181results about How to "Improve rationality" patented technology

This application provides a display device and a household appliance. The display device includes a first display section and a knob assembly. The first display section extends along a first direction. The knob assembly is arranged adjacent to the first display section in the first direction. The knob assembly includes a knob operating section and a second display section disposed radially inside the knob operating section. The dimension of the first display section in a second direction is not less than the dimension of the second display section in the second direction and not greater than the outer diameter of the knob operating section. The first and second directions are perpendicular. In this application embodiment, the display dimension of the second display section in the second direction is between the dimension of the second display section in the second direction and the outer diameter of the knob operating section. This allows the second display section to have a suitable size to match the knob operating section, and the overall size is more ergonomic, which helps to improve the overall layout rationality and visual effect of the display device.

The present disclosure provides a search result sorting method and device, computer equipment and a storage medium, wherein the method comprises: obtaining search results matched with a search term, the search results comprising first results of a first genre and at least one second result of a second genre other than the first genre; the second result comprising at least one result document; for any result document in the second result, determining a document feature corresponding to the result document according to text attribute information of the result document, dimension information of the result document in a plurality of preset characteristic dimensions, the search term and source information of the search term; determining a document association feature corresponding to the second result according to the document feature of each result document in the second result; and sorting the first results and the second results according to the document association feature of each second result and a result click rate of each first result.

This application discloses a method, system, device, medium, and product for scaling up distributed model services, relating to the field of big data processing. The method includes collecting a basic dataset of service metrics, analyzing inter-service call relationships to construct service groups and quantifying the independence of entry services, calculating request pressure values ​​and total resource utilization by combining historical resources and business data, predicting scaling trends and determining adjustment methods, and executing scaling based on independence and adjustment methods. Through multi-dimensional metric fusion and service topology relationship analysis, service priorities are clarified, avoiding decision-making biases based on single metrics. This solves the problems of blind scaling decisions and the inability to balance service stability and resource utilization in related technologies, achieving the technical effects of improving scaling accuracy, ensuring service stability, and enhancing resource utilization efficiency.

This invention relates to a method for predicting sandbar response under the combined effects of water level and waves, considering hysteresis, during storms. The method includes: starting with initial sandbar morphology data of a target shoreline during a specific storm event, using a sandbar evolution model considering hysteresis to predict sandbar response, and outputting a predicted curve of sandbar position change throughout the storm process. The sandbar evolution model calculates storm dynamic forcing based on historical storm hydrodynamic data, establishes a model relating relaxation timescales to storm dynamic forcing, obtains a relaxation timescale characterizing the hysteresis characteristics of the sandbar response, and establishes a model relating the sandbar equilibrium position to hydrodynamic forcing based on historical hydrodynamic forcing data and sandbar position changes, obtaining... t The sandbar equilibrium position at any given moment. This invention can more accurately simulate sandbar behavior throughout the entire storm process, especially during the attenuation phase, significantly improving the practicality and reliability of sandbar response prediction throughout the entire storm process (including the aftereffect period).

The application relates to a question and answer matching method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining a user question and a plurality of candidate questions corresponding to the user question; screening target candidate questions from the candidate questions; the target candidate question is a candidate question having at least one same character with the user question; for any same character corresponding to any target candidate question, determining a user word in which the same character is located in the user question, and determining a candidate word in which the same character is located in the target candidate question; in the case that the user word and the candidate word are different, adjusting the semantic similarity according to the difference between the semantic represented by the user word and the semantic represented by the candidate word; and screening a target question matched with the user question from the candidate questions according to the new semantic similarity corresponding to each target candidate question. The method can improve the accuracy of question and answer matching.

