366 results about "Best matching" patented technology

The present invention provides a deep learning-based natural language understanding method and an intelligent teaching assistant system. First, it involves constructing a knowledge database and a question database, where learning material documents are saved into the knowledge database and preprocessed natural language information is saved into the question database. The method then involves learning and understanding the natural language information in the question database, searching for related knowledge points in the knowledge database based on the understood content, selecting the best-matched learning materials corresponding to these knowledge points as samples to respond to the natural language information, and generating a record that includes the question, response, and evaluation, which is saved into the knowledge database. Finally, it generates multiple forms of responses and outputs them according to the corresponding requirements.

The invention relates to the technical field of human resource management and information, and discloses an employment post recommendation method based on a human resource database, and the method comprises the following steps: S1, data collection; s2, data processing; s3, keyword extraction; s4, performing similarity calculation; s5, post filtering and sorting; s6, post recommendation; and S7, effect evaluation: through automatic data processing and similarity calculation, resumes most matched with post demands can be quickly screened out, the workload of recruiters is reduced, accurate matching degree evaluation is beneficial to realizing optimal configuration of talents and posts, employee loss and recruitment cost waste caused by mismatching are reduced, and the efficiency of recruitment is improved. The recruitment will and the matching degree of the job seekers can be improved through accurate recommendation, so that the recruitment success rate and efficiency are improved, more high-quality job seekers are attracted through efficient post recommendation and accurate matching, and the talent reserve and competitiveness of enterprises are enhanced.

The invention relates to the technical field of retrieval enhancement generation, in particular to a method for automatically adjusting retrieval enhancement generation parameters based on content feature modeling. The method comprises the following steps: receiving an original query text of a user, performing component analysis, identifying terminologies, general vocabularies and question entities, and quantifying to form query fingerprints; acquiring a historical behavior sequence of the user, and constructing a score reflecting the level of the user by combining the query fingerprints and adopting a time decay weighting algorithm; the user level score is converted into specific retrieval parameter configuration, and a retrieval strategy blueprint is formed; guiding document library retrieval according to the retrieval strategy blueprint, and screening out a candidate knowledge set which is most matched with the professional level of the user; and according to the user level score, a preset instruction template is intelligently filled, and a situational generation instruction is constructed. According to the method, the problem of non-uniform cognitive load caused by a traditional system is solved through a retrieval enhancement generation technology, and the technical knowledge transmission efficiency and the user satisfaction are remarkably improved.

The invention discloses an environment adaptability self-optimization method and system of an intelligent sensing robot, and relates to the technical field of robot control, and the method comprises the steps: obtaining a historical environment data set; acquiring a historical performance data set of the target robot; obtaining an optimal matching relationship; constructing a feature data set; constructing an environment-performance prediction model based on the feature data set; generating predicted performance data of the target robot; and optimizing and adjusting a strategy according to the predicted performance data. The technical problems that in the prior art, an intelligent sensing robot cannot dynamically and accurately predict self performance according to different complex and changeable environments, so that the environment adaptability of the intelligent sensing robot is insufficient, and diversified scene requirements are difficult to meet are solved, the performance of the intelligent sensing robot in the different environments is predicted, and the intelligent sensing robot is more intelligent. And optimization and adjustment can be carried out as required based on a prediction result, so that the method can better adapt to the environment, and the performance is improved.

An example device for decoding video data includes a memory configured to store video data; and one or more processors configured to: decode data representing an initial motion vector for a current block of the video data, the initial motion vector having integer-motion vector difference (MVD) precision; determine a search range around a reference area identified by the initial motion vector in a reference picture; perform a template matching search process in the search range to identify a best matching region; determine error values for neighboring pixels to the best matching region; use the error values for the neighboring pixels to perform a model-based fractional-pixel motion vector refinement to derive motion vector difference values; apply at least one of the motion vector difference values to the initial motion vector to determine a refined motion vector for the current block; and decode the current block using the refined motion vector.

