949results about How to "Improve readability" patented technology

The invention relates to the technical field of image processing, and discloses a display method and system for a vehicle-mounted LED display screen. The method comprises the following steps: acquiring ambient light intensity data, performing fusion processing to obtain a characteristic value, and predicting ambient light change; identifying a driving scene according to the road condition data, and analyzing the priority by combining the ambient light change data; arranging a display area in combination with the eye movement data, and determining display parameters; analyzing the multi-modal interaction data, determining an interaction strategy, and verifying to generate response data; adjusting display content according to the ambient light features, and outputting a display effect in combination with response data; and energy consumption is estimated by integrating various data, and control parameters are generated to adjust an LED driving circuit. Through intelligent analysis and processing of multi-dimensional data such as ambient light intensity, driving scene and eye movement tracking, dynamic optimization and energy-saving control of display content are realized, and the problem that display effect and energy efficiency are difficult to consider in the prior art is overcome.

The invention relates to the technical field of image processing, and discloses a detection method, system and equipment for intelligent welding of pipe pile splicing and a medium. The method comprises the steps that noise reduction is conducted on a target weld seam image through a filtering algorithm, registration and splicing are conducted on the image through feature matching, and a weld seam unfolding image is obtained; segmenting the weld joint expanded image by using a deep learning network, and extracting a weld joint center line and surface features to obtain weld joint feature data; defect detection and recognition are conducted on the weld joint feature data, hierarchical calculation is conducted through a rule set, and weld joint quality data are obtained; parameter mapping is conducted according to the weld joint quality data, a welding parameter instruction is generated, welding process variables are adjusted, and target welding parameters are obtained; and the welding seam quality data and the target welding parameters are stored, and a quality report is generated through data analysis. The detection accuracy of intelligent welding for pipe pile splicing is improved.

The invention relates to a PDF extraction method and system based on deep learning and layout analysis, and the method comprises the steps: obtaining a PDF file, carrying out the element recognition of a scanning version file and a text version file through an OCR technology and a deep learning model, and enabling the elements to comprise a text, a picture, a table and a formula; dividing a page of the PDF file into a plurality of logic blocks according to the identified elements, and determining a hierarchical relationship and a sequence; deleting elements without substantial help from the identified elements, and extracting the content of the document; performing page layout analysis according to the document content, and reordering and organizing each logic block to obtain a layout; document contents are classified and analyzed, and then classified storage is carried out; and according to user requirements, splicing the classified and stored document contents in a corresponding layout to generate a document in a target format. Compared with the prior art, efficient and accurate PDF extraction is achieved, and meanwhile the important structure and content of an original document are reserved.

The invention belongs to the field of artificial intelligence and financial science and technology, and relates to a document segmentation method, which comprises the following steps: carrying out style feature recognition and title text recognition on a to-be-segmented document to obtain a title style result and a title text result, and then carrying out recognition verification on the title style result and the title text result through a multi-modal title recognition large model to obtain a segmented document. And obtaining a final title recognition result, constructing tree hierarchical representation based on the title recognition result to obtain a document chapter structure, and segmenting the to-be-segmented document according to the document chapter structure. The invention further provides a document segmentation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the to-be-segmented document can be stored in a block chain. According to the method and the device, the document is segmented in a chapter form, the semantic integrity of segmentation is ensured, and key information is effectively extracted and structured.

The invention relates to the technical field of software development, and particularly provides a self-adaptive code annotation updating method and system, a terminal and a storage medium, and the method comprises the following steps: confirming that codes are updated, extracting an updated code set, and combining and constructing an abstract syntax tree for the codes; performing semantic analysis on the abstract syntax tree by using a deep learning model to generate a semantic vector, and constructing a program dependency graph based on the semantic vector; analyzing a dependency relationship among code elements in the program dependency graph by utilizing a graph neural network; and generating a code annotation based on the semantic vector and the dependency relationship between the code elements by using a natural language generation model. According to the method, the real-time performance and the accuracy of the code document are ensured, the readability and the maintainability of the code are greatly improved, and the maintenance cost is reduced.

