12 results about "Deep processing" patented technology

The invention belongs to the technical field of nuclear power station file management, and particularly relates to an intelligent nuclear power station file classification and retrieval system based on artificial intelligence. The file acquisition module is responsible for uniformly acquiring and accessing multi-modal files in the nuclear power station; the preprocessing and natural language processing module is used for carrying out deep processing and semantic analysis on the collected multi-modal document; the dynamic classification module is used for carrying out multi-dimensional automatic classification on the multi-modal document based on a deep learning model and a nuclear power industry knowledge graph; the dynamic knowledge updating module is used for continuously monitoring new documents and user feedback and keeping adaptability to industry changes; the intelligent retrieval module is used for providing a query function for a user through semantic vectorization and a large-scale rapid retrieval technology; and the intelligent recommendation module is used for providing targeted document recommendation for the user through association analysis and collaborative filtering. According to the method, the problems of low classification efficiency, insufficient retrieval accuracy, weak dynamic adaptive capacity and limited multi-modal data processing capacity are solved.

The invention provides a deep processing method and system for a digital delivery result, and relates to the technical field of data processing. A delivery result file set is disassembled and recombined into a unified object main data set and a three-dimensional entity set; each object attribute record and each object relation record have a unified object identifier, a source identifier and evidence positioning information at the same time, and multiple sets of coding calibers of the same object can be gathered to the same unified object identifier; refined model replacement is executed by taking a unified object identifier as an anchor point in three-dimensional treatment, continuity of a composition relationship and a connection relationship is kept, and after project handover and commissioning, online and field inconsistency found by operation and maintenance personnel is converted into a revision chain capable of being rechecked, judged and audited, so that the operation and maintenance efficiency is improved. Therefore, the problems that the unstructured data is difficult to reuse, the coding calibers are different, the object relationship is easy to lose and the data in the operation and maintenance period is not credible are solved.

This application discloses a method, apparatus, electronic device, and storage medium for constructing a gait recognition enhancement model. The method and apparatus are applied to an electronic device to construct a gait recognition enhancement model capable of multimodal gait recognition of documents. Specifically, in response to a user's model construction request, multimodal data is extracted from multiple documents; the multimodal data undergoes deep processing and standardization to achieve deep alignment, obtaining standardized features; a bio-inspired dynamic fusion mechanism is used to dynamically fuse the standardized features to obtain semantic information; and a generative large language model is used to train the original documents and semantic information to obtain the gait recognition enhancement model. This model can obtain gait information from documents, thereby improving researchers' efficiency in reading documents and the convenience of academic research, assisting researchers in quickly and accurately understanding domain knowledge, and thus helping researchers improve their learning and research capabilities.

The invention discloses a data processing method and device for VR interactive training of a cross-country container forklift. The method comprises the steps that VR interactive training data information of a user is acquired; the user VR interactive training data information comprises an action data set and an expression data set; processing the action data set to obtain a user action evaluation result; processing the expression data set to obtain a user emotion evaluation result; and according to the user action evaluation result and the user emotion evaluation result, performing personalized training suggestion and training content dynamic adjustment on the VR interactive training system. According to the invention, through efficient acquisition, deep processing and intelligent analysis of multi-dimensional data generated in the training process, the forklift driving operation level and safety awareness of trainees are accurately evaluated, the training result is fed back in real time, and the training strategy is dynamically adjusted, so that the quality and efficiency of the forklift driving VR interactive training are improved, and the training experience is improved. And the actual training cost and the safety risk are reduced.

The invention discloses a wood veneer sound-absorbing composite material and a preparation method thereof, and belongs to the technical field of building materials. The material comprises a decorative surface layer and a sound-absorbing base material layer, the decorative surface layer is an aluminum foil veneer formed by compounding a natural veneer and an aluminum foil layer; the sound-absorbing base material layer adopts a colored velvet plate; and the aluminum foil wood veneer and the colored velvet plate are hot-pressed and compounded to form an integrated plate body through the aluminum foil layer of the aluminum foil wood veneer. The preparation method comprises the steps that S1, the aluminum foil veneer is prepared, wherein the natural veneer and the aluminum foil layer are compounded to obtain the aluminum foil veneer; s2, preparing a base material: cutting a colored velvet plate; s3, laminating and compounding to form an integrated plate body; s4, waxing the surface; and S5, carrying out integrated deep processing to form the designed sound absorption structure. The invention relates to a novel building material with functions of decoration, sound absorption and noise reduction, in particular to a material prepared by taking natural veneers and recyclable colored velvet plates as main raw materials through processes such as dyeing, compounding, waxing and CNC (computer numerical control) engraving, and application of the material in various public places.

The application provides a glass deep processing process analysis system and method based on AI cloud data, the method comprising: performing semantic analysis and structured packaging on the obtained process query text in combination with a glass industry term library to obtain a structured query instruction; performing database table association, list matching and context enhancement on the structured query instruction based on a bidirectional mode link algorithm, and performing sentence optimization on the matching result after context enhancement based on a binary selection strategy to obtain a primary query sentence; performing logical self-correction on the primary query sentence based on a multi-round syntax tree traversal method to obtain a database query sentence; querying the original data set from the glass processing database by using the database query sentence, and performing multi-dimensional data analysis on the original data set based on a dynamic threshold anomaly detection algorithm and a mutual information algorithm to obtain an analysis result set; and generating an interactive report according to the analysis result set.

