192results about How to "Exact match" patented technology

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention provides a multi-data source plug-in computing resource scheduling method and system supporting algorithm iteration, relates to the technical field of data sources, and comprises the steps of extracting multi-dimensional features by constructing a data source feature analysis engine, generating a feature fingerprint identifier, designing an intelligent matching mechanism based on the feature fingerprint identifier, and optimizing algorithm plug-in selection. The method has the beneficial effects that the utilization efficiency of computing resources is improved, resource allocation is adjusted in real time, stable system performance is ensured, and closed-loop optimization is formed.

The invention relates to the technical field of electronic component data processing, in particular to a database construction method and system based on electronic components. The method comprises the following steps: carrying out component information acquisition through an electronic component transaction platform to obtain an original component data set; performing component relation mapping construction according to the original component data set to obtain a component association graph; performing multi-dimensional attribute extraction on the component association map to obtain component attribute vectors; performing component similarity calculation and clustering analysis according to the component attribute vector to obtain a component cluster; and extracting pin information according to the component cluster to obtain a cluster pin data set. According to the method, multi-dimensional condition screening, sorting and result explanation are realized, an accurate, reliable and easily understood component replacement recommendation scheme is provided for a user, the user is helped to quickly find a proper component, and the electronic design efficiency is improved.

The invention provides a network data asset security identification method and system based on entity alignment, and relates to the technical field of network security, and the method comprises the steps: obtaining network data assets, historical asset states of the network data assets and corresponding state marks; establishing an association relationship of network data assets; generating a first embedded representation of the concept entity, and generating a second embedded representation of the instance entity; integrating the first embedded representation and the second embedded representation to obtain a target entity; extracting entity features and entity tags of the target entities; constructing a random forest model; acquiring a real-time entity feature, namely a real-time asset state, about the to-be-identified target entity in the network data assets; inputting the real-time asset state into the random forest model, and outputting an identification result of the real-time asset state; and when the identification result is an abnormal state, outputting that the to-be-identified target entity is abnormal, otherwise, outputting that the to-be-identified target entity is normal. Cross-source rapid common defense can be completed, and the data security is improved.

The invention discloses a large model semantic coding BIM data and engineering entity matching system, which comprises a knowledge graph construction module used for establishing a knowledge graph according to building project historical data; the BIM data and engineering entity coding module is used for coding the current BIM data or the current engineering entity into a vector by using a Chinese pre-training language model; the BIM data and engineering entity similar semantic retrieval module is used for retrieving a plurality of similar vectors of the current BIM data vector or the current engineering entity vector in the knowledge graph by using a retrieval enhancement generation model; and the BIM data and engineering entity matching module is used for matching the current BIM data vector or the current engineering entity vector with the corresponding similar vector by using cosine similarity. The invention further discloses a BIM data and engineering entity matching method for large model semantic coding. Compared with manual operation, the technical scheme of the invention has the advantages of high accuracy, high efficiency and high flexibility.

The utility model provides a wafer placement detection system, comprising a wafer box which comprises a containing cavity with an opening, and the containing cavity is provided with a plurality of clamping grooves used for containing wafers at intervals; and the photoelectric sensor is positioned on one side of the arrangement direction of the plurality of clamping grooves, and the photoelectric sensor is positioned at a position corresponding to the notch of the wafer. According to the utility model, the photoelectric sensor can detect the wafers with wrong placement directions in the wafer box, thereby ensuring that the gaps of the wafers can be correctly matched with the blocking PIN on the machine table so as to load the wafers to the specified positions of the machine table.

