278 results about "Application areas" patented technology

The invention discloses an LLM capability enhancement method of a hybrid enhancement strategy, and particularly relates to the technical field of natural language processing. The method comprises the following steps: obtaining corpus data and external literature data of a target application field, carrying out denoising, word segmentation and semantic indexing processing, and establishing a searchable heterogeneous knowledge base; secondly, classifying the corpus data by adopting a topic analysis and word vector clustering method to form a basic corpus set; performing multi-round parameter updating on the large language model by using a domain fine tuning algorithm based on the basic corpus set, and setting a fusion threshold value between a new parameter and an original parameter; and retrieving related literature fragments from the heterogeneous knowledge base through a matching algorithm, screening content conforming to field correlation by utilizing semantic similarity evaluation, fusing the content with the fine-tuned model, processing a fusion result by adopting a context fusion algorithm and an entity linking method, completing syntactic analysis, and generating a precise solution oriented to the target application field.

Disclosed in the present application are an evaluation method and apparatus for a large language model, a storage medium and a computer device. The method comprises: on the basis of a target application field of a target large language model to be evaluated, acquiring a test question bank corresponding to the target large language model, wherein the test question bank comprises objective questions belonging to the target application field, and question stems and answers of the objective questions are obtained by analyzing corpus samples of the target application field; and using the test question bank to test the target large language model, so as to obtain an output result of the target large language model for the tested objective questions; and, on the basis of answers corresponding to the tested objective questions and the output result of the target large language model for the tested objective questions, evaluating the target large language model.

A decentralized artificial intelligence platform is disclosed that enables secure sharing and execution of AI modules in sensitive application domains. The platform comprises a knowledge module registry for discovering specialized AI modules, a security framework enforcing structural integrity of AI modules, a zero-knowledge proof validation service for verifying usage conditions without exposing private data, and a blockchain-based value chain for managing smart contracts and payments. In operation, an AI agent can fetch a required AI module from the knowledge module registry, prove the right to use it, execute the AI module on local data, and automatically pay the AI module's provider through a blockchain transaction.

The invention relates to the field of intelligent optimization systems and application thereof, in particular to a grain storage and transportation disorder plan autonomous scheduling system and method. Comprising the following steps: carrying out calibration and time synchronization on collected data, and carrying out data cleaning, screening, redundancy removal and anomaly detection processing; further performing encryption and structuring processing; constructing a prediction model based on the encrypted structured data, generating prediction output, dynamically optimizing and updating model parameters, and evaluating the prediction performance of the prediction model; an optimization task scheduling scheme is output based on the data after anomaly detection and prediction; calculating performance evaluation indexes and generating optimization suggestions; a new resource allocation strategy and a task scheduling scheme are provided, and functions of monitoring system performance in real time, adjusting an interface of system parameters and the like are provided for users. The problem that the accuracy and the adaptability are low when dynamic data are processed is solved. And in the face of complex and dynamic tasks, resource allocation cannot be adjusted in real time to adapt to constantly changing requirements.

Systems and methods for measuring, grading, evaluating, and comparing AI models via a graphical user interface are disclosed. The technology obtains a set of application domains of the AI model in which an AI model will be used. The application domains are mapped to one or more guidelines to determine a set of guidelines that define operational boundaries of the AI model. The guidelines are used to generate assessment domains, each associated with specific benchmarks that include indicators of a degree of satisfaction with the guidelines. For each assessment domain, assessments are constructed to evaluate the AI model's degree of satisfaction with the corresponding guidelines. The AI model is then evaluated against the assessments. Based on these comparisons, grades are assigned to the AI model for each assessment domain. The application-domain-specific grades are generated and displayed at a GUI, reflecting the AI model's degree of satisfaction with the guidelines.