This invention discloses a lightweight deep processing method based on BIM, belonging to the field of BIM lightweight technology. It involves constructing the complexity of a target model from the structural data obtained through identification. If the obtained complexity exceeds expectations, a lightweight strategy is provided for the target model based on several model features using a model optimization knowledge graph. The target model is simplified, and the accuracy of the simplified model is analyzed. If the obtained model accuracy exceeds expectations, the data within the target model is compressed. After performance testing of the target model, a performance coefficient is constructed from the test data set. If the obtained performance coefficient is not lower than its previous value, the optimization degree of the target model is constructed. If the optimization degree exceeds expectations, a re-optimization instruction is issued. This completes the lightweight processing of the model, reducing its bloat, maintaining model performance, improving model operating efficiency, and enhancing the efficiency of subsequent work.

This invention relates to the field of quality information traceability technology, and discloses a method and system for tracing the quality information of Epimedium sagittatum. The method includes acquiring basic data and planting parameters of the current batch of Epimedium sagittatum seedlings; processing the basic data and planting parameters using a hash algorithm to generate a basic query code; using the basic query code as a parent node and combining it with growth data to generate a growth code; generating a raw material code for the current batch by combining it with process parameters, and associating the raw material code with the growth code; generating an outbound code using a timestamp and the raw material code; generating auxiliary material codes for auxiliary materials involved in deep processing, associating the auxiliary material codes with the outbound code, and generating a product code by combining it with production parameters. This invention facilitates rapid identification of the source and responsible link of quality fluctuations, sets incremental collection frequencies and differentiated collection indicators for different stages, improves the sufficiency of quality assessment basis, and reduces the risk of tampering or falsification during the process.

The invention provides an event trigger word determination method and equipment, and the method comprises the steps: sequentially carrying out initial candidate trigger word extraction, supplementary candidate trigger word extraction and deep processing of at least one iteration round on a target text based on a pre-trained lightweight large model through a preset event trigger word extraction instruction and a sample set, obtaining a candidate set containing each candidate trigger word corresponding to the target text; according to the semantic similarity between each candidate trigger word in the candidate set and each preset historical statement and each historical event trigger word, selecting a preset number of candidate trigger words from the candidate set as target trigger words; and filtering the target trigger word based on a preset similarity score threshold and event type clustering to obtain an event trigger word corresponding to the target text and an event type corresponding to the event trigger word. According to the method, the event trigger word extraction speed can be ensured, and the event trigger word extraction precision and classification precision can be improved at the same time.

The invention discloses an engineering audit data compliance checking method and system based on a Transform model, and relates to the technical field of engineering audit data checking, and the method comprises the steps: S1, collecting financial data and material consumption data in the whole process of engineering audit; according to the method, structural analysis and deep processing are carried out on project auditing full-process data by relying on the context semantic understanding capability of a Transform model, and accurate semantic matching of auditing data and compliance terms is realized by combining dynamic construction of a compliance rule knowledge base and utilizing a self-attention mechanism, so that the auditing accuracy is improved. The problems that in the prior art, manual checking is low in efficiency and insufficient in accuracy, and a traditional rule matching method is insufficient in semantic understanding and poor in adaptability are solved, intelligence and high efficiency of engineering audit data compliance checking are achieved, the comprehensiveness of checking coverage and the accuracy of anomaly recognition are improved, the scene adaptability of the checking method is enhanced, and the checking efficiency is improved. And reliable technical support is provided for engineering audit.

The invention relates to the technical field of intelligent patrol assistance, in particular to an intelligent patrol assistance method and system based on large language model fine tuning, and the method comprises the steps: firstly deploying a large language model LLM after instruction fine tuning in a local government affair server; a user uploads a patrol document, and a back end executes preprocessing; constructing a patrol clue vector library, performing semantic comparison on the preprocessed text and the patrol clue vector library, and identifying potential clues; calling a built-in Prompt template to generate a first draft of a patrol report; in combination with a thematic lexicon and LLM situation judgment, labeling type labels and scores for the suspected high-risk paragraphs; cross-text clustering is carried out on the multiple documents, and repeated problem types are recognized; outputting the structured table and the natural language report; according to the method, hundreds of documents can be processed in batches through fusion application of the local deployment instruction fine-tuning large language model and the semantic retrieval technology, automatic deep processing of patrol documents is achieved, and the working efficiency is remarkably improved.

The invention discloses a multi-modal semantic segmentation method and a storage medium, and the method comprises the steps: obtaining a color feature map and a depth feature map of any ith hierarchy through a feature extraction module of a color processing branch and a depth processing branch at the hierarchy based on one or more groups of multi-modal sample images composed of a color image and a depth image; when i is greater than or equal to 2, inputting the color feature map and the depth feature map of the hierarchy into a modal feature selection module corresponding to the hierarchy to obtain a fusion feature map of the hierarchy; inputting the feature map, the color feature map of the level and the depth feature map of the level into a cross-modal fusion module of the level to obtain an enhanced fusion feature map of the level; and obtaining a semantic segmentation result corresponding to each group of multi-modal sample images according to the enhanced fusion feature map of the last level. The complementarity of the multi-modal features is enhanced through the modal feature selection module, the fusion of the multi-modal features is enhanced through the cross-modal fusion module, and high-precision real-time semantic segmentation is realized.