The application discloses a kind of non-cooperative target centroid intelligent positioning method and system fusing multi-dimensional physical constraint.The method is directed to sparse, noisy point cloud data, and constructs a comprehensive evaluation function containing four-dimensional information of geometry, orbital dynamics, time sequence continuity and surface physical properties;Using a two-stage solution framework of surrogate model and hybrid optimization, first, a lightweight neural network surrogate model is used with a differential evolution algorithm for global coarse search, and then switching to a high-fidelity orbit model combined with an adaptive particle swarm optimization algorithm for local fine search;Finally, the optimal state estimation and its covariance matrix, evaluation decomposition and other decision support information are output.The application improves the accuracy, robustness and computational efficiency of centroid positioning, and enhances the interpretability of the results, suitable for on-orbit servicing, space debris removal and other high-risk space missions.

This application relates to a scene recognition method, apparatus, computer device, storage medium, and product. The method includes: acquiring multiple types of raw data and determining basic indicators based on the raw data; the raw data is data collected from the target vehicle; extracting semantic features of each basic indicator and generating semantic indicators based on the semantic features; aggregating the semantic indicators to determine combinations of semantic indicators, and generating scene indicators based on the combinations of semantic indicators; extracting features based at least on the scene indicators to obtain scene features, and determining a scene recognition result for the target vehicle based on the scene features. This method can improve the accuracy of scene recognition.

This invention belongs to the field of rail vehicle technology. It proposes a method and system for adjusting the alignment of workpieces during the intermediate stage of bogie welding. Based on the design 3D model of the bogie workpiece and the process scaling requirements, key dimensions are selected and adjusted to construct a virtual intermediate model. Feature points are collected from the key feature surfaces of the virtual intermediate model to obtain reference values ​​for each feature point. A 3D scan of the actual bogie workpiece during the intermediate welding stage is performed to acquire point cloud data. Feature points are collected and processed from the corresponding key feature surfaces of the point cloud data to obtain the actual values ​​of each feature point. By comparing the reference values ​​and actual values ​​of each feature point, the deviation of each feature point is obtained. For the key dimensions of the bogie workpiece, a scribing weight mechanism is introduced to assign weight priorities to each key dimension. Based on the deviation of each feature point and the weight priorities, the position of the baseline of the key feature surface is adjusted. This invention achieves a closed-loop process from model adaptation and data comparison to baseline adjustment.

The present application relates to the technical field of welding control, in particular to a large plate welding equipment control system, comprising a space normalization module, an address generation module, a path screening module, a structure verification module and an interconnection output module.In the present application, in the multi-machine collaborative working environment under strong electromagnetic interference of arc welding, the three-dimensional coordinates of the welding torch contact point are collected with high precision and space normalization processing is performed, which fundamentally eliminates the process data differences caused by different welding postures, a unified sequence number is constructed in combination with the starting timing of the core equipment of the welding power source and the wire feeder, a unique control address is generated by fusing the sequence identifier, the accurate mapping of the physical location of the equipment and the network address is realized, the logical connection sequence is intelligently constructed according to the proximity of the coordinate space, the node and path binding is completed synchronously, the rationality of the connection path and the stability of the communication structure are significantly improved, and the logical order, spatial clarity and control uniformity of the arc welding equipment group collaborative work are ensured.

The application relates to the technical field of supply chain management, and in particular to a supply chain management method, system, device and medium. The method comprises the following steps: receiving order demand information uploaded by a client, selecting multiple candidate combinations capable of meeting the order demand information from supply chain participants, each candidate combination comprising a supplier, a manufacturer and a warehousing party; determining a comprehensive score of each candidate combination, determining a candidate combination with the highest comprehensive score as an optimal combination; obtaining to-be-warehoused orders of the warehousing party in the optimal combination, generating a to-be-warehoused order list according to the order demand information of each to-be-warehoused order; determining a carrier of each to-be-warehoused order in the to-be-warehoused order list, and sending a transportation request of each to-be-warehoused order to the corresponding carrier to guide the execution of a transportation task. The application can realize integrated scheduling of supply chain full-link subject selection and order fulfillment, and improve overall collaborative efficiency and rationality of resource allocation.