The invention discloses an intelligent financial statement automatic generation platform, and relates to the technical field of financial statement generation, and the platform comprises a data integration module which is used for connecting and synchronizing a data source, the data source comprises a bank transaction record, an enterprise resource planning system and an electronic invoice system, and data is grabbed through connection configuration of a data interface. According to the intelligent financial statement automatic generation platform, classification rules of financial subjects are customized by a user, so that the platform can adapt to specific financial statement requirements and business characteristics of different enterprises, the flexibility and applicability of the system are improved, statement customization is supported through the platform, financial statements of different versions are provided, and the user experience is improved. According to the method, different requirements of different users on financial information are met, the flexibility and applicability of the system are improved, a temporary version exclusive to the current requirement is formulated based on a customizable mechanism of a classification rule, and more targeted financial support is provided for decision and management of enterprises.

The invention discloses an industry report generation optimization method and system based on reinforcement learning and a knowledge graph, and relates to the technical field of industry report generation, and the method comprises the following steps: firstly, collecting industry data from multiple sources, preprocessing the industry data, determining the collection frequency according to the type and importance, then constructing the knowledge graph, and recognizing entities by using a plurality of technologies. Designing a reinforcement learning model, defining space and reward functions such as states and actions, training according to a specific algorithm, analyzing and generating a preliminary report according to user requirements by means of the model and graph selection data, combining an optimization algorithm with a language model and a graph to improve the report, and finally evaluating, feeding back and adjusting a parameter strategy to improve system performance. The method can improve the industry report generation efficiency, optimize the report quality, enhance the depth and accuracy, adapt to different requirements, can be self-promoted, and effectively assists the decision and development of each industry.

The invention relates to the technical field of computer television image communication, in particular to a computer television all-in-one machine control method, system and device. The method comprises the following steps: through multi-view image acquisition and processing, generating a three-dimensional scene grid and carrying out scene element analysis to form a scene element set, then chasing limbs of a user, generating a user limb image set, restoring an environment basic tone, obtaining display content of the all-in-one machine and carrying out content semantic analysis, and finally obtaining a user limb image set. Calculating interaction intensity to obtain content interaction intensity data, speculating a user body language and performing user intention prediction in combination with the interaction intensity data, adjusting display content of the all-in-one machine based on the predicted user operation intention, generating simulation adjustment content, performing composition optimization through a scene element set, and generating updated display content. The method for controlling the computer and television all-in-one machine is more accurate and more efficient.

The invention belongs to the technical field of front-end development, and particularly relates to a React framework-based tree component optimization method fusing virtualization rendering and increment rendering. Comprising the steps of S1, data preprocessing; S2, dynamic virtualization rendering: dynamically calculating a node index range in a visible area according to a real-time scrolling position of a user viewport, only rendering nodes in the range, and realizing seamless lazy loading of data through scrolling event monitoring; s3, intelligent incremental updating: identifying changed nodes through a state change comparison algorithm, and executing local re-rendering only for the changed nodes based on a component life cycle control mechanism of a React framework; and S4, lazy loading cooperative control. The method aims at solving the problems in the aspects of performance, memory management, user experience and the like when a tree component in a React ecological system processes large-scale data, and is widely applied to various Web application program development scenes needing to display and operate a large-scale tree data structure.

The invention discloses a method and device for automatically converting a cross-format document into a Markdown document and a form enhancement method and system. The Markdown document conversion method comprises the following steps: firstly, obtaining a document image; mining hidden structure information from the document image, wherein the hidden structure information comprises target elements and hierarchical relationships among the target elements; performing semantic content analysis on the document image based on the structure information to obtain a semantic content analysis result; extracting key information in the document image according to an analysis result; the key information is converted into a Markdown format, preliminary formatting is carried out in a form or list mode, and a preliminary Markdown form is obtained; and finally, optimizing the preliminary Markdown form to form a target Markdown form, so that the cross-format document is automatically converted into the Markdown. According to the method, a complex nested structure and a form with irregular layout in the document can be effectively identified and converted, and the integrity and readability of form information when the form is converted into the Markdown format are ensured.

