585results about How to "Exact match" patented technology

The invention provides a plasticizing product recommendation method and system based on user demands, and relates to the technical field of plasticizing product recommendation, and the method comprises the steps: S1, constructing a plasticizing industry knowledge graph; s2, acquiring user historical data and current user requirements, including historical search data, historical browsing data, historical interaction data and historical transaction data; s3, preprocessing the historical data of the user, analyzing the preprocessed historical data of the user, and extracting historical demand features; s4, performing keyword extraction on the current user demand by utilizing the semantic understanding model, and generating an optimized query condition in combination with the chemical and plastic industry knowledge graph; s5, searching in a plasticizing product database by utilizing the optimized query condition to obtain a first list; and S6, carrying out personalized sorting on the first list by utilizing the chemical and plastic industry knowledge graph, generating a recommendation list from the first k lists, and presenting the recommendation list to the user. According to the invention, the relevance and accuracy of recommendation can be improved, so that the user experience is improved.

The invention relates to the technical field of task allocation, in particular to a task allocation method for flexible employment. According to the technical scheme, the method comprises the following steps that a database of related information of tasks and employees is constructed, wherein the database comprises detailed information of the tasks and comprehensive information of the employees; respectively constructing a task model and an employee portrait based on the information in the database; and matching the task with the employee through an intelligent matching algorithm, wherein the intelligent matching algorithm comprises matching algorithm selection and optimization, real-time matching and dynamic adjustment, and multi-objective optimization and tradeoff. According to the method, multiple matching algorithms are combined for optimization, weights are selected and adjusted according to tasks and employee characteristics, accurate matching is achieved, a task model and employee portrait multi-dimension consideration adaptability is achieved, adaptive changes are matched in real time, tasks and multiple aspects of employees are optimized and balanced in a multi-objective mode, the development of rights and interests of the employees is considered, and the matching quality, the working enthusiasm and the stability are improved; flexible employment resources are managed more effectively, and the task allocation effect is improved.

The invention provides a feedback pushing method and system based on background quotation data, and relates to the technical field of data processing, and the method comprises the steps: receiving a quotation request uploaded by a client, carrying out the semantic analysis, obtaining a commodity name keyword, carrying out the extension of the commodity name keyword, carrying out the standardization processing of a commodity attribute, and determining the feature of the commodity attribute; determining customer quotation preference features, and comprehensively obtaining multi-dimensional quotation request feature vectors; constructing a combined retrieval condition, extracting feature vectors of the target quotation data, performing weighting, performing screening through a multi-criterion decision model, generating a comprehensive matching degree matrix, and performing screening to obtain high-quality target quotation data; and sorting, determining optimal quotation data, pushing the optimal quotation data, receiving feedback information and feedback scores, if the feedback information is acceptance, generating corresponding order information and sending the order information to a supplier, and if the feedback information is rejection, pushing the optimal quotation data again.

The invention discloses a bad traffic monitoring method and system based on an LSTM and a clustering algorithm, belongs to the technical field of network security, and efficiently converges network traffic by using a BPF technology. The method comprises the following steps: accurately identifying fragmented traffic through an LSTM network, and capturing a complex dependency relationship by using a special memory unit structure of the LSTM network; performing session recombination by adopting an FCM clustering algorithm, restoring a complete network session, and quickly identifying malicious traffic through feature matching; and finally, timely treatment measures are taken for the confirmed malicious traffic. According to the method, rapid and accurate detection and identification of bad website traffic fragmentation behaviors are realized, and the technical problem that a traditional method is difficult to deal with is solved; through efficient caching and recombination mechanisms, the efficiency and accuracy of malicious traffic processing are improved; intelligent disposal measures are adopted, and it is ensured that malicious traffic is effectively restrained in time; the overall protection capability of network security is improved, and enterprise network resources and user data security are protected.