A system and method for selecting, from a series of cardiac implants having different sizes, the cardiac implant having optimum size for implantation in a patient. The method includes obtaining data representative of a patient-specific cardiac region and predicting the optimum size of the cardiac implant best matching a predefined criterion when deployed in the cardiac region. The predicting includes querying a database; determining parameter values for a parametric model representation of the patient-specific cardiac region; and / or entering the data representative of the patient-specific cardiac region into an artificial intelligence device.

The invention discloses an intelligent scheduling and order dispatching management method and system, and relates to the technical field of intelligent scheduling, and the method comprises the steps: collecting original data, and carrying out the preprocessing; performing feature extraction on the preprocessed original data to obtain task priority related features and employee condition related features; based on historical data, constructing an intelligent scheduling model, inputting task priority related features into the intelligent scheduling model, calculating task priority scores, and performing task priority ranking according to the task priority scores; on the basis of task priority ranking and employee condition related characteristics, optimal matching personnel are automatically selected for task allocation; and monitoring execution condition data of the task in real time, and optimizing the intelligent scheduling model by utilizing the execution condition data. According to the method, the intelligent scheduling model is constructed, the health and skills of employees are considered, efficient and reasonable distribution is ensured, the model is optimized in real time, and the task execution quality and efficiency are improved.

The invention belongs to the technical field of cloud computing and edge computing collaboration, and particularly discloses an intelligent scheduling and optimizing method for a cloud-edge collaboration network based on reinforcement learning. By constructing the state sensing matrix and generating the action decision vector, the problem that a traditional scheduling method is insufficient in correlation analysis of multi-dimensional operation state data in a complex network environment is solved, and the comprehensive sensing capability of the operation state of the network node is improved; a dynamic mapping mechanism among the running state, the resource limitation and the task allocation strategy is established, the task allocation and resource scheduling strategy is automatically and differentially adjusted according to the real-time state of the node, and the optimal matching between the task demand and the resource supply and the dynamic balance between the performance and the efficiency are realized; through performance index monitoring and closed-loop feedback optimization, the scheduling effect is mastered in real time, continuous iterative optimization is performed on the reinforcement learning model according to objective data, and resource waste and scheduling delay are reduced.

The invention discloses a heterogeneous computing system, a cache consistency maintenance method and device, equipment and a medium, and relates to the technical field of heterogeneous computing. The method comprises the step of redefining a cache coherence protocol of the heterogeneous computing system as a metadata index protocol, a multicast synchronization protocol and a hybrid response protocol. Entropy weights of different feature dimensions are determined according to feature values of all data blocks of the heterogeneous computing system, and a protocol most matched with the task load running state at the current moment is determined from a metadata index protocol, a multicast synchronization protocol and a mixed response protocol according to the entropy weights of the different feature dimensions; and determining whether to switch the protocol according to whether the current protocol is consistent with the selected protocol. According to the method, the problem that the protocol cannot be effectively optimized in related technologies can be solved, and the consistency protocol which is most matched with the current task load of the heterogeneous computing system can be accurately determined.

The invention provides an agent strategy optimization method based on multi-modal fusion, an agent and electronic equipment. The method comprises the following steps: selecting a best matching fusion strategy for a target task in a pre-constructed fusion strategy library; wherein the fusion strategy library comprises a plurality of predefined fusion strategies; fusing the multi-modal data required by the target task by using a best matching fusion strategy; when the target task is executed, learning is carried out based on the fused multi-modal data corresponding to the target task, and a task decision is generated. According to the method, information loss possibly caused by simple splicing can be avoided, a foundation is laid for the accuracy of subsequent task decision making, and meanwhile, the task decision making can be dynamically adjusted according to the interaction condition with other agents, so that rapid and efficient learning is realized in a complex scene, and the accuracy and adaptability of agent decision making are greatly improved.