The invention belongs to the technical field of intelligent traffic, and discloses a space-time fitting-based whole vehicle type traffic feature accurate recognition algorithm, which comprises the steps of obtaining driver behavior data, vehicle dynamic data and road supervision data; preprocessing the driver behavior data, the vehicle dynamic data and the road supervision data to obtain a driver behavior feature data set, a vehicle dynamic feature data set and a road supervision feature data set; according to the vehicle dynamic feature data set and the road supervision feature data set, obtaining a vehicle initial driving track; optimizing the initial driving track of the vehicle through an improved space-time interpolation algorithm to obtain a complete driving track of the vehicle; according to the complete driving track of the vehicle, the vehicle driving speed of each road section is calculated and compared with the limiting speed of the corresponding road section, and whether the vehicle is overspeed is judged; and traffic accidents caused by overspeed, fatigue driving and the like are effectively avoided.

The invention relates to the field of image enhancement, in particular to an image enhancement method and system of a vehicle-mounted image sensor. The method comprises the following steps: acquiring driving record images of a vehicle at multiple angles; dynamic scene self-adaptive exposure adjustment is carried out on the driving record images of the vehicle at the multiple angles, so that multiple self-adaptive exposure driving images are obtained; carrying out deep network noise identification on the plurality of adaptive exposure driving images, and carrying out dynamic filtering and noise reduction on sub-images one by one so as to generate a plurality of filtering and noise reduction optimized images; carrying out image texture analysis on the plurality of exposure sub-images, and carrying out texture distortion reconstruction to construct a plurality of texture reconstruction images; and road object visual identification is carried out on the plurality of texture reconstruction images, and adaptive contrast enhancement processing is carried out, so that a plurality of detail contrast enhancement images are constructed. According to the invention, a high-definition and stable panoramic vehicle-mounted image is realized.

The invention provides a context understanding-based software operation prompt automatic optimization method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting the multi-dimensional context feature data of user software operation, carrying out the feature coding through a multi-modal feature fusion network, modeling the time sequence dependence through a bidirectional long-short-term memory network, and carrying out the feature coding through the bidirectional long-short-term memory network. And a context semantic representation vector is generated based on a multi-head attention mechanism, and a prompt generation strategy is continuously optimized in combination with reinforcement learning. According to the method, personalized customization of software operation prompts can be realized, the accuracy and timeliness of prompt contents are improved, and the software use experience of a user is enhanced.

The invention relates to the technical field of oil field geological prediction, in particular to an oil field geological parameter intelligent prediction system based on machine learning, which acquires static geological data and environmental data in real time through a data acquisition module, and performs noise reduction, normalization and cleaning on the acquired data through a data preprocessing module, so as to obtain an oil field geological parameter prediction result. The feature extraction module adopts an XGBoost model and a long-short-term memory network model to process static features and time sequence data respectively. And the model optimization and self-adaption module dynamically adjusts model parameters according to real-time feedback data by using a reinforcement learning algorithm so as to ensure the accuracy and adaptability of a prediction result. The visualization module provides visual display of a prediction trend, a geological data prediction value and a risk indicator, and helps an operator to make a decision based on data driving. According to the method, the prediction precision of the oil field geological data can be effectively improved, the adaptability to environmental changes is enhanced, and a scientific basis is provided for oil field management and production optimization.

The invention relates to the technical field of computer code upgrading, and discloses an automatic code upgrading method and device based on a compiler and a storage medium. The method comprises the steps that firstly, lexical analysis, grammatical analysis and semantic analysis are conducted on a source code, an abstract syntax tree is generated, then a new standard grammatical rule mapping table is constructed, and a new standard grammatical rule mapping table is generated; and traversing the abstract syntax tree, querying whether the nodes of the abstract syntax tree can be queried in the mapping table, outputting the character strings mapped to the queried nodes, and normally outputting codes conforming to node semantics for the nodes which are not queried. The abstract syntax tree of the original code is automatically traversed, and node matching and conversion are performed according to the syntax rule mapping table of the new standard, so that the need of manual intervention is greatly reduced, the automation degree of code migration from an old standard to the new standard is improved, a large amount of manpower and time cost is saved, and the migration problem caused by human errors is reduced.