The invention relates to the technical field of natural language processing, in particular to a cross-domain sentiment analysis method fusing comparative learning and a domain alignment strategy, which comprises the following steps: inputting source domain and target domain texts into a model encoder to obtain source domain and target domain text features, and outputting each text feature through a model decoder to correspondingly generate a tag; constructing contrast loss, domain adversarial network loss and regularization item loss based on contrast learning, the domain adversarial network and a KL divergence adjustment mechanism; a pseudo label prediction model is obtained by minimizing the first loss function training model; inputting the source domain label and the target domain label into a pseudo-label prediction model encoder to obtain source domain label characteristics and target domain label characteristics, and outputting enhanced texts corresponding to the label characteristics through a pseudo-label prediction model decoder; constructing node matching and structure matching loss according to a graph matching principle; and training the pseudo label prediction model by minimizing the second loss function to obtain an enhanced text generation model. According to the invention, the cross-domain sentiment analysis effect is improved.

The invention discloses a form rendering method and device, computer equipment and a storage medium. The method comprises the steps that process data needing to be displayed are obtained, and the process data comprise instance data; judging whether the form type of the process data is a URL (Uniform Resource Locator); if yes, a version number and a process definition identifier are extracted from the process data; determining a front-end development component of a corresponding version, loading the front-end development component through the URL, and transmitting instance data to component rendering; if not, extracting a version number, a process definition identifier and form data from the process data; analyzing the form data to obtain recognizable form data; obtaining a form rendering component of a corresponding version; and inputting the recognizable form data and instance data into a rendering component for rendering. By implementing the method provided by the invention, the technical problems that the existing rendering engine is different in compatibility, difficult in dynamic adjustment and high in operation complexity, and the user experience is affected due to the fact that updating cannot be carried out in time when the business process is changed can be solved.

The invention relates to the technical field of AI large models, in particular to a large model resume screening system and method for the human industry, and the system consists of a working post analysis module, a candidate resume analysis module, a matching degree analysis module and a personal information module. The working post analysis module is used for deeply analyzing and extracting key requirements of working posts; the candidate resume analysis module is used for comprehensively analyzing the uploaded candidate resumes and extracting key information; the matching degree analysis module is used for carrying out accurate matching degree analysis in combination with working post requirements and candidate information and giving a comprehensive ranking; the personal information module is used for the user to manage personal information and account setting; the large model resume screening system and method for the human industry have the beneficial effects that efficient screening and processing of a large number of resumes are achieved through an automation technology, so that the working pressure of a human resource department is remarkably reduced, and the screening efficiency is greatly improved.

The embodiment of the invention discloses a data processing method and device, equipment and a computer readable storage medium. The method comprises the following steps: performing semantic feature extraction on a plurality of data points contained in point cloud data of specified equipment to obtain semantic tags corresponding to the plurality of data points respectively; performing voxel division on the point cloud data to obtain a plurality of first voxels, and selecting a target data point from the plurality of data points contained in each first voxel based on semantic tags corresponding to the plurality of data points; based on the semantic tag of each target data point, determining an associated feature point matched with each target data point from a preset local map point cloud; and calculating the current pose information of the specified equipment based on the plurality of associated feature points. Through the method, the accuracy of pose estimation can be improved.

The invention discloses a matching engine determination method and device, equipment, a medium and a program product, and relates to the field of artificial intelligence. Obtaining first matching request data; inputting the first matching request data into a matching engine; performing n times of iterative matching simulation on the first matching request data through a matching engine to obtain matching results respectively corresponding to the n times of iterative matching simulation; wherein the matching parameter used by the ith matching simulation is adjusted through the matching result obtained by the ith matching simulation, and the matching parameter used by the (i + 1) th matching simulation is obtained; and on the basis of matching results corresponding to the n times of iterative matching simulation, determining that the target matching parameter is a matching parameter used by the matching engine in account matching with the same flow level as the plurality of first accounts. The matching engine used in account matching suitable for different flow levels can be determined, and the matching effect of the matching parameters is improved.