The invention discloses an intelligent number asking method based on a large language model, and relates to the field of artificial intelligence application, a question proposed by a user is analyzed and understood through an LLM, a number asking API matched with the question is searched according to the question of the user, then a system inputs the searched API, query parameters of the API and the question of the user into the LLM together, and the query parameters of the API and the question of the user are input into the LLM; the LLM further analyzes user questions and API query parameters, then generates an API call request body and provides the API call request body to the system; when the number query API cannot be found, performing a query task by using a query SQL; the problem that the length of the cue word exceeds the context length limit of the LLM due to the fact that the number of APIs for query access is too large and API description is too long is effectively solved, and the situation that when the LLM is pre-trained, some knowledge is not learned or expired, and consequently the problem cannot be solved or mistakenly solved when the number asking requirement of a user is processed is avoided by adding a special label into the cue word.

The invention provides a vocational ability assessment system based on a skill map, and relates to the field of human resource technology and knowledge map application. The evaluation main system comprises a skill star map generation module, an occupational trajectory simulation module, a skill challenge module, a skill authentication chain module, a future skill navigation module, a skill collaborative ecological module, a skill evolutionary tree module, an occupational story generation module, a skill energy pool module, an occupational time capsule module and a control flow management module; according to the invention, the dynamic skill star map is constructed and the 5G network is combined to transmit data in real time, so that the occupational experience, learning records and test data of the user can be collected in time, and the node weight is dynamically adjusted through the semantic analysis algorithm and the weighted scoring algorithm; the problems that traditional manual evaluation and online testing are high in subjectivity and low in efficiency, and the capability cannot be accurately quantified are effectively solved.

The invention discloses a user non-inductive resource efficient scheduling method and device for a VR application and a storage medium, and belongs to the field of VR application. The method comprises the following steps: respectively extracting track time sequence features and video content features from user track data and image content data; respectively calculating attention weights of track time sequence features and video content features through a cross attention mechanism, adaptively and dynamically adjusting the attention weights of the features, and generating fusion feature information; inputting the fused feature information into a viewport prediction model, and outputting a viewport position prediction result in a future time window; dynamically selecting a multi-stream data source to perform resource scheduling by taking the viewport position prediction result and the current network state as resource scheduling conditions; and allocating a first code stream channel and network resources meeting the set QOS standard to a high-priority region concerned by the user in the viewport position prediction result. The dynamic change and scene switching of user behaviors are effectively handled, and the user experience quality is ensured.

The invention discloses a large model fine tuning data acquisition method and device, equipment and a storage medium. The method comprises the following steps: generating an input instruction based on an application field, a training question, an original training data document and a document cue word of a to-be-adjusted model, and inputting the input instruction into a language generation model with a reflection mechanism to generate a plurality of question and answer results; wherein the document prompt word is used for indicating the generation requirement. Then, candidate results are determined from the question and answer results, and target vector clauses are extracted from the original training data document; and by calculating the similarity between the candidate result and the target vector clause and carrying out threshold judgment, screening out a target result meeting a condition. And finally, combining the target result and the training question into a question-answer pair to form large model fine tuning data. The answer generation is guided through the document cue word, the multiple question and answer results are generated in combination with the reflection mechanism, the optimal answer is screened through similarity matching, and therefore it is ensured that the question and answer result serving as the target result is comprehensive and accurate and meets the requirement.

The invention belongs to the field of federated learning technology application, and particularly relates to a federated learning method based on distributed perception regularization, which comprises the following steps: in each round of federated learning, a server determines M clients participating in the training; the server obtains a data processing mode of each client according to the computing power and the local data volume, and each client obtains training data according to the data processing mode corresponding to the client; the server issues a global model, and each client trains the global model through training data to obtain local model parameters and uploads the local model parameters to the server; the server calculates a time window according to the historical training data, and collects local model parameters in the time window for aggregation to obtain a new global model; repeating the operation until the maximum federal learning round is reached; according to the invention, the problem of equipment isomerism among a plurality of clients is effectively relieved.