The invention provides a multi-stage progressive enhanced knowledge retrieval method for industrial process operation and maintenance, and relates to the field of natural language processing and information retrieval, and the method comprises the following steps: constructing a knowledge base in the field of industrial process operation and maintenance; obtaining user query and classifying; screening the documents in the knowledge base through the classified user query and a BM25 algorithm, and determining a first candidate document; screening the first candidate document through a lightweight filtering method combining TF-IDF word frequency-inverse document frequency and cosine similarity to obtain a second candidate document; the second candidate documents are accurately sorted through retrieval based on dense vectors, answers most matched with user query are obtained, the retrieval process is optimized layer by layer through retrieval strategies of four stages of query routing, keyword recall, lightweight filtering and vector fine arrangement, and therefore the retrieval efficiency and the retrieval precision are improved.

A tallying data processing method and system for an intelligent port, a medium and a product relate to the field of electric digital data processing, and the method comprises the following steps: obtaining a ship loading and unloading plan, tallying operation records and cost accounting data according to a preset period, and generating standard tallying data; extracting feature data in a pre-time window from the standard tallying data; inputting the feature data into a prediction calculation model, and generating a plurality of groups of loading and unloading plan change prediction scenes according to a historical operation mode; performing parallel calculation on the multiple groups of prediction scenes to obtain scene prediction data; comparing the real-time tallying data acquired at the port site with the scene prediction data, and calculating to obtain a data goodness of fit; selecting the most matched prediction scene as a current execution scene based on the data goodness of fit, and storing other prediction scenes into a standby scene library; and generating a tallying operation instruction and expense settlement data according to the current execution scene. By implementing the application, the efficiency of port multi-link data processing can be improved.

An example device for decoding video data includes a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry, the processing system being configured to: generate a prediction block for a current block of video data using a neural network; determine an equivalent intra mode for the prediction block from a set of available intra-prediction modes using decoder-side intra mode derivation (DIMD), the equivalent intra mode representing one of the intra-prediction modes that would generate an intra-prediction block that would best match the prediction block generated using the neural network; decode a residual block for the current block of the video data based on the equivalent intra mode; and combine the prediction block with the residual block to decode the current block of the video data.

Disclosed herein are system, method, and computer program product embodiments for a customer records management translation extension. A computer system receives customer data comprising a first name, last name, an email address, and a phone number from a front-end interface of an agent workstation. Based on the customer data, the computer system obtains one or more customer objects from a customer object database, wherein each of the customer object comprises a customer identifier. The computer system selects the customer object that best matches the customer data and obtains a customer lead identifier from the customer object database that corresponds to the customer identifier of the selected customer object. Based on the customer lead identifier, the computer system obtains a lead object from a lead object database and generates a link to the lead object. Finally, the computer system transmits the link to the front-end interface of the agent workstation.

The invention relates to the technical field of information interaction, in particular to a retail customer service response method and a retail customer service system. The response method comprises the following steps: based on retail data, constructing a retail large language model by using a Transform model architecture, and carrying out training and fine tuning, so that the retail large language model has a question and answer ability in the retail field; performing feature extraction based on the multi-modal data input by the user to generate question and answer text data; based on the question and answer text data, topK information with most matched semantics is retrieved from a preset vector knowledge base; and based on the text data and the topK information, calling the retail large language model to respond. According to the response method of the retail customer service, questions of the user can be deeply understood, intelligent response is carried out, and the shopping experience of the user is improved.

The invention provides a well drilling and completion report self-adaptive SQL generation and intelligent question and answer data processing method. The method comprises the steps that S1, natural language query input of a user is received; s2, inputting user query input into a 'Zhongqi-7b-chat-1m' model, understanding a query intention, and outputting a most matched database table name; s3, accessing database metadata according to a table name output by the model, and obtaining structure information corresponding to the table; s4, inputting the natural language query and the obtained table structure information into a 'Zhongs-Code-32B-Instruct' model together, and generating an SQL (Structured Query Language) query statement conforming to semantic logic by the 'Zhongs-Code-32B-Instruct' model; and S5, executing the generated SQL query statement, and returning a structured query result. According to the method, the advanced natural language processing technology and the deep learning model are combined, so that automatic conversion from natural language query to standardized SQL is realized. According to the method, the query efficiency and accuracy are greatly improved, and the method is particularly suitable for non-technical personnel to perform complex drilling data query.