The invention discloses a building scheme generation system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, the system comprises a preprocessing module, a picture classification module, an input analysis module and a scheme generation module; the preprocessing module is used for collecting a building scheme and a building picture, and determining building scheme elements and elements and element values of a manual annotation picture; the picture classification module is used for performing preliminary classification and re-classification on the pictures according to the elements and clustering the pictures of the same classification to determine representative pictures; the input analysis module is used for analyzing user input; and the scheme generation module is used for generating a building scheme according to user input and feedback and providing a selection and judgment mechanism to optimize scheme generation. The invention also provides a method for realizing the system. According to the method, the conditions that text analysis and picture processing are difficult to effectively fuse and picture and data classification standards are relatively single in the prior art can be effectively improved.

The invention discloses an AI substitute inspection method and system based on multi-modal perception, and relates to the technical field of intelligent detection. According to the method, images, audios, environmental parameters and equipment state data of an inspection area are synchronously collected through a multi-modal sensor array, and after space-time alignment preprocessing, multi-modal features are extracted and input into a pre-trained fusion model to generate unified feature representation. The fusion model adopts a Transform architecture to realize cross-modal feature interaction, an anomaly detection algorithm is used to identify and classify anomalies, a confidence coefficient is calculated in combination with an evidence theory, and finally an inspection report containing anomaly positions, types and processing suggestions is generated. According to the invention, the information limitation of single-mode inspection is solved, the detection accuracy and robustness in a complex environment are improved, unmanned inspection in a high-risk scene is realized, the labor cost is reduced, the safety is guaranteed, and the method is suitable for automatic inspection in the fields of industrial equipment, public facilities and the like.

The present invention relates to the field of drone control technology, and specifically to a drone swarm collaborative control system and method in a complex environment based on image recognition. The system preprocesses collected real-time environment image data of the drone swarm to generate real-time environment image feature data of the drone swarm, builds real-time environment three-dimensional model data of the drone swarm based on the real-time environment image feature data, and matches the data with the collected preset flight route data of the drone swarm. According to the matching result, preset flight route adjustment data of the drone swarm is generated. If the preset flight route adjustment data of the drone swarm needs to be adjusted, the flight route of the drone swarm is planned by using a constructed drone swarm flight route planning model to generate drone swarm flight route planning data. Finally, drone swarm collaborative control data is built, and drone swarm flight route adjustment operations are performed to achieve collaborative control of the drone swarm and scientific adjustment of the flight route.

The invention provides a longitudinal wave and converted wave matching method and system based on inversion, and belongs to the technical field of oil exploration, and the method comprises the steps: obtaining logging information, a longitudinal wave superposition data body, a longitudinal wave pre-stack gather data body and a converted wave superposition data body of a multi-component earthquake; performing well-seismic calibration on the longitudinal wave superposition data body and the converted wave superposition data body, and determining the time depth of the target stratum in longitudinal waves and converted waves; correcting the converted wave from the converted wave time domain to the longitudinal wave time domain to obtain a converted wave data body; according to the logging information and the longitudinal wave pre-stack gather data body, carrying out pre-stack inversion to obtain transverse wave impedance; according to the logging information and the converted wave data body, carrying out post-stack inversion to obtain shear wave impedance; and determining a time difference according to the shear wave impedance, and matching the converted wave data volume according to the time difference. The problem that longitudinal waves and converted waves are difficult to match due to large energy, frequency and phase differences is solved, the matching precision of the longitudinal waves and the converted waves is improved, and meanwhile accurate matching between marker layers can be achieved.

The invention discloses a satellite-borne radar measurement data timestamp synchronous timing method and system. The method comprises the steps that a satellite time timer is designed through an FPGA logic circuit for timing; according to the second pulse signal, second synchronous timing is carried out on the star time timer through an FPGA logic circuit; according to an irregular satellite time broadcast signal and the second pulse signal, world coordinated time correction is carried out on the satellite time timer through an FPGA logic circuit; and performing timestamp synchronous timing on the spaceborne radar measurement data. Through the design of the FPGA logic circuit, second synchronous time calibration and world coordinated time calibration are carried out on the satellite time timer, high-precision synchronous time calibration of spaceborne radar time is achieved, the high-precision synchronization requirement of spaceborne radar of a GNC control system is met, the time stamp synchronous time calibration design is further added to output measurement data of the spaceborne radar, and the time calibration precision of the spaceborne radar is improved. And the measurement precision of spaceborne radar measurement data is effectively improved.

