accuracy and modeling completeness of online public opinion evolution prediction.

This invention discloses a method and system for detecting and evaluating the settlement of buried pipelines based on ground-penetrating radar (GPR). The detection method acquires B-Scan mask images of shallow-buried pipelines, extracts the overall and local characteristics of target hyperbolic reflection signal feature points in the images, removes singular points, performs curve fitting on all valid target hyperbolic reflection signal feature points, and calculates and scores the depth and wave velocity values ​​corresponding to the target feature points to obtain the pipeline burial depth. The evaluation method, based on the pipeline settlement detection results, identifies the location of maximum settlement deformation by using the angle formed by the height change between two points on the pipeline, and predicts the location where the risk of fracture in the detected section may occur. The detection system implements this detection method, and the evaluation system implements this evaluation method. This application solves the problem in engineering measurements where hyperbolic reflection signals with characteristic damage caused by electromagnetic wave attenuation and coupling cannot be effectively calculated, significantly improving the data's processability and analyzability.

The invention discloses a field-circuit coupling numerical simulation method for calculating spatial thermal field distribution of a high-voltage tunnel cable, and belongs to the technical field of energy research, and the simulation method specifically comprises the following steps: S1, simulating important geometric parameters collected and recorded by a simulation system according to high-voltage tunnel cable equipment which is actually put into operation; the method can comprehensively analyze the temperature field distribution of the cable system under the conditions of different loads, tunnel structures, laying modes and the like, improves the precision and reliability of temperature monitoring, and compared with the traditional technology, reduces the computing resources, accurately simulates the operation condition of the KM-level long-distance tunnel cable, improves the analyzability of the simulation result, and reduces the construction cost. According to the method, the engineering reference precision of practical application is deepened, the temperature field distribution condition of the high-voltage tunnel cable in a long-time operation state can be analyzed, and the method has important engineering application value and particularly has great significance in operation monitoring, fault early warning and optimization design of the high-voltage tunnel cable.

The embodiment of the invention provides a space-time research and judgment method, a research and judgment system, electronic equipment and a storage medium. The method comprises the following steps: acquiring network access data corresponding to an entity to be researched and judged, and processing according to a preset feature extraction rule to obtain basic feature information and associated feature information; constructing a spatial-temporal feature sequence according to the basic feature information and the associated feature information, and inputting the spatial-temporal feature sequence into a trained feature recognition model to obtain behavior feature information; comparing the behavior characteristic information with behavior characteristic conditions in a behavior rule base to obtain a characteristic comparison result; according to a feature comparison result, when it is determined that the entity to be researched and judged meets a preset research and judgment condition, determining an expanded network entity according to the associated feature information; and according to the research and judgment result of the entity to be researched and judged and the expanded network entity, generating and outputting a space-time research and judgment result. According to the invention, the time-space research and judgment of the target entity and the associated network space thereof are realized, and the comprehensiveness and accuracy of identification are improved.

The present invention discloses an online experimental system and method for high-temperature and high-pressure steam oxidation in a thermal power plant. The system is provided with a steam introduction module, an experimental module and a steam recovery module. The steam introduction module introduces the high-temperature and high-pressure steam actually operated by the thermal power plant generator set from the hot re-drainage pipeline. After passing through the experimental pipeline, the steam enters the steam recovery module and finally enters the heating pipeline for recovery, which has little impact on the efficiency of the generator set. The system can use the high-temperature and high-pressure steam actually operated by the thermal power plant generator set to conduct high-temperature and high-pressure steam oxidation experiments on metal materials to be studied. The experimental parameters of the system are the same as the actual service parameters of the metal materials, and can be controlled and adjusted within a certain range. The experimental data has high accuracy, analyzability and comparability, which reduces the adverse effects caused by the difference between the experimental parameters in the laboratory of the scientific research institution and the actual service environment parameters of the metal materials.

The application relates to the field of image recognition and discloses an obstacle cross-frame tracking method, device and equipment and a storage medium, which comprises the following steps: acquiring an obstacle recognition result in a first detection image, and generating a tracking query based on the obstacle recognition result; extracting an image feature of an obstacle in a second detection image, and obtaining a new obstacle query based on the image feature; inputting the tracking query and the new obstacle query into a preset obstacle tracking model, tracking and identifying the obstacle in the second detection image through the obstacle tracking model, and obtaining a tracking and identifying result. Through the method, the query value of the obstacle feature between two continuous frame images can be compared based on image information, the tracking process for consecutive images in time sequence is directly completed implicitly in the obstacle tracking model, the complexity of the algorithm architecture is reduced, and the optimizability and analyzability of the whole tracking process are improved.

This application relates to a domain-specific language compiler for cache coherence protocols, belonging to the field of computer architecture modeling and simulation technology. The compiler takes a high-level abstract specification of the cache coherence protocol as input and automatically converts it into cache controller and / or directory controller code executable by a periodic precision simulator. Through systematic mapping and translation of the protocol's finite state machine, event-triggered mechanism, concurrent transaction management, and asynchronous hardware interaction, it achieves event-driven, non-blocking control logic generation. Simultaneously, the compiler supports network communication code generation, debug tracing injection, and formal logical equivalence checks. Furthermore, it incorporates a performance constraint-aware optimization module to automatically optimize the generated state machine, thereby improving simulation efficiency, reducing development complexity, and enhancing verifiability while ensuring the semantic correctness of the protocol.

The invention relates to the technical field of image data processing, and in particular to a detection method and system for a graphene far-infrared electric heating sheet system. Nanoparticles responsive to lasers of specific wavelengths are uniformly injected into a graphene material to generate interference patterns. Interference image data are generated by multi-wavelength laser scanning, and pre-processing, fringe detection, feature extraction and multi-frequency feature fusion are performed on the interference image data to generate multi-frequency interference fringe feature data. Multi-frequency spectrum response analysis is performed based on the data, a dynamic nanoparticle response model is established, and a comprehensive response feature vector is generated. An adaptive fault detection model is trained by using the vector, and model parameters are adjusted in real time through a dynamic correction mechanism to perform real-time fault detection and classification. A fault handling suggestion is generated in combination with an intelligent decision engine, a fault report is automatically generated and an alarm system is triggered, and the model is optimized through an online learning and feedback mechanism. The invention significantly improves the accuracy and robustness of fault detection.