The invention relates to the field of artificial intelligence, and discloses a dialogue process control method and device based on a large language model, equipment and a medium, and the method comprises the steps: obtaining a predefined target business range, and collecting corresponding historical dialogue data; performing data mining and analysis on the historical dialogue data, extracting a plurality of dialogue strategies, and constructing to obtain a strategy library; generating a corresponding dialogue process according to each dialogue strategy, and configuring a response template of each dialogue node in the dialogue process; when an input text of a user is received, matching in the strategy library according to the input text to obtain a target strategy, and switching to a target dialogue node according to a dialogue process of the target strategy; and generating a corresponding prompt text based on the response template of the target dialogue node and the input text, inputting the prompt text into the trained large language model, and generating a reply text of the target dialogue node. A strategy library is formed according to service requirements, replies are made by a unified response template based on the most matched dialogue strategy, and dialogue accuracy and reliability are improved.

The embodiment of the invention provides a marketing short video generation method and device based on a large language model, and the method comprises the steps: carrying out the matching degree analysis of a hot title and product data based on the large language model, and outputting a hot topic which is most matched with a product according to the sequence of the matching degree from high to low; searching a hot video related to the most matched hot topic in a video platform, and extracting an oral copy in the hot video based on an automatic voice recognition technology; generating a creation copywriting by using a large language model based on the oral copywriting, the hot topics and the product data; and performing similarity matching on the embedded vector corresponding to the created copywriting and the semantic vector of the video slice in the database, and sorting and generating a mixed video meeting the duration requirement according to the similarity.

The invention provides a code reuse method and device based on AI drive, equipment and a medium. When a code submission event is detected, a code scanning process is triggered, a code analysis module driven by AI carries out multi-dimensional analysis on submitted codes, quantitative evaluation is carried out on the basis of a preset reusability evaluation model, and code snippets meeting a reuse standard are stored in a code knowledge base with a semantic index structure; analyzing annotation semantics based on a natural language processing technology through an AI retrieval engine, calculating semantic similarity between demand description and code snippets in a knowledge base in combination with a deep learning model, and positioning the code snippets which are optimally matched; after code multiplexing execution, performing incremental modification on the multiplexing code snippets and automatically generating change records; and carrying out value layering on the code snippets based on the Pareto analysis principle by using frequency trend prediction. Through combination of the AI technology and code reuse, the development efficiency can be remarkably improved.

A data management system receives updates to records of a source dimension. Some records of the source dimension reference target dimensions. The data management system identifies template records from existing records in the source dimension for modeling changes to connections with the target dimensions based on the updated records in the source dimension. The template records are discovered using rules-driven processes, AI-driven processes, or a serial or parallel hybrid processes including rules and AI. These processes use ancestor information from the updated records to find best-matching template records. The rules-driven processes additionally rely on matching fields, and the AI-driven processes additionally rely on vector embeddings and optionally clustering. Updates are made to the target records in the target dimensions, including any roll-up structures indicated for data propagation, identified using the template records, and downstream applications using the target records may consume the updates.

The invention discloses a heterogeneous computing system, a cache consistency maintenance method and device, equipment and a medium, and relates to the technical field of heterogeneous computing. The method comprises the following steps: determining a hotspot data access path at the current moment according to an access sequence and dependency relationship strength of each data block of the heterogeneous computing system at the current moment; generating current running state information according to the hotspot data access path, the workload information of the heterogeneous computing system at the current moment, the cache effective information and the cross-device communication information; and based on the relationship between the running state of the heterogeneous computing system and the cache coherence protocol type, determining the cache coherence protocol most matched with the current running state of the heterogeneous computing system according to the current running state information. According to the method, the problem that the cache consistency protocol cannot be effectively and dynamically optimized in related technologies can be solved, the cross-device data dependency relationship can be dynamically captured, the dynamic change can be accurately sensed, and the high performance and data consistency of the system can be ensured.