The invention relates to a sea area management and control early warning evidence obtaining method based on video intelligent analysis, and the method comprises the steps: collecting equipment parameters: collecting internal and external parameters of equipment and environment parameters; equipment screening control is carried out, controllable and controllable equipment with a good detection effect is selected through equipment state analysis and target detection effectiveness analysis, and follow-up monitoring of a target area is realized through pan-tilt control; performing video intelligent analysis, determining a follow-up concerned target through mapping matching of a video intelligent analysis model and different coordinate system positioning information, and performing accurate linkage and video snapshot by fine tuning equipment; according to early warning and evidence obtaining association, structured attribute analysis is performed on a target and an area detected in a video capturing process, and an evidence obtaining result is added to early warning information with an association relationship, so that repeated evidence obtaining is avoided. According to the invention, the accuracy and efficiency of early warning evidence obtaining can be effectively improved, the utilization efficiency of data and resources is improved, and powerful technical support is provided for sea area management and control.

The invention relates to the technical field of literature retrieval. The invention discloses a literature recommendation method, device and equipment based on a double-tower model and a medium, and the method comprises the steps: obtaining behavior data of a target user; according to the behavior data of the target user, extracting a behavior preference feature vector of the target user, and calculating a deep representation vector of the target user based on a double-tower model; obtaining a deep representation vector of the candidate literature based on a preset vector database, and calculating the similarity between the deep representation vector of the target user and the deep representation vector of the candidate literature; and generating a literature recommendation list of the target user according to the similarity. According to the method, the semantic features and the interest preference features of the user are obtained by deeply fusing the historical behavior data of the user, a literal matching category is exceeded, user requirements can be more accurately matched, and personalized recommendation is realized. And meanwhile, by utilizing the parallel processing capability of the double-tower model, the response speed of the recommendation system can be increased, and the recommendation efficiency is improved.

The invention discloses a pig feed feeding device for gene breeding, and relates to the technical field of pig breeding, the pig feed feeding device comprises a mounting box and a feed conveying module, the mounting box is internally provided with a stirring module and a mixing and discharging module, different feeds in different bins are quantitatively conveyed into the stirring module according to the proportion, and the stirring module and the mixing and discharging module are arranged in the mounting box; the stirring module can uniformly stir different feeds and then quantitatively convey the feeds into the mixing and discharging module, and after the mixing and discharging module adds liquid additives or fixed mineral additives into the feeds, the mixing box body is shaken, so that the feeds are uniformly mixed with the liquid additives and the fixed mineral additives to obtain accurately matched pig feeds. And a discharging switch is turned on, the accurately matched pig feed is output to the feed conveying module, and the feed conveying module conveys the feed into the pig feeding trough, so that accurate matching and efficient feeding of the feed are realized, the feeding efficiency is greatly improved, the time and energy of manual operation are reduced, and construction of an intelligent pig farm is facilitated.

The invention relates to a business resource retrieval method and device based on an AI large model, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a business file, and determining business file content in the business file; the business file content comprises at least two content elements with different content formats; matching the business file content with a preset business keyword according to the matching priority of the content format corresponding to each content element; key information matched with the business keyword in the business file content is extracted, and the key information is stored in a business resource question and answer database; in response to an input business resource search text, outputting a business resource search result used for responding to the business resource search text based on business file content corresponding to the target key information; the target key information is key information matched with the business resource search text in the business resource question and answer database. By adopting the method, the retrieval result accuracy of the business resources can be improved.