This invention provides a method and system for optimizing the deployment of environmental monitoring networks by combining the Internet of Things (IoT) and deep learning. It acquires IoT node perception information and environmental evolution characteristics of the target monitoring area, and constructs a dynamic association architecture that enables real-time bidirectional linkage between node perception and environmental evolution. The dynamic association architecture is then input into a pre-trained intelligent deployment adaptation deep learning model to generate multiple candidate deployment association schemes. These candidate schemes are then cross-adapted and validated, and an intermediate optimized deployment set is obtained by resolving conflicts and fusing advantageous features. Finally, based on the real-time feedback information from the dynamic association architecture, the intermediate optimized deployment set is iteratively adjusted to generate the final optimized deployment scheme for the environmental monitoring network. This invention fully considers the characteristics of IoT nodes and environmental evolution characteristics, achieving dynamic optimization of the deployment scheme and improving the accuracy, comprehensiveness, and real-time performance of environmental monitoring.

The application provides an electronic chart system, method and equipment with water depth change prediction capability, relates to the technical field of marine electronic information technology and marine geographic information, and the system comprises a data acquisition module, a water depth change analysis and prediction module and a risk visualization module. The application superimposes and displays predictive water depth risk information in a standard ECDIS interface through the fusion of official electronic chart data and a dynamic water depth model, so that the existing operation process of the driver can be changed, and enhanced navigation support reflecting the recent seabed change trend can be provided in the case that the chart updating cycle is long.

This invention relates to the field of tunnel engineering, and particularly to a tunnel shotcrete design method, storage medium, and electronic device that considers spatiotemporal effects. The method includes: calculating the final value of vertical deformation pressure and the radius of the plastic zone of the surrounding rock without support based on tunnel foundation parameters and tunnel shotcrete design parameters; calculating the deformation pressure as a function of time using a deformation pressure calculation formula, combining tunnel excavation speed parameters, the radius of the plastic zone of the surrounding rock, and preset shotcrete hardening characteristic parameters; inputting the deformation pressure-time function into a shotcrete load-support structure model, calculating the safety factor of the shotcrete at each time node based on the shotcrete hardening characteristic parameters, and iteratively adjusting the tunnel shotcrete design parameters according to whether the safety factor meets preset requirements, until outputting tunnel shotcrete design parameters that meet the preset requirements. This invention dynamically calculates deformation pressure considering spatiotemporal effects and iteratively adjusts parameters to ensure the load-bearing safety of the shotcrete throughout its entire life cycle and reduces construction risks.

The application discloses a kind of education resource sequence recommendation method, device and equipment based on three-view structure distillation and storage medium, the method includes: based on student-course interaction log, the learning sequence of time sequence course index is constructed, three types of view hypergraph are constructed according to semantic, path, concept structure multidimensional feature, three-view course representation matrix is generated by structure coding fusion, and the recommended list is output by inputting education resource recommendation model;Education resource recommendation model generates student state vector by the coding of Transformer, and the total course score is obtained by fusing three-view branch score and predicted;The present application predicts the education resource recommendation by three-view collaborative scoring from multiple perspectives, accurately captures course representation, effectively depicts learning path high-order law, improves the accuracy, explainability and generalization ability of education resource recommendation in sparse interaction and cold start scene.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

This disclosure provides an order processing method, apparatus, electronic device, medium, chip, and product. The method includes: responding to a user's refund request by obtaining the user's first feedback tone and first feedback text; determining a first risk value corresponding to the user based on the first feedback tone and first feedback text using a pre-trained model; and performing a first processing on the user based on the first risk value. This method, by utilizing the user's first feedback tone and first feedback text to determine the user's risk value, thereby judging whether the user's refund request is reasonable, improves the reasonableness of processing customer refund requests and protects the rights and interests of both customers and merchants.