The invention provides an intelligent assistant method and system based on a large model, relates to the field of large model application, is used for providing a question and answer result for a user question, and comprises the following steps: constructing an entity recognition cue word, and recognizing an entity in the user question through the large model; constructing intention recognition and tool selection prompt words, recognizing user intentions in the user questions through a large model, and determining tools to be used; based on the assembled user questions and entities, related information is retrieved from a pre-constructed vector knowledge base, and a large model is combined with the retrieved related information to enhance and generate an answer text; processing the answer text according to the user intention and the tool, and outputting a final question and answer result; according to the method, the limitation that a traditional intelligent assistant cannot deeply understand user semantics and only can mechanically carry out rule matching is solved, and the requirements of the user can be more accurately grasped to provide a more accurate problem solving strategy.

The invention discloses a code generation method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: screening out a target reusable code meta-model corresponding to code generation demand information from a pre-constructed code model library according to the code generation demand information; the code model library comprises reusable code meta-models corresponding to various businesses, and the reusable code meta-models comprise one or more of an application template class model, a function module class model and a code snippet class model; verifying the target reusable code meta-model by using a pre-constructed rule base to obtain a verified target reusable code meta-model; and combining all the target reusable code meta-models passing the verification to obtain a program code corresponding to the code generation demand information. On the basis of ensuring the accuracy of code generation, the generation of multi-field program codes can be realized, and the universality of code generation in the application field is improved.

The invention discloses a Teamcenter-based model parameter and bill of materials (BOM) management method, relates to the field of product life cycle management system application, and aims to realize efficient management of model parameters and a bill of materials (BOM) through the steps of integrated data management, automatic process, authority control, version control, intelligent assistance and the like on the basis of a Teamcenter platform. The uniform storage and integration capability of Teamcenter is utilized to ensure the consistency and integrity of model parameters and BOM data; automatic processes such as automatic consistency checking and automatic PDF generation are designed, and manual intervention is reduced; the data security is guaranteed through an authority management function; a strict version control mechanism is implemented to ensure data traceability; and intelligent assistance is provided for the user by using functions of searching, querying and the like, so that the working efficiency is improved. According to the method, the problems of data updating lagging, high error rate and untimely information sharing in a traditional management mode are effectively solved, and powerful support is provided for intelligent manufacturing and digital transformation of enterprises.

The invention discloses a label-based digital equipment model dynamic creation method and system, and relates to the field of complex data integration and equipment management technology application in the power industry, and the method comprises the following steps: predefining a general data label model, dynamically configuring a query model, and establishing a database; and constructing a digital equipment data entity and designing a technical process of parallel computing and asynchronous processing. Data standardization is realized, and the query efficiency is improved; through a dynamic configuration mechanism, the system can automatically generate the query model, and the flexibility is improved; through the data entity construction method, different business data can be associated through a standardized model, and the data consistency is improved; according to the method, parallel computing and cache optimization technologies are utilized, and data query and processing are accelerated; according to the method, an incremental updating mechanism is adopted, so that the real-time performance and consistency of data are ensured; according to the method, the creation efficiency, query performance and system flexibility of the equipment model can be remarkably improved, and better technical support is provided for digital transformation of the power industry.

Embodiments of systems and methods for dynamic and / or live retrieval and display of relevant clinical outputs to a clinical entity are provided, for a clinical entity processing a case. The systems and methods leverage advanced models (e.g., multimodal models) for retrieval, processing, and rendering of relevant information to the clinical entity, in a manner that improves worklist processing performance. Application areas include systems and tools for radiologists.

The invention particularly relates to a statement embellishing method and system based on a large model. According to the statement retouching method based on the large model, massive natural language statements are collected in a user-defined mode and preprocessed, the preprocessed training data and the deep learning technology are utilized to train a large-scale language model based on a Transform architecture, a statement retouching model is built based on the trained large-scale language model, and a plurality of candidate retouching results are generated; establishing an evaluation mechanism in a user-defined manner, sorting from high to low according to scoring results, and selecting a polishing result in a user-defined manner; and outputting the polished statement to the user, and allowing the user to apply the statement to various scenes. According to the statement polishing method and system based on the large model, the input statement is deeply analyzed and processed through the deep learning model, automatic statement polishing is achieved, the quality and efficiency of text polishing are improved, the application field of text polishing is expanded, and the requirement of the modern society for high-quality texts can be met.