The invention provides a voice recognition model training method, an intelligent customer service voice processing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining voice sample data, generating a label for each piece of voice sample data, training a pre-training model through the voice sample data, obtaining a trained pre-training model, and carrying out dialect adaptability training on the pre-training model by using the voice sample data with the dialect label to obtain a dialect understanding model; and carrying out model fusion on the pre-training model and the dialect understanding model to obtain a language understanding model. According to the method, the label is generated for the voice sample data, the pre-training model is trained by using the dialects, so that the dialect understanding model can accurately identify the dialects, the model fused with the pre-training model can accurately identify mandarin and dialects at the same time, answers of the user during question making can be more accurately matched, the communication efficiency is improved, and the user experience is improved. And better service experience is brought to the user.

The utility model discloses a pre-twisted phase-to-phase spacer, which is used for connecting four leads arranged in parallel. The device comprises a first pre-twisted wire clamp, a first hanging plate, a second pre-twisted wire clamp, a universal joint, a turnbuckle with adjustable length, a spacer composite insulator, a second pre-twisted wire clamp, a second hanging plate and a first pre-twisted wire clamp which are sequentially connected from front to back, the front end of a first rotating part of the universal joint is rotationally connected with a second pre-twisted wire clamp, and the rotating axis is perpendicular to the ground; the rear end of the first rotating part is rotationally connected with the front end of a transmission part, and the rotating axis is parallel to a wire; the rear end of the transmission part is rotationally connected with the front end of the second rotating part, and the rotating axis is perpendicular to the ground. The rear end of the second rotating part is rotationally connected with the front end of the turnbuckle, and the rotating axis is perpendicular to the ground. The pre-twisted phase-to-phase spacer can rotate in multiple directions when windage yaw occurs.

This application discloses an image-text matching method, device, and storage medium. The image-text matching method includes: extracting global visual features using the visual coding features of the target image, and extracting global text features using the text coding features of the target text; using the text coding features, generating importance parameters corresponding to each visual feature channel in the global visual features; removing features corresponding to visual feature channels whose importance parameters do not meet the requirements from the global visual features to obtain enhanced visual features; and performing feature matching on the enhanced visual features and the global text features to obtain a matching result for the target image and the target text. This method can improve the accuracy of image-text matching.

Embodiments of the present application provide a vulnerability scanning strategy matching model training method, device and equipment, and relate to the technical field of network security. The method comprises: obtaining vulnerability scanning records of network devices uploaded by a vulnerability scanning device, including: attribute information of the network devices, vulnerability scanning strategy parameters adopted by the vulnerability scanning device for scanning the network devices, and corresponding vulnerability scanning results; determining vulnerability scanning strategy target parameters corresponding to the network devices according to the vulnerability scanning strategy parameters and the corresponding vulnerability scanning results; generating device attribute samples according to the attribute information, and generating corresponding labels according to the corresponding vulnerability scanning strategy target parameters; generating a training set according to the samples and the labels; training a preset vulnerability scanning strategy matching model using the training set to obtain a model with strong matching capability, and then quickly matching vulnerability scanning strategy parameters corresponding to a network device to be scanned, i.e. a vulnerability scanning strategy, based on the model.

The invention discloses a data analysis and display system based on a large model, and the system comprises a data collection module which is used for carrying out the matching with a business database according to a current business stage, obtaining a matching result, starting a data burying point according to the matching result, and carrying out the data collection, and obtaining initial data; the data processing module is used for deploying a plurality of edge computing nodes on an edge server and performing multi-thread preprocessing on the initial data by utilizing the edge computing nodes; the data analysis module is used for transmitting the preprocessed initial data into an analysis model of the current service stage to obtain an analysis result; and the result display module is used for carrying out classified statistics on the preprocessed initial data and the analysis result to obtain a plurality of data reports and displaying the data reports in a monitoring center. The invention relates to the technical field of e-commerce data analysis, and solves the technical problems of low data processing efficiency and insufficient accuracy and breadth of data analysis in an existing e-commerce data analysis system.