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

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 credential platform data migration verification method and system, and relates to the technical field of computers.The method comprises the steps that all to-be-migrated source data in a credential platform database are read, basic information of the source data is obtained, and a data label is set for each piece of data; reading fields and contents in the migration data, and constructing a data similarity verification model; selecting a migration path and a target database according to the migration demand, and dynamically evaluating the similarity between the source data and the target data through a data similarity verification model; verifying the migrated source data based on the target database, and performing incremental verification on data of different fields in the table; the data table of the to-be-migrated source data is verified in real time among different migration nodes, data changes on each node are verified step by step through an increment verification mechanism, if data missing or verification inconsistency occurs in the verification process, an alarm mechanism is triggered, and the problem of data missing or inconsistency can be automatically recognized and corrected.

The invention discloses a talent pushing system and method based on multi-channel data fusion, and relates to the technical field of pushing systems.A big data analysis module extracts key features and generates a high-quality matching model by processing and analyzing mass data from different sources; therefore, the recommendation accuracy and the recruitment efficiency of the enterprise are remarkably improved. Based on the analysis results, the intelligent recommendation module can flexibly cope with personalized requirements of different enterprises and accurately match candidates and posts, so that the recommendation success rate is improved, and meanwhile, the time and energy of the enterprises for screening improper candidates are reduced. Besides, through a real-time monitoring and feedback mechanism, the system can continuously optimize a recommendation algorithm and sensitively respond to market changes, the recommendation accuracy and effectiveness are further improved, and enterprises are helped to take the earlier opportunity in the talent market with intense competition.

The invention discloses a tunnel apparent disease detection method. The method comprises the following steps: collecting three-dimensional point cloud data in a tunnel through a moving vehicle carrying a three-dimensional laser scanner; calculating a depth value according to a Z value of the three-dimensional point cloud data, and mapping the depth value to a gray scale range of 0-255 to obtain a gray scale image; identifying a gray value abrupt change area in the gray image through an edge detection algorithm to obtain an abrupt change crack area on the surface of the tunnel lining; performing gray segmentation on the gray value mutation region to obtain a water leakage region, and performing connected domain analysis on the water leakage region to obtain the area of the water leakage region; identifying a gray value mutation region according to a region growing algorithm to obtain a lining surface layer layering region; according to a template matching method, a drainage ditch area in the gray level image is identified; and marking tunnel cracks, water leakage, lining surface layer peeling and drainage ditch damage areas. According to the invention, the three-dimensional laser scanning and image processing technology is adopted to detect the apparent diseases of the tunnel, so that the disease maintenance efficiency is improved.

The invention discloses a big language model tool matching method and system based on a knowledge graph, belongs to the technical field of artificial intelligence, and solves the problem that an API (Application Program Interface) tool is difficult to efficiently manage and accurately select in a real-time information processing process of an existing big language model. According to the method, a multi-source data fusion technology is introduced to collect and sort information of external API tools of different data sources, and a dynamic relation weight adjustment mechanism is utilized to dynamically adjust the weight of the relation between different API nodes according to the actual use condition of the API tools and user feedback; representing the characteristics of each API node through a graph embedding technology based on an intelligent matching algorithm of deep learning, and calculating the matching degree of each candidate API and a request by using a sequence processing model; according to the method, the knowledge graph and the intelligent matching algorithm are combined, an external API tool used by a large language model can be dynamically managed and optimized, and the information processing accuracy and the system response speed are improved.

The invention discloses a metasurface reverse design method of a generative adversarial network based on anchor point network control. The method comprises the following steps: collecting metasurface design parameters and spectral response data, preprocessing, and encoding the data into a format which can be processed by a deep learning model; and analyzing the training data by using a K-means clustering algorithm to generate a structured control vector. And constructing an AcGAN framework, and integrating the spectrum similarity measurement SOC into a loss function of a generator and a discriminator to enhance the spectrum matching precision. Through an adversarial training method, a generator is trained to generate a design conforming to target spectral characteristics, and meanwhile, a discriminator and an anchor network AncorNet are optimized to quickly predict and evaluate spectral response. Candidate designs are generated using the trained generator in combination with control vectors and random noise. And screening the candidate design to select the optimal design. According to the method, the spectrum regulation and control precision and the design efficiency of the metasurface design are effectively improved, and the challenge faced by a traditional method when a complex spectrum requirement is processed is solved.