The invention belongs to the technical field of allele typing, and discloses a gene haplotype typing method and device based on sequencing data and a medium, and the method comprises the following steps: obtaining to-be-detected gene sequencing data from a to-be-detected sample; splitting the sequencing data into genes according to a reference sequence, and performing variation information detection and variation information filtering; after sequence splitting is carried out on the basis of the sequence obtained after variation information filtering, the haplotype sequence obtained after sequence splitting is corrected, and a to-be-detected gene haplotype typing result of the to-be-detected sample is obtained. According to the method, complex calculation is simplified by adopting a mode of firstly splitting sequences into genes, the method does not completely depend on sequence comparison results, and similar typing is finally evaluated by adopting a mode of combining comparison with backtracking variation information scoring, so that typing difference information can be effectively refined, and interference of sequencing data noise on the results is reduced; and a haplotype result is verified for multiple times by adopting a primary typing and correction mode, so that the result accuracy is higher.

The invention discloses an automatic test method based on natural language processing, which comprises the following steps: S1, generating a test case: performing semantic analysis on a software requirement document or a test requirement by utilizing a natural language processing technology, extracting key information, and combining the extracted test information and a preset test case template to generate a test case; a preliminary test case is automatically generated; the key information comprises a test purpose, an operation step and an expected result; s2, analyzing the test case; s3, generating a test script; s4, executing the test script; and S5, analyzing a test result. According to the automatic test method based on natural language processing, the test requirements described by the natural language can be automatically analyzed, the test case is generated, the test is automatically executed, and the test report is finally generated, so that the software test efficiency is improved, the workload of manually compiling and executing the test case is reduced, and the test efficiency is improved. And the coverage rate and the accuracy of the test are improved, more software defects can be found, and the quality of software products is guaranteed.

The invention discloses a multi-source information fusion query method based on RAG Fusion, which comprises the following steps: receiving original query data input by a user, and carrying out preprocessing and expansion processing on the original query data to obtain an expanded query set; retrieving each extended query in the extended query set in a preset vector library by using a plurality of retrieval strategies to obtain a document set corresponding to each retrieval strategy, and reordering all documents in the document set to obtain a document list; dynamic context construction is carried out on documents in the document list, and a context document set with weights is generated; performing sentence-level segmentation on each document in the context document set, extracting fragments related to the original query data from segmented sentences by utilizing a pre-trained question and answer model, and performing duplicate removal and combination on the extracted fragments to generate an information unit set; and inputting the original query data, the context document set and the information unit set into a pre-trained large-scale language model to generate a target answer.

The invention discloses a user experience design method based on a natural language processing technology, relates to the technical field of natural language processing technologies and user experience design, and adopts the natural language processing technology to intelligently collect and analyze user feedback information. The method is constructed on the basis of advanced natural language understanding and sentiment analysis technologies, and an intelligent feedback management system realizes efficient mining and deep insight of mass text data and covers deep information extraction, sentiment recognition and quantification and automatic report generation; according to the application of the natural language processing technology in the field of user feedback collection and analysis, not only is the crossing from passive receiving and manual processing to active detection and intelligent analysis realized, but also the user experience is improved through seamless voice interaction and accurate path guidance. The user experience and the response speed of the enterprise to the user demand are greatly improved, and the intelligent upgrading of the feedback system is really realized.

The invention relates to the technical field of network advertisements, in particular to an advertisement data management system based on market trend analysis, which comprises a data acquisition module, an analysis module, a prediction module, a conversion rate calculation module and an adjustment module. The advertisement effect is reflected by acquiring click and purchase data after advertisement putting, the change trend of user behaviors is accurately recognized through the analysis module, and the user change rate is calculated, so that data support is provided for an advertisement putting strategy, and the advertisement putting strategy is more accurate by analyzing historical data, predicting the future purchase trend and comparing with predicted data in real time. The conversion rate change of the advertisement is accurately evaluated, a basis is provided for optimizing the advertisement effect, whether the advertisement putting duration needs to be adjusted or not is judged according to the comprehensive analysis of the user change rate and the conversion rate change rate, efficient utilization of advertisement resources is ensured, the accuracy and flexibility of advertisement putting are remarkably improved, the conversion rate and the return on investment of the advertisement are facilitated, and the user experience is improved. And continuous optimization and improvement of the advertisement effect are realized.