The application discloses a visual positioning method based on memory self-correction. The existing visual positioning method uses fixed image and text representation to capture cross-modal semantic consistency, which limits the flexibility of adjusting image representation according to different text information. In order to cope with this limitation, the application proposes a new memory self-correction network, which dynamically refines the image representation according to the query, thereby improving the semantic consistency between the text and the image to realize visual positioning. A semantic related filtering module (SRFM) and an adaptive memory fusion module (AMFM) are constructed to explicitly model the relationship between the image and the text. SRFM focuses on filtering image information irrelevant to the query, while AMFM adaptively fuses text-related representation with initial image features to enhance the understanding ability of the MSCN model. Comprehensive experiments on three datasets verify the superiority of the proposed method compared with existing methods.

This specification provides a method, device, medium, and program product for training a generative model and retrieving goods. The method includes: acquiring first sample data including first sample goods information; generating multiple first sample query messages from an initial generative model based on the first sample goods information; determining a first positive sample and a first negative sample from the multiple first sample query messages; wherein the correlation between the first positive sample and the first sample goods information is higher than the correlation between the first negative sample and the first sample goods information, and the number of historical queries corresponding to the first positive sample is greater than the number of historical queries corresponding to the first negative sample; determining a first probability that the initial generative model outputs the first positive sample based on the first sample goods information and a second probability that the initial generative model outputs the first negative sample based on the first sample goods information, and training the initial generative model with the goal of increasing the first probability and decreasing the second probability to obtain a target generative model.

The application discloses an article recommendation method and related device, and relates to the field of article recommendation. According to the article ID contained in the article recommendation request, a positive query result is obtained. If the positive query meets the first missing level, and the incremental benefit evaluated based on the article recommendation scene data is not less than the first benefit threshold, a semantic vector is generated according to the article key field to recall a first group of candidate articles similar to the current article from a vector library, a second group of candidate articles corresponding to the current article is recalled from other multiple different databases, multi-dimensional feature fusion evaluation and sorting are performed on each candidate article, and the top N articles are selected as recommended articles. The application reduces invalid filling of low-value recommendation requests through information missing level and incremental benefit evaluation. When the positive feature is missing, candidate articles are recalled from the vector library and multiple different databases outside the vector library, multi-dimensional feature fusion evaluation and sorting are performed on each candidate article, and article recommendation is realized.

The invention relates to a full-automatic performance detection system and method compatible with multi-model lightning arresters, and the system comprises a multi-degree-of-freedom adaptive clamp module which is used for adapting to different models of lightning arresters, and achieving the automatic clamping and positioning of the lightning arresters; the performance detection module comprises an insulation detection sub-module and a withstand voltage detection sub-module and is used for performing performance detection on the lightning arrester; the data acquisition module is used for acquiring detection data in the detection process and transmitting the detection data to the data processing module; the central control module is used for generating a control instruction and controlling cooperative operation among the modules based on the control instruction; and the data processing module analyzes the lightning arrester detection process based on the detection data to obtain a detection result. According to the invention, the problems of poor compatibility and much manual intervention of a traditional detection method are solved, and accurate, efficient and safe detection of the performance of the lightning arrester is realized.

The invention provides a fan temperature-sensing frequency conversion control method and system for flexible production of an aluminum-silicon alloy electrolytic cell. The fan temperature-sensing frequency conversion control method comprises the steps that preset control parameters related to flexible production of the aluminum-silicon alloy electrolytic cell are obtained; temperature parameters during flexible production of the aluminum-silicon alloy electrolytic cell are collected; according to the collected temperature parameters, reference temperature parameters in the control parameters, reference frequency parameters in the control parameters and a preset control strategy, the target frequency of the draught fan is calculated; and on the basis of the target frequency, a frequency converter connected with a fan motor is controlled to operate, accurate and dynamic matching of the air volume of the fan and the production working condition is achieved, the energy consumption of the fan is reduced, and the control flexibility is improved.