The invention discloses a sound wave positioning device and method for a coal mine auxiliary transportation digital twin system. According to the device, two loudspeakers are installed on the side wall of a roadway of an auxiliary transportation equipment operation area at intervals; the omnidirectional microphone and the edge computing node are mounted on the auxiliary transportation equipment; the method comprises installing the sound wave positioning device; constructing an asymmetric sound field; off-line RSS acquisition is carried out; constructing a multi-dimensional RSS fingerprint vector according to the received interference intensity, and constructing a gradient fingerprint image based on the multi-dimensional RSS fingerprint vector; establishing a fingerprint database; acquiring an RSS vector Rtest of a current to-be-positioned point, converting the RSS vector Rtest into a corresponding to-be-matched gradient fingerprint image gtest, and performing fingerprint matching by using a fingerprint image matching algorithm based on a discrete Frechet distance to obtain position information; and digital twinning integration. According to the device and the method, the auxiliary transportation equipment can be quickly and accurately positioned in a complex coal mine environment, and the safety and the efficiency of mine operation can be effectively improved through real-time feedback and visual monitoring.

The invention discloses a visual tracking and real-time guiding robot and conveying belt following method, and belongs to the technical field of book packaging, the visual tracking and real-time guiding robot and conveying belt following method comprises a conveying belt device used for conveying articles and having adjustable running speed and direction control functions; the robot main body is arranged on one side of the conveying belt device; the fixed vision device is connected with the robot main body; through cooperative work of the robot vision module and the independent fixed vision device on the robot body, all-directional vision coverage of the conveying belt and the surrounding environment is achieved, and the robot vision module focuses on local detail information of the robot and objects on the conveying belt; the relative position and posture change of the robot and an object can be captured in a close-range and high-precision mode in the operation process of the robot, and the fixed vision device continuously monitors the overall condition of the conveying belt from the overall perspective.

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 provides a mouth shape generation method and device for voice driving, and relates to the technical field of natural language processing. The method comprises the following steps: based on an ffmpeg tool, carrying out image processing according to original video data to obtain spliced frame image data and facial feature points; according to the original audio data, performing feature extraction through a deep audio feature extractor to obtain audio features; performing feature fusion through an audio-video sequence feature fusion device to obtain fusion features; performing video generation through a lip action generator according to the facial feature points and the fusion features to obtain synthesized video data; optimizing a lip action generator according to the original video data and the synthesized video data; and performing video generation based on the depth audio feature extractor, the audio-video sequence feature fusion device and the optimized lip action generator to obtain target synthesized video data. The invention relates to a mouth shape generation method aiming at voice driving, which is high in video resolution and sufficient in facial texture detail reservation.

The invention discloses a person and post matching method and device based on a heterogeneous graph, equipment and a medium. Comprising the steps of obtaining position information, resume information and historical matching behavior data between the position information and the resume information; taking the position information as a position node, taking the resume information as a resume node, and establishing a first edge relationship between the position node and the resume node based on historical matching behavior data; based on the similarity of each piece of position information, the similarity of each piece of resume information and historical matching behavior data, establishing a second edge relationship between position nodes, a third edge relationship between resume nodes and a fourth edge relationship between the position nodes and the resume nodes; constructing a global heterogeneous graph based on each position node, each resume node and the edge relationship thereof; training a GLAN model based on the global heterogeneous graph; and converting the position information to be matched into heterogeneous graph features based on the GLAN model, and screening matched target resume information for the position information to be matched based on the heterogeneous graph features.

