237results 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 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 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 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 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 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 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.

The invention relates to the technical field of single cell data processing, in particular to a database visualization method based on single cells. The method comprises the following steps: acquiring a single cell data set; standardizing the single cell data set to obtain standardized single cell data; performing high-dimensional feature extraction on the standardized single-cell data to obtain single-cell high-dimensional feature data; and performing nonlinear dimension reduction processing on the single-cell high-dimensional feature data to obtain single-cell dimension reduction data. Performing data clustering on the single cell dimension reduction data to obtain single cell clustering data; performing gene differential expression extraction on the single cell clustering data to obtain differential expression gene data; multi-modal data fusion analysis is carried out on single cell data through a data processing technology, a feature mapping technology and a visualization technology; and dynamic weight division is carried out on the single cell database, so that the effect of visualization of the single cell database is enhanced.

The invention discloses a CLCC converter multi-source information carrier construction method and system based on a knowledge graph, and the method comprises the steps: obtaining related data of a CLCC converter, and constructing and storing triple information in an entity-attribute-attribute value manner based on the data; constructing a knowledge hierarchical structure of the converter based on the converter equipment entity; constructing a knowledge graph of the converter multi-source information based on knowledge fusion, and establishing knowledge relationship connection and knowledge fusion; dynamic circulation of CLCC transverter transparent information is realized based on a knowledge hierarchical structure of CLCC transverter multi-source information; and carrying out network topology modeling on the knowledge graph of the CLCC converter by using the graph database, and constructing a transparent information carrier of the CLCC converter. According to the method, the problems that the CLCC multi-source operation and maintenance information processing efficiency is low, the fragmentation problem is serious, the data structure, the technical architecture, the construction standard and the construction content are not uniform, and an effective data organization framework is difficult to form are solved.

The invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a business report generation method, which comprises the following steps: acquiring business data, inputting the business data into a text generation model, and generating a plurality of business description texts; inputting the business data into an image generation model to generate a plurality of business display images; performing association matching on the service description text and the service display image to obtain a text and an image which are associated with each other; and integrating the mutually associated text and image to generate a complete report. According to the method, the text generation model and the image generation model are combined, and the generated text and image are intelligently matched and integrated, so that the content richness and readability of the report are improved. Meanwhile, through automatic data processing and generation steps, the generation efficiency is improved, and the accuracy and consistency of data description and image display in the report can be ensured.

The invention discloses a code abstract generation method oriented to semantic structure feature joint enhancement. According to the method, an encoder-decoder architecture is followed, and a multi-form combined semantic feature enhancement method is adopted to automatically generate a code abstract. Wherein the encoder learns code semantics at token and statement levels, and the decoder receives code embedding and generates a code abstract in combination with an attention mechanism. Unlike a single tree or graph coding process, the method uses graph representation to enhance the interval divided tree structure. The joint decoder aggregates the text sequence information and the structure sequence information containing the location node features, and predicts and generates a model understood code summary text. According to the method, the problems of repetition and redundancy of code texts with different lengths caused by disordered code text features are relieved. In a relatively complex code text data set, a word ambiguity phenomenon caused by insufficient knowledge information understanding is reduced, and a code abstract with relatively high quality is generated. Meanwhile, the method has good convergence performance.

The invention provides an annotation data generation method and system based on a large language model, and the method comprises the steps: S1, obtaining a structured text of a representative contract of the same category, and generating a corresponding information extraction template based on the obtained structured text of the representative contract; s2, generating annotation data in batches based on the information extraction template and all contract texts in the same category; s3, summarizing different types of annotation data and corresponding contract texts, generating an annotation data set, and performing fine adjustment on the large language model by utilizing the annotation data set to obtain a fine-adjusted large language model; and S4, marking the contract text based on the fine-tuned large language model.

The invention discloses an atlas digital analysis method and system based on a notarization file database, and the method comprises the steps: S1, obtaining and analyzing notarization file data in the notarization file database, and carrying out the preprocessing of the notarization file data; s2, constructing map nodes according to the extracted key information elements; s3, carrying out attribute assignment on nodes and relation edges in the graph structure; s4, storing the atlas structure to a notarization file atlas database; s5, receiving a query request of a user; s6, querying demand parameters based on the query conditions; s7, outputting a query result, and generating a graph structure containing a node association relationship; and S8, outputting an analysis result including potential correlation among the nodes, an event development trend and pattern recognition output. According to the invention, the problems of low data association degree and low query efficiency in a traditional archive management system are effectively solved.

