37 results about "Match algorithms" patented technology

This invention discloses a substation secondary circuit design method based on equipment functional areas and template matching. The method includes assigning descriptions to secondary equipment based on voltage level or bay; constructing secondary circuit data templates; matching the data template library based on the connection relationships of local equipment functional areas within a bay; extracting functional area connection information through a typical template information flow table; and converting the functional area connection information into actual equipment terminal connections to complete the substation secondary circuit design. This invention mutually converts the functional areas of secondary equipment with the design of secondary circuits, constructing data templates for substation secondary circuits. By improving the VF2 graphical matching algorithm, it achieves digital storage of data templates and rapid matching of complete bay information using local information from data templates. After matching, the functional area connections of the data templates are reverse-converted into equipment terminal connections, realizing automatic secondary circuit design and improving the digital design level of secondary systems.

This invention discloses an improved DBSCAN algorithm and a many-to-many matching algorithm for 6G vehicle-to-everything (V2X) networks, belonging to the field of V2X technology. It designs an improved density-based spatial application noise clustering algorithm to cluster more dispersed vehicles, employs a many-to-many matching algorithm to pair vehicles with auxiliary MEC servers, and designs a multi-agent-based task offloading mechanism to reduce latency and improve resource utilization efficiency. The improved DBSCAN algorithm proposed in this invention overcomes the sensitivity of parameter selection, does not require particularly precise parameter settings, performs well on datasets with uneven density, overcomes the influence of vehicle density on clustering results, and the proposed many-to-many matching mechanism improves the utilization of remaining vehicle computing resources and greatly alleviates the pressure on edge servers, while ensuring that high-priority tasks are computed first.

The application provides a kind of addressing matrix analysis method for multi-dimensional identification system, by the instruction of terminal input is disassembled into different components, combined into addressing information;Structured data based on multi-dimensional identification attribute, namely addressing matrix, is constructed;Terminal sends addressing request message to access routing device;The addressing request message is forwarded to regional server;K-d tree index is constructed;Using the pre-constructed k-d tree index, the terminal node coordinate C closest to the query point P in Euclidean distance is found;Match appropriate terminal node coordinate;After locking the target terminal through coordinate mapping and similarity matching algorithm, extract the key identifier as the analysis result of query;The method can significantly improve the positioning accuracy and query efficiency of terminal node, can significantly reduce the delay of data transmission, and provide faster response time.

This invention relates to the fields of data processing and talent matching technology, and in particular to a two-way matching method for university-enterprise talent based on financial capability profiling. The method includes: constructing a corporate financial capability profiling indicator system, including indicators of corporate financial stability and job financial capacity; constructing a talent financial capability profiling indicator system, including indicators of financial knowledge reserves, financial practice skills, financial risk awareness, and financial digitalization capabilities; collecting and preprocessing data from both the corporate and talent sides; calculating a comprehensive evaluation value based on a combined weighting method using an improved analytic hierarchy process (AHP) and entropy weighting method; constructing a corporate job demand vector and a talent supply vector; solving for the optimal matching scheme based on a bipartite graph matching algorithm, with the objective function of maximizing two-way matching satisfaction; and outputting the matching results. By constructing a two-dimensional evaluation system of corporate and talent financial capabilities, and using an improved weighting method and matching algorithm, a precise two-way matching of university and enterprise talent is achieved, improving the scientific nature of the matching.

The invention discloses a to-do list collection and processing method and system based on Java, and belongs to the technical field of computer software, collection and processing of to-do lists are achieved through feature dictionary matching, and the method comprises the steps that multi-source data are collected, a to-do feature dictionary is constructed, and to-do information is recognized through a multi-dimensional matching algorithm; the rear end constructs a layered architecture based on the SpringBoot and the SpringMVC, and the SpringMVC is used for providing a standard RESTfulAPI (Application Program Interface) and supporting to-do query and state updating functions; the front end adopts Vue3 + ElementPlus to realize a response type Web interface, and a back-end interface is called through Axios to realize efficient collaboration of the front end and the back end. According to the method, automatic access of multi-source heterogeneous data and extraction of the information to be handled are realized, the accuracy of identification of the backlogs is improved, and automatic classification, priority ranking, reminding triggering and state updating of the backlogs are realized.