The invention relates to the field of artificial intelligence, in particular to an intelligent diagnosis system for crop diseases and insect pests and a self-evolution method of the intelligent diagnosis system. The diagnosis system extracts features from a disease and insect pest image and a description text of a user for disease and insect pests, performs multi-modal fusion, generates a diagnosis report by using the fused features, and further comprises a gating network and a LoRA adapter which is specific for various disease and insect pest tags. And the gating network selects a corresponding LoRA adapter according to the description text of the plant diseases and insect pests, the corresponding LoRA adapter is dynamically injected into a Transform layer of the basic model, a reasoning path of the LoRA adapter is temporarily reconstructed, and the model with updated parameters is utilized to generate a diagnosis text. According to the method, the most matched expert capability can be loaded in time, so that the adaptability and the diagnosis accuracy of complex and changeable diagnosis scenes are remarkably improved.

The embodiment of the invention provides a CSI (Channel State Information) performance monitoring report triggering method based on an AI / ML (Artificial Intelligence / Markup Language) model and a related device, and provides a channel environment adaptive cumulative sum CUSUM algorithm, the algorithm configures different CUSUM parameter sets for different states of UE (User Equipment) respectively, each CUSUM parameter set comprises a relaxation factor k and a decision threshold h, and the relaxation factor k and the decision threshold h correspond to each other. The values of k and h in different parameter sets are different; the UE can select the most matched CUSUM parameter according to the current state (or scene), so that a performance monitoring mechanism of the UE can intelligently balance the detection sensitivity and robustness. Moreover, according to the scheme, performance differences are accumulated through a CUSUM algorithm and then compared with a decision threshold value to judge whether a performance degradation report is triggered or not, instantaneous jitter of a channel is effectively filtered through accumulation of the performance differences, and it is ensured that the report is triggered only when the performance of the AI / ML model continuously declines. Therefore, the uplink signaling overhead caused by mistaken touch and the resource waste caused by subsequent network response (such as mode switching) are reduced.

The invention provides a three-dimensional flow velocity field inversion method and system based on coherence-assisted SAR adaptive offset tracking, and a storage medium, so as to improve the problem of decoherence caused by time heterogeneity in a synthetic aperture radar interferometry (InSAR) technology, and relates to the technical field of electric power engineering geological disaster monitoring. The method comprises the following steps: establishing a space-time baseline network between SAR images; obtaining coherence data after geocoding; selecting a pair of SAR images from the space-time baseline network as a reference unit, calculating an offset result through a pixel offset tracking technology for the reference unit, and determining an optimal matching window parameter of the reference unit; establishing a mapping function between coherence and optimal matching window parameters; according to the established mapping function, calculating an optimal matching window parameter of each remaining SAR image pair; and in combination with the line-of-sight average deformation rate fields of the ascending and descending rails, inverting a surface three-dimensional flow velocity deformation field of the target area through a geometric vector decomposition model.

The invention relates to the field of data processing, in particular to an injection mold temperature control method and system, and the method comprises the steps: uniformly dividing the surfaces of injection molds of the same model and different batches into regions based on the area, and obtaining a historical temperature sequence and a real-time temperature sequence of each region; a sliding window is preset for the historical temperature sequence, the temperature fluctuation degree is calculated, and the temperature sensitivity degree of each area is determined. And calculating the similarity between the real-time temperature sequence and the historical production stage temperature sequence, selecting the historical stage with the maximum similarity as the best matching stage, and calculating the comprehensive temperature error. And according to the temperature sensitivity degree and the comprehensive temperature error, a temperature control signal of the PID control center is corrected, a comprehensive temperature control signal is obtained, and accurate temperature control is realized. By calculating the temperature sensitivity degree and dynamically adjusting the temperature control strategy, accurate and stable temperature control is achieved, manual intervention is reduced, and the production efficiency and the product quality are improved.