The invention relates to the field of mobile applications, and particularly provides a cross-platform mobile application system and a task processing method thereof, a terminal and a medium, and the system comprises a cross-platform application framework layer which is used for constructing an interface and processing an interaction event; the core intelligent layer is constructed based on an AI agent development suite and is used for dynamically scheduling an AI agent according to a user intention and an application state; the AI agent pool comprises a plurality of agents with independent functions; the native function interface layer is used for bridging and calling native hardware functions of the equipment; and the large language model service interface is used for accessing large language model service. The method comprises the steps of receiving and standardizing a user event, analyzing a user intention, dynamically scheduling an agent to cooperatively execute a task, and finally updating a user interface by calling a native hardware function or accessing a large language model to enhance the capability. The intelligent level, the development efficiency and the user experience of the mobile application are improved.

The invention relates to the field of large model application, and provides a cloud environment intelligent operation and maintenance method and system based on an MCP protocol. The method comprises the following steps: in response to a natural language task instruction input by a user, generating a structured operation instruction according to an accessed large model; the structured operation instruction is sent to the user side for confirmation, if the user side modifies historical information or to-be-confirmed content, difference points are marked, incremental context is generated, and then the incremental context is sent to the server side to execute specific operation; after a user side submits modification information or makes a new request, correlation analysis is carried out on the large model, only relevant conclusions are reserved or intermediate key results are summarized, the results are submitted to the large model, a next decision is generated, and a natural language task instruction is directly executed and returned to the user side. According to the method, the context length can be greatly reduced, and the memory loss problem of the model in a long task can be relieved.

The invention relates to the field of computer application, in particular to a method, a device, equipment and a medium for integrating a heterogeneous business system and a workflow system.The method comprises the steps that business entity modeling is conducted on business receipts of the heterogeneous system, and a business table structure, a field type and a business entity referenced by associated fields are described in a setting form; binding a corresponding heterogeneous service system data query API (Application Program Interface) for the created service entity; performing approval form modeling, binding a mapping relationship between form control display contents and business entity fields, generating an approval form, and mapping business form data in real time by the approval form; performing flow modeling, defining a flow chart and binding a flow event, and calling a heterogeneous service system data query API to write back service form data at the event execution time; and modifying a submission button response event of the business form, and calling an open standard API of the workflow system to initiate an approval process. And flow centralized management and control are realized, approval entrances are unified, and consistent approval experience is provided.

The invention discloses a multi-source big data analysis cloud platform and a data analysis method thereof, and relates to the technical field of big data analysis. The method comprises the steps of receiving multi-source data to form a multi-source big database, obtaining a to-be-analyzed application field, extracting theme elements, capturing corresponding application field data from the multi-source big database and classifying the application field data, constructing an application field classification database, determining a multi-source data fusion coefficient influencing the application field according to the theme elements, and analyzing the multi-source data fusion coefficient. And performing multi-source data classification feature extraction and feature fusion on the application field classification database to generate multi-source data fusion features, and inputting the multi-source data fusion features into a pre-trained application field data analysis model to obtain an analysis result. According to the method, mass data of different formats and structures from different service systems can be gathered, multi-source data of the required application field can be quickly captured from multi-source big data, the multi-source data is integrated and analyzed, potential relations which are difficult to perceive by a traditional analysis method are found, and the analysis accuracy and reliability are improved.