The application discloses a customer service interaction evaluation method and system based on multi-dimensional semantic understanding, and the method comprises the following steps: obtaining multi-round interaction data of a service customer, analyzing the behavior description representation of a service object through a behavior analysis layer; outputting corresponding score results of the service behavior of the multi-round interaction data through a multi-dimensional scoring layer based on behavior logic division, wherein the behavior description representation serves as the context constraint of the multi-dimensional scoring layer; detecting the scored multi-round interaction dialogue through a compliance judgment layer based on a multi-level matching algorithm to obtain corresponding violation results; and outputting the comprehensive evaluation result of the customer service through an evaluation template and a condition trigger according to the behavior description representation, the score result and the violation result. It can be seen that the application can realize the full-link intelligent evaluation of service interaction from the process, scoring, compliance and optimization, and is suitable for the unified management of artificial attendants and intelligent external calls.

The application discloses a kind of shipbuilding industry intelligent manufacturing operation system, belong to shipbuilding digital management technical field.System includes ten big modules such as basic data management, production plan and scheduling, material management, production process control, equipment management, quality management, data traceability and analysis, exception and safety management, cost and change management, system integration;Adopt microservice architecture, containerized deployment and encryption security system, built-in shipbuilding global collaborative optimization algorithm, intelligent scheduling algorithm, matching algorithm, equipment health degree prediction algorithm, quality traceability algorithm, exception hierarchical response algorithm, cost dynamic accounting algorithm and multi-dimensional data analysis algorithm, realize multi-objective optimization by mathematical formula modeling.The application solves the problems of weak shipbuilding plan coordination, disordered material management, difficult quality traceability, low resource utilization, incompatible system, etc., realizes transparent, refined and intelligent control of the whole production process, and significantly improves production efficiency.

This invention proposes an intelligent matching and allocation method and device for experts and projects. The method includes: constructing a multi-dimensional fusion matching model based on acquired expert and project information. This model calculates a comprehensive matching score between experts and corresponding projects by weighted fusion of sub-scores based on expert professional matching degree, experience fit, workload balance, and geographical distribution balance; selecting a matching algorithm based on the number of experts and projects to be allocated; using a first matching algorithm when the problem size is no greater than a preset threshold; and using a second matching algorithm when the problem size is greater than the preset threshold; and generating the optimal matching scheme between experts and projects based on the comprehensive matching score using the selected matching algorithm. Based on this method, this invention also proposes an intelligent matching and allocation device for experts and projects. This invention achieves more accurate quantitative matching by constructing a comprehensive evaluation model integrating four dimensions: professional expertise, experience, workload, and geographical distribution.

The application relates to a batch setting unreal engine blueprint asset material plug-in. The plug-in comprises a blueprint inter-material one-key copy module, a smart material name matching and replacing mechanism module in multiple modes, a same material setting module for all mesh bodies in a blueprint and a same material setting module for specified named components in the blueprint, the smart material name matching and replacing mechanism module is combined with a set of configurable multi-rule string matching algorithm and an unreal engine blueprint asset structure traversal system, the algorithm intelligently analyzes and compares existing material names and candidate material names according to a matching mode selected by a user, after successful matching, the system accurately and batch assigns corresponding material asset pointers to target slots, and triggers instant compilation and updating of the blueprint. The application allows developers to easily and batch modify material assets in a blueprint asset, thereby simplifying the production process of a system such as a film or a game.