The invention discloses an object data detection system, which comprises a scanning device, a projection device and a processor, and is characterized in that the scanning device is used for scanning a target object to obtain target scanning data of the target object and sending the target scanning data to the processor; the processor is used for acquiring standard object data corresponding to the target scanning data, determining target projection data corresponding to at least part of object areas of the target object according to a projection pose relation between the projection device and the target object and the standard object data, and sending the target projection data to the projection device; and the projection device is used for projecting the target projection data onto the target object. The target projection data is projected to the target object through the projection device, the workpiece deviation data can be visually observed, the readability of the workpiece deviation data is improved, and the correction accuracy of the workpiece deviation data is further improved.

The invention relates to the technical field of appearance defect monitoring, in particular to a rubber whole mold appearance defect detection method and system based on machine vision. The method comprises the following steps: acquiring rubber whole mold parameter data; performing O-shaped ring inner and outer diameter setting on the rubber whole mold based on the rubber whole mold parameter data to obtain rubber whole mold built-in O-shaped ring inner and outer diameter adjustment data; performing first surface overall shooting on the rubber whole mold according to the inner and outer diameter adjustment data of the O-shaped ring arranged in the rubber whole mold to generate a first overall appearance image of the standard rubber whole mold; performing detection area division on the first overall appearance image of the standard rubber whole mold to generate rubber whole mold detection area data; and comparing the rubber whole mold detection area data with a preset detection area number range to generate rubber whole mold product specification data. Through accurate parameter setting, automatic region division, focal length adjustment, high-precision defect detection and comprehensive report generation, the accuracy and comprehensiveness of defect detection are improved.

The invention discloses an intelligent security monitoring and early warning method and system for an industrial control network, relates to the technical field of network security monitoring, and can collect multi-dimensional data such as network traffic, user behaviors and equipment states in real time through a data acquisition module and a system to ensure the timeliness and comprehensiveness of monitoring. Therefore, potential security threats can be quickly identified, and the overall security protection capability is improved. And the data preprocessing module cleans and standardizes the collected data, so that the data quality and consistency are improved, a reliable basis is provided for subsequent risk assessment, and misjudgment caused by data inconsistency is reduced. And the risk assessment module calculates a comprehensive risk index through a multi-dimensional assessment formula, different types of security threats can be identified more accurately, and a scientific basis is provided for a subsequent early warning mechanism. The multi-level early warning mechanism module divides the risk into a low level, a middle level and a high level according to the comprehensive risk index, and a targeted response strategy can be realized.

The invention relates to the technical field of chip design, in particular to a timing constraint automation generation method. According to the method, the actual demand of the clock needing to be created is determined based on the design document, and then the clock list is generated based on the actual demand; the content of the clock list comprises a PLL source, a clock type, a clock name, a source path, a main clock name, a main clock source path, a frequency, a main clock duty ratio, a derivative clock duty ratio, a frequency division coefficient, whether the clock has a cross-clock requirement or not, and the mutual relation between the created clocks; executing the script in a clock list which needs to be read by the configuration script and the specified script; and traversing all options in the clock list by the script, generating a time sequence constraint, and automatically finishing GCA check. According to the method, timing constraint compiling and checking can be automatically achieved through the script only by completing output of the clock list, and the method for compiling the timing constraint is accurate and easy to maintain.

The embodiment of the invention provides an inspection report generation method and device for a cloud network networking scene, a medium and a product, and relates to the technical field of computers, and the method comprises the steps: retrieving a document related to the semantics of abnormal item information from a predetermined knowledge base based on the abnormal item information, and taking the document as the context information of the abnormal item information; the abnormal item information is used for indicating an abnormal detection result of any inspection item of a detection object, and the detection object is one or more products used for cloud network networking; based on the context information and the exception item information, performing exception summary on the inspection items by using a predetermined large language model to obtain an exception item summary text; and generating an inspection report by using the abnormal item summary text. In the scheme, the context information can enhance the semantic understanding of the large language model for the abnormal item information, the abnormal item summary text generated by the large language model can more accurately describe the abnormal item information, the accuracy and readability of the inspection report are improved, and the interpretation difficulty of the inspection report is reduced.