The invention relates to the technical field of detection devices, in particular to a road maintenance ground permeability detection device which comprises a detection support, an inner enclosure, an outer enclosure and a check ring. The inner enclosure is arranged in the vertical direction and located at the lower end of the detection support, and a detection space is defined among the inner enclosure, the detection support and the ground. The outer enclosure is rotationally installed at the lower end of the check ring, and a smearing space is defined by the detection support, the inner enclosure, the outer enclosure and the check ring. According to the ground permeability detection device for road maintenance, the detection support, the inner enclosure, the outer enclosure and the check ring are arranged and matched, when a sealing material is smeared, an automatic smearing mode is adopted to replace manual smearing, the smearing area is large, the efficiency is high, and in the whole smearing process, the smearing efficiency is high; the detection space and the smearing space are separated from each other through the inner enclosure, so that the sealing material in the smearing space can be prevented from entering the detection space, and the accuracy of subsequent detection is improved.

The invention provides a method, device and equipment for generating a test case based on a large language model, and the method comprises the steps: obtaining a test demand of the test case, analyzing the test demand, and obtaining the type, the application field, the business process and the first key test information of the test case; on the basis of the type of the test case, the application field, the business process and the first key test information, constructing a cue word for generating the test case; and based on the cue word, adopting a pre-trained large language model to generate a test case. According to the method and the device, the cue word is constructed by considering the application field and the business process to which the test case belongs, so that the large language model can construct the test case in combination with knowledge information of the application field and context constraints of related business processes, and the generated test case naturally conforms to system business logic and a state machine contract; and seamless embedding with the existing system is realized.

The invention discloses a software testing system based on virtual reality, which comprises a data acquisition module, a testing module and an output module, and is characterized in that the testing module is used for deploying a running exercise amount target of a user on the current day; the data acquisition module, the test module and the output module are in communication connection with one another, user picture information is called and analyzed within different time through the head inclination angle detection sub-module, and a favorable basis is provided for the test system to monitor the motion state of a user; a foot force application area detection sub-module is used for acquiring a specific foot force application area of the user in a monitoring time period, and judging whether the current motion state of the user is stable or not; through the step number change trend detection sub-module, the step number increase condition of the user in the monitoring time period is monitored, the humanization degree of the treadmill is greatly improved, the daily experience of the user using the treadmill is improved, and the treadmill has the advantages of being high in humanization degree and high in motion parameter monitoring precision.

The invention discloses an official document processing method and device based on a large model and an official document generating and checking all-in-one machine. The official document processing method based on the large model can quickly respond to a user request, automatically match and call a pre-trained official document generation sub-model corresponding to a literary and sports category by automatically identifying an official document title and an official document keyword, and automatically process the official document in combination with knowledge base data of a corresponding application field. According to the method, the large language model technology is utilized to quickly and intelligently generate the official document file with high quality, official document processing which is specially refined in various official document styles and is combined with the user industry can be realized, and the official document processing efficiency is greatly improved. According to the document generating and checking all-in-one machine, software and hardware are perfectly combined, the problems of document format accurate generation, large model illusion, safety risk, computing power support and the like can be solved at the same time, safe and efficient operation of the all-in-one machine in a user intranet environment is achieved, and the difficulty and cost of building and maintaining a complex system by a unit are reduced.

The invention discloses a file security level checking method, device, equipment, medium and product based on an API HOOK of a windows operating system, and relates to the field of computer software application, the method comprises the steps that a callback function is registered by utilizing a driving module, when the windows operating system creates a process, a created process ID is sent to a service module in a user mode in the callback function, and when the process is created, the service module in the user mode is used for checking the security level of the file; receiving a service completion message of the service module; in the service module, based on a dll injection mechanism, injecting a dll injection program of the API HOOK module into the memory space of the created process; after the dll injection program is injected, an API HOOK module is utilized to modify an entry address of a target process API, and the entry address points to a self-defined hook function; the target process is the created process; and when the application opens the file corresponding to the target process, calling the security level judgment logic of the hook function, and judging whether the user security level can open the file corresponding to the target process, thereby avoiding the problem of high-density file leakage.