The present application relates to livestock traceability technical field, specifically for livestock meat slaughtering, cutting and packaging traceability method and system based on internet, the method comprises: collecting quarantine information of livestock individual, obtaining initial traceability data; according to initial traceability data, determine the slaughter batch code, and the initial traceability data source is bound with the slaughter batch code, and the slaughter credible data package is obtained; based on the slaughter batch code, the cutting operation process information of livestock individual is tracked and filed in real time, and the cutting link data chain is obtained; based on the cutting link data chain, the multi-dimensional quality of livestock individual is judged, and the comprehensive quality index is obtained; based on the comprehensive quality index, the intelligent matching planning of meat product is carried out, and the packaging batch planning is obtained; based on the packaging batch planning, the livestock individual is coded and identified, and the product traceability code is obtained; the present application can improve the efficiency of livestock meat slaughtering, cutting and packaging traceability based on internet.

This application provides a spatial intelligent non-planar reflection generation method based on surface normal guidance. Multi-layer visual representations are extracted from the original RGB image of a scene containing a non-planar reflective medium. The non-planar reflective regions are identified by combining the brightness distribution and spatial symmetry of the original RGB image. The nonlinear deformation features of the texture in the non-planar reflective regions are analyzed, and pixel-level 3D surface normal vectors and confidence distributions are predicted using the multi-layer visual representations to construct a surface normal map. A gaze vector is determined based on a camera imaging model, and geometric optics mapping operations are performed on the gaze vector, surface normal map, and confidence distribution to construct a reflection offset field. Intermediate semantic feature representations corresponding to the non-planar reflective regions are extracted, and a pre-distorted reflection feature representation is generated based on the reflection offset field and the intermediate semantic feature representation. The pre-distorted reflection feature representation, multi-layer visual representation, and initial reflective region mask are injected into the generation model for image reconstruction, generating a non-planar reflective image.

The application relates to a multi-protocol adaptive control method, system, device and medium of an LED dimming power supply, which comprises the following steps: receiving a dimming signal output by an external dimming device, and preprocessing the dimming signal to obtain a target input signal; extracting protocol identification features from the target input signal, and constructing a protocol feature vector; matching the protocol feature vector with a preset protocol template library to generate a candidate protocol set and corresponding initial confidence; dynamically correcting the initial confidence by combining historical recognition results, signal quality indexes and output response consistency to determine a target protocol type; calling corresponding protocol analysis rules and control parameter templates according to the target protocol type to generate target dimming control parameters; and adjusting LED drive output based on the target dimming control parameters. The application has the effect of improving the adaptive identification capability of the LED dimming power supply for various dimming protocols.

The application provides a contract text processing method and device, equipment, medium and program product, which can be applied to the technical field of big data and the technical field of financial technology. The method comprises the following steps: performing word segmentation on a to-be-processed contract text based on preset words about agreement information, to obtain a plurality of to-be-processed words; determining a first keyword from the plurality of to-be-processed words based on an initial weight corresponding to the to-be-processed word; determining a target weight corresponding to a neighboring to-be-processed word according to an importance coefficient corresponding to the first keyword and an initial weight of the neighboring to-be-processed word, the neighboring to-be-processed word being determined from a specified syntax segment containing the first keyword in the contract text, the specified syntax segment being a text segment between the first keyword and a specified syntax symbol; generating an abstract text based on the first keyword and the target weight corresponding to each of the neighboring to-be-processed words; and determining structured feedback information according to the abstract text and the first keyword.

This invention belongs to the interdisciplinary field of medical image analysis and deep learning, and discloses a method and apparatus for pathological slide image segmentation using multimodal supervised contrastive learning. The method generates biological prior feature maps through decoupling, extracts visual and semantic features by combining the master encoder and prior encoder, and achieves feature alignment using a cross-modal attention mechanism. Supervised contrastive learning is introduced to enhance intra-class compactness and inter-class separability. A multi-scale decoupled decoder is designed, with structural similarity loss and boundary-aware loss respectively supervising structural and detail branches. Finally, dynamic weighted fusion and pseudo-label calibration strategies are used to optimize segmentation performance, significantly improving the accuracy and robustness of pathological image segmentation.