The invention discloses a high-precision registration method for multi-view point clouds of welding workpieces, which is characterized by comprising the following steps of: firstly, carrying out spot welding on welding grooves of two workpieces to obtain a to-be-welded workpiece; a structured light camera is used for collecting multiple frames of original point clouds of a to-be-welded workpiece at different visual angles, background point clouds are removed, and multiple frames of workpiece point clouds at different visual angles are obtained; then extracting the point cloud of the upper surface of the workpiece containing the welding groove, and performing coarse registration on the point cloud of the upper surface of each frame of the workpiece; the mass weight of each point in the point cloud of the upper surface of the workpiece is calculated, then the point clouds of adjacent frames are subjected to precise registration through a weighted ICP algorithm to optimize the poses of the adjacent frames, precise splicing of the point clouds of the upper surface of the workpiece at multiple frames of different view angles is achieved, and the complete point cloud of the upper surface of the workpiece containing the welding groove is obtained; the method has the advantages that the influence of point cloud distortion on point cloud precise registration is well reduced, and the precision of point cloud registration is improved, so that the precision of subsequent three-dimensional model reconstruction and the precision of automatic welding are ensured.

The invention discloses a contract and law consistency review method based on fine-grained semantic multi-task learning. The contract and law consistency review method can be used for legal contract review. According to the method, a legal provision matching task serves as a main task, a BERT model is used for learning coarse-grained representation of a legal text, deeper fine-grained semantics contained in the legal text are extracted by constructing a fine-grained legal semantic enhancement module, and cosine similarity is used for matching legal provisions with high relevancy with input contract terms. According to the method, a legal text classification task is used as an auxiliary task, and the learning ability of legal text features is improved by sharing rich representations learned by legal texts in different tasks. Experiments on a CLSAD data set prove the effectiveness of the method.

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 relates to a combined control method based on chilled water storage and phase change cold storage in a cold supply system, and the method comprises the steps: obtaining electricity price fluctuation information and weather information, and inputting the information into a prediction model for trend prediction when user demand information is received; equipment state information is obtained, and a corresponding federated cold storage strategy model is matched; inputting a trend feature set output by the prediction model and equipment state information into a federated cold storage strategy model to generate a cold storage strategy; solving a cold storage strategy generated by the federated cold storage strategy model to output an optimal cold storage strategy set; through the application of the combined control method and the federated cold storage strategy model, efficient combined control of chilled water storage and phase change cold storage equipment is achieved; by deploying the federated cold storage strategy model, the cold supply system can be quickly matched with the federated cold storage strategy model when facing a new cold storage demand, so that a highly personalized and precise cold storage strategy is generated, and the effectiveness and high efficiency of the strategy are ensured.

The invention belongs to the technical field of image stitching, and discloses a multi-camera image stitching method and system. The method comprises the following steps: collecting data of a plurality of real-time images shot by a multi-camera device, and carrying out image preprocessing; collecting real-time image edge information of each piece of preprocessed real-time image data, and extracting a plurality of real-time feature points; performing feature point matching on the plurality of real-time feature points by using a pre-trained feature point matching model; performing image registration on all the preprocessed real-time image data according to a plurality of feature point matching results; carrying out image fusion on the real-time overlapping region of the real-time image data after all the images are registered by using an improved multi-band fusion algorithm; and according to the real-time splicing parameters, carrying out image splicing on the real-time image data after all the images are fused to obtain real-time holographic image data. The problems of poor visual effect, low accuracy, low processing speed, poor splicing quality and poor fusion effect in the prior art are solved.

The invention provides an auditor and task intelligent matching method and system and electronic equipment, and the method comprises the steps: obtaining the type of a task to be executed by an auditor, obtaining the initial capability information of the auditor, and carrying out the initial static capability classification of the auditor according to the initial capability information of the auditor; after the auditor performs task trial, performing dynamic ability grading on the auditor; and according to the results of the initial static capability grading and the dynamic capability grading, forming a multi-dimensional capability label of the auditor, and matching the auditor with the task type, so that the auditor can be matched with the task type more accurately, the task execution quality and efficiency are improved, and the task execution efficiency is improved. And outputting a compensation point matched with the type of the corresponding task of the auditor according to the matching degree, training the auditor according to the compensation point, and then performing dynamic capability grading and re-matching of the auditor and the type of the task again, so that the evaluation process is repeatedly iterated, and the dynamic capability spirally rises.