The invention provides an aerospace application knowledge graph construction method, device, system and equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-modal data; based on the data types, data processing is carried out on the modal data, and lightweight markup language texts and embedded vectors are obtained; performing knowledge extraction on the lightweight markup language text on the basis of a preset cue word and a large language model to obtain metadata information, and constructing an entity relationship triple on the basis of a relationship between entities and the metadata information; and based on the aerospace knowledge file number information, determining an association relationship among the aerospace knowledge file, the lightweight markup language text, the embedded vector and the entity relationship triple, and constructing the aerospace application knowledge graph according to the association relationship and the entity relationship triple. According to the space application knowledge graph constructed by the method, the space application field entities and the association relationship can be accurately presented, and efficient and accurate knowledge support is provided for space application knowledge questions and answers.

The invention provides a trusted data space platform and a fusion base thereof, in one embodiment of the trusted data space platform, a system architecture comprises a fusion base layer, a capability supporting layer, an application service layer and a global monitoring layer from bottom to top; the fusion base layer is a base support of a trusted data space, internalizes a space-time code and a digital network into a bottom layer protocol rule, and externally embodies a function service related to a right root; the capability supporting layer is used for forming basic capability of the trusted data space platform with the fusion base layer and directly carrying out interactive activities facing a user, the interactive activities are triggered by a data connector on a user side, and the data connector serves as an engine of the trusted data space platform; the application service layer provides data service for each application field; and the global monitoring layer is used for realizing global credible and controllable monitoring and analysis. Clear data ownership and credible data circulation are guaranteed from a global level, and large-scale circulation of data elements is supported.

The invention discloses an engineering safety video generation method and system based on a generative large model. The method comprises the following steps of obtaining an application field and a theme requirement of a required engineering safety video; on the basis of application fields and theme requirements, a retrieval enhancement generation mechanism is adopted to retrieve in the multi-modal knowledge base to obtain related data, and a large language model is utilized to generate a training script copywriting; extracting cue words from the training script copywriting, and based on the cue words, generating a corresponding image by using a diffusion model; and converting the training script copywriting into an explanation audio, and finally synthesizing a virtual explanation video with synchronous mouth shapes by an audio driving model. The method can be suitable for a plurality of engineering scenes such as buildings, mining industry, tunnels, high-altitude operation and the like, has the characteristics of process automation, high content specialty, high generation efficiency and high cross-scene adaptability, and effectively improves the production efficiency and training effect of engineering safety education videos.

The invention discloses a voice-driven virtual scene generation and switching method and an implementation system, which are applied to meta universe VR (virtual reality) glasses equipment, and comprise the steps of recognizing an instruction of a user through voice recognition and natural language processing technologies, generating or switching a virtual scene in real time, and realizing personalized scene creation and object generation. The edge computing node is adopted to process a high-calculation-amount task, the delay of scene generation and switching is remarkably reduced, the data transmission efficiency is improved by dynamically selecting the optimal node, the privacy security of a user is guaranteed, and through frame rate smooth adjustment and a scene fade-out mechanism, the experience of the user for exiting the virtual scene is optimized, the dizziness is reduced, and the user experience is improved. And the interaction fluency and comfort are improved. The method has the characteristics of quick response, convenient operation and strong privacy protection, and is widely applied to the virtual reality application fields of games, education, medical treatment and the like.

The invention provides an information acquisition method and device and electronic equipment, and relates to the technical field of artificial intelligence, in particular to the application fields of large language models, generative search, search engines, information retrieval, knowledge questions and answers, intelligent document editing, intelligent assistants, virtual humans and the like. According to the specific implementation scheme, the method comprises the steps of obtaining prompt word content subjected to enhancement processing; wherein the cue word content comprises a fixed prefix, a retrieval result and a variable suffix; obtaining a plurality of information block subsets based on N retrieval information blocks included in the retrieval result; selecting a target subset from the plurality of information block subsets according to the sequence of the number of the included retrieval information blocks from large to small; under the condition that it is determined that first key value information matched with target data obtained based on the fixed prefix and the target subset exists in the key value cache library, reply information for the cue word content is obtained based on the first key value information and the variable suffix; wherein the target data is obtained based on the fixed prefix and the target subset.