This invention relates to a method, apparatus, medium, and device for generating woodblock New Year picture images, comprising: using a DMECS-YOLOv10 element recognition model to identify and extract the constituent elements of the woodblock New Year picture, obtaining its semantic features; using edge detection technology to extract the line drawing structure features of the woodblock New Year picture as style features; and fusing the semantic features and style features to generate a target woodblock New Year picture image. By introducing a woodblock New Year picture element recognition model to detect and locate key elements and obtain structured semantic information, and combining this with an improved line drawing extraction method to extract representative line drawing structure features from the New Year picture image, a semantic-style jointly constrained image generation model is constructed. This allows the generation process to be controlled by both content structure and artistic style, thereby effectively improving the thematic expression, compositional rationality, and stylistic consistency of the generated image, demonstrating good practical value and promising prospects for wider application.

This invention discloses a field name standard mapping method and system based on semantic matching, specifically relating to the field of data governance technology. The method involves obtaining a set of source fields to be mapped and a set of standard fields from a standard field library; standardizing field names and descriptions and generating textual representations of the fields; generating semantic vectors using a pre-trained language model and recalling a set of candidate mapping pairs; calculating string similarity, synonym expansion matching scores, data type consistency scores, and sample value pattern consistency scores for the candidate mapping pairs; generating a nearest neighbor confusion risk index based on semantic nearest neighbor density, entity category distribution deviation, synonym inflation, and contextual proof, and performing risk gating and correction, combined with difficult example discrimination scores; applying table-level consistency constraints within the same business table or entity domain to obtain the optimal table-level mapping scheme through joint consistency solving; generating confirmation confidence and outputting mapping results that are automatically confirmed or manually reviewed.

This application provides a dietary recommendation method and system based on multi-dimensional data analysis. The method includes: obtaining a set of modern nutritional attributes and a set of traditional Chinese medicine (TCM) theoretical attributes of the target food; obtaining a TCM constitution suitability score by matching the TCM theoretical attribute set with the user's TCM constitution type using a first rule; obtaining a disease nutritional suitability score by matching the modern nutritional attribute set with the user's list of diagnosed diseases using a second rule; determining whether there is a dietary recommendation conflict based on the TCM constitution suitability score and the disease nutritional suitability score; if a dietary recommendation conflict exists, assessing the severity of the disease and the deviation of the constitution for the user based on the list of diagnosed diseases and the TCM constitution type, respectively, to obtain corresponding disease severity indicators and constitution deviation indicators; and generating dietary recommendations for the target food based on the disease severity indicators and the constitution deviation indicators, thereby improving the accuracy and rationality of dietary recommendations.

The application discloses a bidirectional metering method and device applied to abnormal flow under pipe network disturbance, a medium and a product, relates to the technical field of ultrasonic water metering, and comprises the following steps: determining the period flow time difference and the period flow direction code corresponding to each period based on sampling data; taking the period flow direction code as an index, and constructing a period flow time difference sequence in chronological order; and determining the cumulative flow corresponding to the current flow sampling period sequence based on the period flow time difference sequence. The application can improve the bidirectional metering precision applied to abnormal flow under pipe network disturbance by constructing the period flow time difference sequence.

This application discloses a method for predicting the distribution of oil and gas layers in an oil well reservoir. The method includes: determining the reference clay content and reference resistivity of the oil and gas layers under each porosity range; determining the reference clay content and reference resistivity at each logging depth; determining the difference in clay content between the measured clay content and the reference clay content at each logging depth, and the difference in resistivity between the measured resistivity and the reference resistivity; determining the resistivity correction value for each depth to be predicted in the oil well reservoir using a resistivity correction model; correcting the measured resistivity at each depth to be predicted in the oil well reservoir using the resistivity correction value to obtain the standard resistivity at each depth to be predicted, and determining the distribution of oil and gas layers at each depth to be predicted in the oil well reservoir. The technical solution provided by this application can improve the accuracy of predicting the distribution of oil and gas layers based on resistivity.