The application discloses a kind of based on the standardization adaptation method of mood interaction of companion device, comprising the following steps: obtaining the multimodal data of companion device, and standardization processing is generated adaptation state parameter;Identify current mood state, determine corresponding role quota constraint;Identify current device response capability, determine the coupling constraint relationship between each device capability unit;Determine the proposal rule, acceptance rule and update rule of current round stable matching, form the basis of current round stable matching;Using Gale-Shapley stable matching algorithm executes multiple-to-one stable matching, obtains current round stable matching result;Around current round stable matching result, determine local broken stable area;For local broken stable area, again using Gale-Shapley stable matching algorithm executes local reconfiguration, generates target mood interaction adaptation result.The application improves the accuracy, continuity and coordination of mood interaction response.

The application provides a matching method, a number state detection method, a device and electronic equipment, and relates to the technical field of computer matching algorithms. The method comprises the following steps: obtaining a to-be-matched text and a preset pattern string set, the pattern string set comprising a plurality of pattern strings; determining a shortest character number and a longest character number from the number of characters of each pattern string, and determining a first stop position and a second stop position in the to-be-matched text, the interval character number of which is equal to the shortest character number; and finally performing bidirectional pattern matching on the to-be-matched text based on the pattern string set, the shortest character number and the longest character number to obtain a bidirectional matching result; the bidirectional matching result comprising a pattern string that is matched in the to-be-matched text. The application adopts a bidirectional matching mode, can significantly reduce the number of unnecessary character comparisons under the premise of ensuring high matching accuracy, and improves the overall matching efficiency.

The application discloses an injection molding workpiece template matching method, an electronic device and a storage medium, and realizes a template matching mechanism by establishing a J(ψ ij ) arbitration function. The method comprises four main steps: injection molding workpiece image data preprocessing; contour feature extraction of an image data set and establishment of a standard template; obtaining matching accuracy by using a contour matching algorithm based on Hu moments on the injection molding workpiece and determining a matching threshold and a statistical scaling value thereof; and finally, using a plastic part template matching mechanism based on the J(ψ ij ) arbitration function to match the standard template with the workpiece to be tested. The application replaces the detection based on the gray value in the traditional detection method, so that the template matching of the injection molding workpiece has stability to factors such as translation, rotation and scaling. The application realizes automatic detection of defects of the injection molding workpiece, and the detection speed, accuracy and robustness are obviously improved compared with the traditional method.

This invention provides a big data-based intelligent matching method for upstream and downstream enterprises in the chemical industry chain, belonging to the technical field of matching upstream and downstream enterprises in the chemical industry chain. The method includes collecting multi-dimensional feature data of the chemical industry chain; analyzing basic enterprise data using an industry chain attribute matching algorithm; analyzing the dynamic changes in supply and demand relationships with market cycles; constructing a quantitative model of supply and demand impact, analyzing the influence weight of dynamic supply and demand data on initial enterprise matching data; and building an intelligent matching model of the industry chain to evaluate the matching process of upstream and downstream enterprises in real time. By integrating multi-dimensional feature data of enterprises and utilizing industry chain attribute matching algorithms, dynamic supply and demand analysis methods, quantitative supply and demand impact models, and intelligent matching models of the industry chain, this invention achieves accurate matching and dynamic optimization of upstream and downstream enterprises in the chemical industry chain, solving problems such as reliance on manual experience in matching, untimely response to dynamic changes in supply and demand, and insufficient risk management capabilities in existing technologies.

A method, system, and computer-readable medium are disclosed for processing and comparing documents in varying formats, incorporating advanced data extraction, normalization, and comparison techniques. The method includes receiving documents containing structured and unstructured data, processing them with optical character recognition and layout analysis to identify structural elements, and extracting key data fields using natural language processing, including named entity recognition and contextual analysis. Extracted data is normalized through schema mapping and synonym resolution, ensuring consistency in terminology and structure. The system employs fuzzy matching algorithms to identify discrepancies between documents and provides an interactive user interface with graphical visualizations, such as heatmaps and comparison charts, for reviewing and resolving differences. Machine learning techniques refine the system over time by integrating user feedback to improve data extraction, synonym resolution, and comparison accuracy.