The invention belongs to the technical field of artificial influence weather, and discloses an artificial rain and snow enhancement effect evaluation method based on a layer-by-layer iteration mode, and the method comprises the steps: determining a catalyst diffusion track and an affected region through employing a high-resolution numerical mode, the airplane observation data comprises the background ice crystal number concentration of the affected area and the ice crystal number concentration under the condition that the catalyst is used; reading the ice crystal number concentration of the sowing layer from the observation data, and calculating the correlation between the L0 ice crystal number concentration of the sowing layer and the L1 radar reflectivity factor of the first layer; calculating correlation coefficients of radar reflectivity factors between every two adjacent layers from the sowing layer to the ground layer by layer; a high-resolution numerical mode is adopted to simulate diffusion of a catalyst, the ice crystal number concentration of an affected area in airplane observation data is read and substituted into the relational expression, radar reflectivity factors of all layers are calculated layer by layer in an iterative mode, and the precipitation rate is calculated according to the radar reflectivity factors of all layers; and calculating the rainfall rate under the background ice crystal number concentration, comparing, and quantitatively evaluating the artificial rain and snow increasing effect.

The invention discloses a city information model management system based on a CIM basic platform and an analysis and display method, provides an innovative city information management and display solution, takes the CIM basic platform as a core, and aims to construct a high-precision and dynamically-updated city three-dimensional information model management system through an integrated information technical means. The urban space structure, the function layout and the infrastructure state can be visually and interactively explored, so that construction and development of a smart city are promoted, and the intelligent level and the comprehensive efficiency of urban management are improved.

The invention discloses a low-code management system and method based on the AIot Internet of Things, and relates to the technical field of code management, the system comprises a template learning optimization module, a component dynamic adaptation module, a demand conversion module, a code annotation generation module and a code compatibility conversion module; the template learning optimization module is used for automatically extracting optimization points and updating template settings by analyzing historical cases and user data so as to improve the applicability of the template in practical application; according to the invention, through the template learning optimization module, deep analysis of historical cases and user data is realized, optimization points are automatically extracted, template setting is updated, the applicability and development efficiency of the template in practical application are remarkably improved, and through the automatic template updating process, manual intervention is reduced, the development cost is reduced, and the development efficiency is improved. And meanwhile, the stability and compatibility of the system are kept.

The invention provides a text structured extraction method and system, a terminal and a medium, and particularly relates to the technical field of natural language processing and information retrieval, and the scheme comprises the following steps: obtaining an analysis text of a target text, adding an index number based on the analysis text, and splicing to obtain a target spliced text; obtaining a plurality of training data sets according to the plurality of texts; performing fine tuning on a preset large language model by using the plurality of training data sets to obtain a fine-tuned large language model; and based on the target spliced text, performing processing through a fine tuning large language model, and generating structured content of the target text. According to the scheme, the index numbers are fused into the text paragraphs, the key information of the target text can be pointed through the index numbers, the ability of a large language model to accurately and comprehensively understand the whole text structure is improved, it can be ensured that the structured content of the generated target text keeps the hierarchical structure of all the paragraphs in the text, and the user experience is improved. And the readability and accuracy of the structured content of the target text can be improved.

The invention provides a method and device for supporting complex product manufacturing process model reconstruction. A user can input manufacturing process reconstruction requirements according to a language structure specified by a manufacturing process reconstruction template, wherein the manufacturing process reconstruction requirements comprise production units, manufacturing activities needing to be added, manufacturing targets and manufacturing constraints; the method comprises the following steps: analyzing a reconstruction demand according to a manufacturing process reconstruction dictionary, performing information extraction and element matching in a manufacturing process model library according to a production unit and manufacturing activities needing to be added to obtain a primary manufacturing process model scheme, and optimizing the primary manufacturing process model scheme according to a manufacturing target and manufacturing constraints to obtain a manufacturing process model; and a final manufacturing process scheme is reconstructed, and a model-driven self-adaptive reconfigurable manufacturing process function is realized. By using the method, rapid generation of the complex product manufacturing process model can be realized, and the efficiency and the quality of product design are improved.