This invention discloses a heterogeneous two-order wind power prediction method and system considering physical constraints, belonging to the field of wind power prediction and microgrid energy management technology. The method includes: acquiring and preprocessing raw data; constructing input features including wind speed, wind direction encoding, temperature, humidity, and historical power; dividing the data into training, validation, and test sets; training an XGBoost multi-step direct master prediction model using Bayesian optimization; training an LSTM model based on the prediction residuals and outputting residual prediction values; superimposing the master prediction values ​​and residual prediction values ​​to obtain a two-order prediction result; applying power boundary and ramp rate constraints, and outputting the final prediction result. This invention, by constructing a heterogeneous two-order prediction architecture of XGBoost and LSTM combined with physical constraints, improves prediction accuracy while adapting to small sample scenarios, thus enhancing the engineering usability of the prediction results.

The embodiment of the application relates to the technical field of seismic exploration, and discloses a brittle prediction method, device, equipment and medium for a rock reservoir, the prediction method comprising the following steps: based on well logging data of a target rock reservoir, a target layer section of the target rock reservoir is constructed according to rock components and rock physical characteristic parameters, so as to construct a rock physical model for representing the relationship between the volume modulus, shear modulus, rock density and the content of main brittle minerals of the rock; a model of a brittle indicator factor is constructed according to the rock physical model and the change of the content of the main brittle minerals, the brittle indicator factor being used for representing the relative brittle degree of the rock mass; and the brittle indicator factor is converted into actual brittleness for representing the actual brittle degree of the rock mass. The brittle prediction method disclosed by the application fully utilizes the rock physical characteristic analysis of the target rock reservoir to analyze the influence of the brittle minerals on the brittle prediction, and effectively improves the rationality and accuracy of the rock brittle prediction.

The application provides a power consumption load level determination method and device, electronic equipment and storage medium, relates to the technical field of big data, and the method comprises the following steps: acquiring power consumption data of a to-be-tested object; acquiring a first mean value and a first standard deviation of each power consumption in the power consumption data; determining each power consumption threshold value according to the first mean value, the first standard deviation and an initial setting coefficient corresponding to at least one power consumption threshold value; and determining a target power consumption load level of the to-be-tested object in a target period according to each power consumption threshold value and the power consumption in the target period. In summary, each power consumption threshold value is determined based on the statistical information of the power consumption data of the to-be-tested object in multiple periods, instead of being fixedly set, so that the accuracy and rationality of the target power consumption load level determination can be improved. Moreover, the power consumption of the to-be-tested object in at least one target period does not need to be forcibly divided into all power consumption load levels, so that the accuracy of the division result (i.e. the target power consumption load level) can be improved.

This invention discloses a brain-inspired optimization method for sentence structure-based self-attention mechanisms, comprising the following steps: acquiring a large-scale unlabeled corpus, preprocessing the corpus text, and identifying sentence boundaries; constructing structured attention constraints based on sentence boundaries: constructing intra-sentence attention constraints for ordinary characters to allow direct attention computation between characters within a sentence, constructing intra-sentence compression constraints for sentence boundary positions to form sentence-level compressed representations, and constructing cross-sentence constraints to allow both ordinary characters and boundary positions in the current sentence to access the boundary positions of the previous sentence; applying the structured attention constraints to the self-attention modules of each layer of a pre-trained language model for training or fine-tuning based on the corpus; and performing performance testing and brain-likeness analysis on the optimized model. This invention reduces the computational scale and memory consumption of the attention matrix while retaining long-range information integration capabilities, thus lowering computational complexity.