The application discloses a user cold start recommendation system and method based on similarity matching, constructs a knowledge graph database according to users, products and the interaction relationship between the users and the products, and carries out standardization processing. The processed data is extracted to score information and mapped to a user like-dislike type space, so that the like-dislike product type of each user is determined, and a similarity matching algorithm is designed to find the old user with the highest similarity to the new user. The old user product type score vector and the new user product type vector score are processed by an association function and used as the recommendation basis of the system, the reasonable expansion of the new user data is completed, and the cold start problem of the recommendation system is effectively alleviated. The application solves the user cold start problem caused by the introduction of a new user into an industrial recommendation system. The application can be used for the scene of effectively recommending the product types that meet the preferences of new users in the industrial recommendation system.

This invention discloses a token-based AI inference scheduling, measurement, settlement, and computing power trading method and system, belonging to the field of artificial intelligence computing power infrastructure technology. This invention uniformly encodes multimodal input data into token sequences to generate task quantification tags; the scheduling engine allocates computing power based on the node's single-second token processing capacity profile using a fourth-order matching algorithm; real-time high-precision measurement of input, output, and context tokens is achieved through measurement probes embedded in the computation graph, and pre-deduction and on-the-spot settlement mechanisms are used for cost control; after task completion, a settlement document is generated, hashed, digitally signed, and written to the consortium blockchain distributed ledger for notarization. This invention significantly improves cluster computing power utilization and low-latency performance, achieving accurate measurement and reliable transactions, and is applicable to core scenarios such as large-model commercial inference, heterogeneous computing power scheduling, and computing power trading.

This invention discloses a method for resource management and task scheduling of heterogeneous computing clusters for reconfigurable hardware accelerators, comprising: a management control node dividing time into equally spaced scheduling time slots; at each scheduling time slot, the management control node collecting request processing tasks arriving in the previous scheduling time slot and the currently idle computing resources of the heterogeneous computing cluster; the management control node establishing a three-sided matching game framework for request processing tasks, service functions, and heterogeneous computing nodes; the management control node defining the preference criteria of each party based on the optimization objective; the management control node running a three-sided stable matching algorithm for matching; the management control node offloading request processing tasks to the heterogeneous computing nodes where the matching service functions are located for processing based on the matching results; waiting for the next scheduling time slot to arrive, and repeating the above steps. This method can effectively reduce the total task processing latency while maintaining a high task completion rate and task satisfaction.

The present application relates to the technical field of resource scheduling, in particular to a software project resource optimization allocation system and method, the system comprises, in the present application, the task execution priority sequence is compared with personnel pool language item, framework item, module history, code branch occupation, work time slot, concurrent upper limit is executed item by item, and the task number and personnel number are matched with the help of hungarian matching algorithm to form a row-column matching structure, the matrix position is locked under the joint participation of the completely adaptive bit, the substitute bit, the frozen bit and the limit bit, the batch task resource allocation table is counted, the continuous occupation segment, the module switching segment and the defect single insertion segment, the high load member and the low load member are circled, and the execution person number is replaced, the task sequence is rearranged, the continuous occupation time period is corrected, the module switching order is adjusted, and the iteration screening is executed with the help of simulated annealing algorithm, so that the resource reallocation process can continuously compare and retain the better arrangement state between local rewriting and overall arrangement.

The application discloses a positioning method based on a dynamic area of a robot, comprising the following steps: 1, in the case that the repositioning result fails, determining whether the matching score in the repositioning result is greater than a first preset score threshold; if yes, step 2 is entered; 2, the matching scores of the point cloud points falling on the corresponding area of the target map are weighted and calculated to obtain a target matching score; then step 3 is entered; 3, determining whether the target matching score is greater than a second preset score threshold; if yes, the positioning succeeds; otherwise, step 4 is entered; 4, setting a search distance based on the relationship between the mask extracted from the reference map and the mask extracted from the depth dynamic area of the target map, selecting a navigation target point in a preset positioning distance range based on the search distance; then step 5 is executed; 5, when the robot moves to the navigation target point, a repositioning result is obtained through a repositioning matching algorithm, and the repositioning result is detected to determine whether the positioning succeeds.