The invention relates to a method for quantitatively monitoring the pollution degree of groundwater. The method comprises the steps of near-infrared hyperspectral imaging, construction of a prediction model and fitting of a prediction function. The invention further provides a groundwater analysis system and application of the method. According to the method, a hyperspectral imaging technology is adopted to shoot a mixed sample of organic pollutants and water, key features of a sample image are obtained by combining an image preprocessing technology and a feature extraction technology, the sample features with remarkable performance are used as training data, and a machine learning algorithm is applied to obtain training data; the model can accurately predict the water-oil volume ratio in a sample, and meanwhile, provides spatial distribution of the organic pollutants in the environment, so that an efficient and innovative solution is provided for quantitative analysis of the organic pollutants.

The invention provides a heeling angle measuring device and a heeling angle measuring method for a ship inclination test. The heeling angle measuring device for the ship inclination test comprises a supporting bracket, a reduction gear set, a pendulum bob, a pointer and a side magnet strip, the supporting bracket comprises a bottom plate and a side plate which is perpendicular to the bottom plate and fixed to the bottom plate, a shell of the reduction gear set is fixed to the rear end face of the side plate, and the pendulum bob is fixedly connected to the lower portion of an output shaft of the reduction gear set. An input shaft of the reduction gear set penetrates through a through hole of the side plate and then is fixedly connected with a pointer on one side of the front end face of the side plate, a dial is arranged on the front end face of the side plate to observe the rotation angle of the pointer, a side face magnet strip is fixed to the front end face of the side plate, the supporting support is made of non-metal materials, and the side face magnet strip is used for making the pendulum bob swing still. According to the heeling angle measuring device for the ship inclination test, the accuracy of ship heeling angle measurement can be improved, and meanwhile the size of the heeling angle measuring device is small.

The invention provides a complex industrial contract information extraction method and system based on a large language model, and the method comprises the steps: S1, carrying out the clustering analysis of different obtained industrial contract texts, and determining a cluster where each contract text is located; s2, stratified sampling is carried out on each cluster, and representative samples are obtained; s3, carrying out key content extraction meeting a preset requirement on the representative sample corresponding to each cluster; obtaining a corresponding structured text based on the extracted key content meeting the preset requirement; s4, labeling the structured text to obtain labeled data; step S5, acquiring annotation data of all clusters to generate an annotation data set, and performing fine tuning on the large language model by using the annotation data set to obtain a fine-tuned large language model; and S6, deploying the fine-tuned large language model into a production environment, and extracting key information, meeting a preset requirement, of the unlabeled contract text.

The invention relates to an operation log recording method, device and equipment based on an SPI mechanism. The method comprises the steps that a loading operation log package is started, and log variable parameters are read; starting a log component to form log information, and determining a log dropping mode according to the number of logs to be processed; scanning, loading and defining an SPI function, and dropping the to-be-processed log into a disk according to the log dropping mode; a monitor is initialized, and whether the system runs normally or not is judged through the monitor. At least code readability and maintainability can be improved, memory consumption is reduced, performance is improved, and compatibility is improved.

The utility model provides an electronic tag applied to an electric pole tower. The electronic tag comprises a passive radio frequency unit and an energy obtaining unit, the energy obtaining unit is used for obtaining external energy to generate electric energy and directly outputting the electric energy; the power supply end of the passive radio frequency unit is connected with the electric energy output end of the energy obtaining unit; the radio frequency end of the passive radio frequency unit is used for receiving an external radio frequency signal and sending out a radio frequency signal. External energy is obtained through the energy obtaining unit to generate electric energy, and then the electric energy is directly output to the passive radio frequency unit, so that the passive radio frequency unit obtains extra energy input on the basis that energy is generated by receiving external radio frequency signals originally, the sensitivity of the passive radio frequency unit is improved, and the readable distance of the electronic tag is increased; meanwhile, compared with an existing mode that power is supplied through a battery, power is directly supplied to the passive radio frequency unit through the energy obtaining unit, battery power supply is not needed, and the service life of the electronic tag can be greatly prolonged.

The invention provides a geological map standard symbolization method, electronic equipment and a storage medium, and relates to the technical field of geological map standard symbolization, and the method comprises the steps: obtaining target vector data related to geological data to be rendered; obtaining an initial annotation font list A; adding a preset field to each initial annotation font in the A to obtain a middle annotation font list B corresponding to the A; establishing a first mapping table QT; encoding the middle labeled fonts in the QT to obtain a target font library C; slicing the target fonts in the C to obtain a vector slice list set D corresponding to each zoom level; rendering the target vector data according to the zoom level of the user in the preset historical time period T0 and the C; according to the method, the problems that the symbolization technology generally has insufficient flexibility and customization of a symbolization system, the symbolization process is tedious, errors are easy to introduce and the like when the symbolization technology is used for processing a complex thematic map can be avoided.