The invention belongs to the related technical field of path planning, and discloses a line patrol planning method and system considering route information age, and the method comprises the steps: judging whether a route network graph G has an Euler loop or not, finding out all nodes with odd degrees in the graph G if the Euler loop does not exist, and constructing a complete graph Gf; solving a minimum weight perfect matching problem for the graph Gf to obtain a set OM of optimally matched edges, taking the graph G as an initialized expansion graph G ', traversing each edge (v, u) of the set OM, searching a shortest path Rs from a node v to a node u in the graph G, adding each edge in the path Rs into the current graph G', and obtaining a final graph G 'after traversing is completed; and searching an Euler loop as a line patrol path R from the graph G '. According to the method, the Euler loop is constructed as the line patrol path, so that the average age information of the to-be-patrolled network diagram can be optimized to ensure that each part in the line is patrolled in time, and the patrol reliability is ensured.

The invention discloses a research and development demand and research and development personnel accurate matching method and system, and relates to the technical field of task allocation, and the method comprises the steps: obtaining a research and development demand document meeting a description rule; the method comprises the following steps: automatically disassembling an obtained research and development demand document into a research and development task set with minimum granularity through three operations of natural language processing, document pre-training learning and deep learning; key features of each research and development task in the set are extracted, the key features are compared with items in a preset task classification and classification library through a matching algorithm, and the most matched task type and level are found out; and on the basis of the key features, task types and levels of the research and development tasks, the research and development tasks are compared with research and development personnel in a preset research and development personnel comprehensive rating library through a matching algorithm, the most suitable research and development personnel with the shortest prediction time are found out, and the corresponding research and development tasks are distributed. According to the invention, accurate matching between research and development requirements and research and development personnel can be realized, the research and development efficiency and quality are improved, and resource waste is reduced.

The invention relates to the technical field of artificial intelligence, in particular to an emotional dialogue method of a terminal digital person based on a large model, which comprises the following steps: after a user sends a query, a system retrieves the most matched memory fragment by combining the semantic and emotion information of the query, so that the dialogue content is consistent with both semantic logic and emotional information when being generated; and resonance with the emotion of the user can be generated. According to the method, the generated dialogue can be more humanized through an emotion perception retrieval and generation mechanism, the emotional state of the user can be effectively adapted, and the emotional interaction effect of a terminal digital person is improved.

The invention discloses an automatic impedance matching method for a radio frequency matcher, and the method comprises the steps: alternately adjusting the size of a vacuum variable capacitor through the standing-wave ratio and other information obtained by a measurement module and through several stages of an algorithm, including the steps of gradient test, iterative fitting, extreme value backtracking and the like, so as to gradually reach an optimal matching point; the method is clear in logic state, simple in parameter adjusting process and convenient for engineering application and maintenance. Meanwhile, the matching speed of the algorithm is high, and the influence caused by measurement noise can be improved by adjusting the window length through variable-length slope fitting.

The invention discloses a building construction progress intelligent monitoring method and device and electronic equipment, and belongs to the technical field of intelligent monitoring, and the method comprises the steps: comparing a label of a building construction image with a building information model library, and obtaining a two-dimensional visual angle image data set; performing semantic segmentation on a bounding box of the building construction image to obtain a segmentation mask set; calculating the cosine similarity of the two-dimensional visual angle image data set and the segmentation mask set according to the feature vector cosine similarity, and determining the angle corresponding to the maximum value of the cosine similarity as the best matching angle; based on the optimal matching angle, a two-dimensional optimal matching view angle image and an optimal matching mask are determined, and the construction progress of the building construction image is determined; semantic segmentation is carried out on the bounding box, and parts related to the building are extracted in a targeted mode; and by calculating the cosine similarity between the two-dimensional visual angle image data set and the segmentation mask set, similarity matching is carried out on the building construction image and the building information model library, so that the monitoring accuracy is further ensured.