A small target detection method, system, device and medium based on a local attention feature correlation mechanism, the method comprising: data preprocessing, model construction, model training, small target detection; the system, device and medium are used to realize a small target detection method based on a local attention feature correlation mechanism; the application extracts spatial features and semantic features through a residual network, performs feature fusion through a feature pyramid mechanism, reconstructs features based on a local attention feature correlation mechanism, trains a model using a Hungarian matching algorithm, obtains an optimal matching model suitable for a data set, can ensure high accuracy with fewer iteration times, and has the characteristics of low network operation complexity, low training cost, easy model migration, and high model detection performance.

The application discloses a kind of prediction-based test resource matching method and system, belong to the field of automation test, including constructing test resource model and demand resource model, using resource qualifier set and corresponding capability value vector to express resource attribute;Predict future resource demand based on historical resource use data, combine prediction results with matching algorithm to establish prediction matching model;Resource matching calculation is carried out using multi-tree forest structure;Establish dynamic correction mechanism, when detecting that new task enters, prediction error exceeds threshold or fails to match, dynamically adjust prediction parameters and update model.The application can realize the interconnection application of virtual resource and entity resource, significantly improve the utilization of test resources, reduce resource conflict, optimize resource allocation efficiency, especially suitable for complex test environment of multi-task concurrency.

The application discloses a land resource supply and demand intelligent matching method, and belongs to the technical field of data processing and intelligent recommendation. The method comprises the following steps: acquiring the interactive behavior data of demand parties on land plots, historical land acquisition records, basic information and preset behavior type depth weights; determining a decision cycle reference value based on the historical land acquisition records; performing time decay processing on preference scores according to the decision cycle reference value, the depth weights of corresponding behavior types and behavior occurrence times; determining the similarity between demand parties according to the basic information, the historical land acquisition records and the interactive behavior data; and determining the predicted interest degree of demand parties on non-interacted land plots and generating a recommendation result according to a land plot similarity matching algorithm, the similarity, the decayed preference scores and the similarity. Through the implementation of the application, the problem that the traditional recommendation algorithm adopts a global unified time decay function to cause preference distortion can be solved, adaptive modeling of user preference timeliness can be realized, and the matching accuracy of supply and demand can be improved.

This invention relates to a cross-platform software porting system based on an AI agent. A type identification module generates code type features based on target code information. A rewrite execution module includes several different rewrite execution strategies and a rewrite matching algorithm. The rewrite matching algorithm calculates and generates a rewrite matching vector based on the code type features, and determines and executes the corresponding rewrite execution strategy based on the rewrite matching vector to obtain the rewritten code information. A rewrite evaluation module includes a rewrite evaluation strategy, which generates several test data sets to test the rewritten code information and generates test feedback data. The test feedback data is compared with pre-configured benchmark test data to generate test deviation data, and the parameters in the rewrite matching algorithm are rewritten based on the test deviation data. The selection and use of rewrite strategies are continuously iterated to ensure that each piece of code information matches the optimal rewrite strategy during subsequent software migration, guaranteeing the rewrite effect.

Methods, systems, and computer-readable storage media for a job scheduler system that determines a balance matrix for each group of N jobs to N job workers and a bipartite graph is generated using the balance matrix. The bipartite graph is processed using a maximum matching algorithm to ensure that the N jobs match the N job workers with a maximum value of the sum of a degree of balance of remaining resources of each of the N job workers. Each job is assigned to a respective job worker using the result of the maximum matching algorithm.