The invention relates to the technical field of employment management, in particular to a flexible employment management system based on a block chain and big data and a skill evaluation method. According to the invention, through autonomic skill label selection of the user and intelligent skill index generation, recommendation and matching are more accurately carried out on service supply and demand parties; according to the technical scheme, skill authentication information of a user is linked through the block chain technology, the skill authentication information comprises skill certificates and training experiences, the key problems of information asymmetry, non-transparent evaluation, low matching efficiency, insufficient right and interest guarantee and the like in a traditional system are effectively solved through combination of the block chain technology and the big data technology, and the user experience is improved. According to the flexible employment management system, a complete and coherent closed loop is formed from skill authentication to matching recommendation to right and interest guarantee and occupational development, the efficiency and fairness of a flexible employment market are greatly improved, and the sense of trust and the degree of participation of users are enhanced.

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 multi-target tracking method based on joint detection and feature embedding. The method comprises the following steps: acquiring different features of an input detection branch and an identity branch through a feature separation module; inputting the features of the identity branches to obtain finer feature expression through a multi-scale feature fusion module, and inputting the features of the detection branches to obtain a detection result of a t frame through a target detector; the data association module firstly matches a high-score detection frame with all existing tracks for the first time, and then matches unmatched tracks in the first stage with a low-score detection frame for the second time, so that a target in the low-score detection frame is correctly matched with the previous track and background interference is removed; and if the two times of matching are not successful, carrying out continuous hypothesis tracking, reserving target trajectory information and a feature x frame, and finally executing unified trajectory management. According to the method, the tracking precision and speed can still be kept under the conditions of camera shaking, local shielding and the like.

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 invention discloses a method and device for generating a dynamically switchable heat dissipation strategy based on an OpenBMC, and relates to the technical field of server intelligent heat dissipation regulation and control, and the method comprises the steps: firstly constructing a configuration library comprising optimal heat dissipation strategies corresponding to various devices and models and Sensor thresholds; the configuration library predefines a series of tested heat dissipation strategies and sensor thresholds according to factors such as hardware characteristics, power consumption and heat dissipation capability of equipment. And according to the equipment type, model and the like acquired by the equipment information acquisition module, searching corresponding configuration in the heat dissipation strategy and Sensor threshold configuration library. According to the method, corresponding thresholds and strategies are quickly and accurately matched by using technologies such as a hash table and database query, and the heat dissipation strategies are adjusted in real time according to parameters such as temperature provided by the sensor so as to meet different heat dissipation requirements generated by different devices and models, so that the technical problems of sensor threshold stiffness and non-agility in heat dissipation strategy switching in the prior art are solved.

The invention provides a network computing power energy sensing network, a resource measurement method, a resource measurement device and a program product. The method comprises the following steps: determining a current available resource corresponding to an infrastructure through a resource sensing unit; before the calculation task is executed, resources needed for executing the calculation task are measured through a measurement device based on the task type, the task scene and the task load corresponding to the calculation task, target resources are obtained, and resource configuration is carried out according to the target resources and resources corresponding to the infrastructure; in the execution process of the calculation task, generating predicted available resources corresponding to the infrastructure in the target period through a measurement device based on the current time feature and the task feature corresponding to the calculation task; performing resource configuration according to the predicted available resource, the current available resource and the target resource; the problem that a single resource measurement index is difficult to meet the requirements of task types and task scene complexity can be solved; and the requirements of task type and task scene complication can be comprehensively and accurately met.

The invention relates to the technical field of dry-type transformers, and discloses a dry-type transformer with a lead-out wire arrangement structure, which comprises a dry-type transformer main body, a control cabinet and a base, and is characterized in that the dry-type transformer main body is connected with the control cabinet through a plurality of wire groups; wire arranging mechanisms with the same number as the wire groups are arranged between the dry-type transformer main body and the control cabinet, and the wire arranging mechanisms are used for independently fixing a plurality of wires in the same wire group. According to the invention, the plurality of independent junction box assemblies are arranged on the wire mounting part, and can be used for separately fixing and arranging a plurality of wires of the same wire group, so that each wire is kept at a safe distance, and the problem of chain reaction of the wires can be avoided.

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.