2499 results about "Interaction interface" patented technology

A system is provided for managing specialized tasks and information retrieval processes. Agents are configured to perform tasks and / or retrieve information in a specialized domain. The system receives, via an interaction interface, a message from a user for the trained generative model to generate an output, generates a context of the message, generates a request including the context and the message, executes an orchestrator configured to: receive the request, determine, using semantic decision making, one or more agents to handle the request, input the request into one or more agents to perform a task and / or retrieve information in specialized domains, generate a prompt based on the retrieved information and / or the performed task and the message from the user, provide the prompt to the trained generative model, receive, in response to the prompt, a response from the trained generative model, and output the response to the user.

The invention discloses an intelligent inspection method for fusion of Internet of Things and virtual reality based on an AI large model, particularly relates to the technical field of industrial intelligent inspection, and is used for solving the problem of end-to-end response lag caused by multi-modal data fusion delay and resource competition under an existing layered architecture. The method comprises the following steps: synchronously acquiring heterogeneous data of target equipment through a multi-source sensor and visual equipment, and generating time-space synchronous data through cross-modal feature extraction and time-space alignment; computing resources are dynamically allocated to an AI model or a rendering pipeline in combination with cross-modal correlation analysis and environmental interference assessment, and key tasks are preferentially guaranteed to be executed; performing deep correlation reasoning on the multi-modal data by using an AI large model, and generating equipment state features and an abnormal region mask; and finally, superposing the abnormal features and the three-dimensional scene through a virtual-real fusion rendering technology to form a visual interaction interface. Efficient fusion and real-time interaction of multi-modal data are realized, and the accuracy of anomaly detection and the decision response efficiency of an operator are remarkably improved.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

The invention discloses a text classification method, device and system based on a large language model, a storage medium and a product, and relates to the technical field of text classification, the method comprises the following steps: receiving a to-be-classified text and a classification label input or selected by a user through a user interaction interface of the text classification system; and according to the to-be-classified text and the classification label, constructing prompt words, and calling a pre-trained large language model to perform different-level classification on the to-be-classified text to generate a classification result. According to the technical scheme, the low-cost and low-use-threshold text classification method is provided based on the large language model, classification of different levels can be achieved, in addition, due to the fact that the text classification result is in a light-weight and convenient-to-analyze JSON format, the system can visually display the classification result to a user and can also provide an interface for a third-party application to call, and the user experience is improved. And the application scene of text classification is expanded.

The invention discloses a medical and educational informatization comprehensive supervision and diagnosis platform system based on multi-modal data fusion. A data acquisition module acquires multi-modal data from a medical and educational information system and preprocesses the multi-modal data; the data storage module constructs a hybrid architecture to classify and store data and establishes an index. The multi-modal data fusion module deeply fuses medical records, images and physiological monitoring data of medical treatment and teaching resources, learning behaviors and teaching evaluation data features of education by means of a feature extraction technology and a fusion algorithm. The supervision and diagnosis module constructs models of medical service quality evaluation, disease diagnosis assistance, teaching quality monitoring and the like based on fusion features to realize accurate analysis. The user interaction module provides interaction interfaces for different roles and supports operations such as data query and uploading. The platform system breaks the data barrier, fully mines the data value, provides powerful support for informatization management, decision making and service optimization in the medical and education fields, and promotes the innovative development of the two fields.

The invention provides a bank financial management product recommendation method and system, and the method comprises the steps: firstly collecting a multi-modal dialogue data flow which is generated by interaction of a user terminal and an intelligent customer service system and contains voice input signals and text input contents, and then carrying out the semantic recognition of the voice input signals, and generating a structured demand description set; performing entity extraction and intention analysis on text input content to generate a multi-dimensional semantic tag set, performing time-space alignment and fusion on the text input content and the multi-dimensional semantic tag set to form a user portrait enhanced feature matrix, and performing multi-level association analysis on the user portrait enhanced feature matrix and a financial product knowledge graph based on a deep matching model to generate an initial recommendation result queue; and finally, according to the real-time environment perception data, queue context perception optimization is carried out, a dynamic adaptive recommendation list is generated, and visual rendering output is carried out through a multi-channel interaction interface, so that accurate and dynamic financial management product recommendation is realized by utilizing multi-modal data, deep analysis and combination with a real-time environment.

A method for facilitating conversational interaction with users to help the users includes transmitting a conversational interaction interface for conversationally interacting with a user to a user device, receiving a request of the user through the conversational interaction interface from the user device, identifying an information based on the request, generating an input comprising the request and the information for a machine learning model based on the request and the information, processing the input using the machine learning model, generating a response for the request based on the processing of the input, transmitting the response through the conversational interaction interface for conversationally interacting with the user to the user device, and storing the machine learning model, the request, and the response.

The invention provides a network security and data security comprehensive analysis method and system based on a large model, and the method comprises the steps: collecting multi-source heterogeneous security data of a network communication link, a data storage node and an application interaction interface, carrying out the risk behavior atomization association processing, and constructing a dynamic risk association hypergraph; based on a preset security domain knowledge graph, calling the large model to execute multiple rounds of risk attribution reasoning, performing attack chain fragment matching and evidence chain completion on a behavior hyperedge set in the dynamic risk association hypergraph, and generating a risk attribution reasoning chain; and constructing a risk evolution probability model according to the risk attribution reasoning chain and the time sequence constraint set of the dynamic risk association hypergraph, and calculating a short-term diffusion probability and a long-term evolution trend vector of each association risk path based on the risk evolution probability model to obtain a risk evolution path prediction result. The pertinence and the dynamic adaptability of protection measures can be improved, and the problem that a static protection strategy is difficult to deal with the hysteresis quality of dynamic risk changes is solved.

The invention discloses a 500kV standardized switching operation method based on a VR virtual reality technology, and aims to solve the problems of unreal environment, incomplete evaluation and low efficiency in the switching operation training of an existing 500kV transformer substation. The method comprises the following steps: constructing a full-immersive virtual reality scene, collecting actual environment data of a transformer substation, and constructing and optimizing a high-precision model; designing multi-modal interaction of the standardized switching operation process, wherein the multi-modal interaction comprises visual guidance, a multi-modal interaction interface and an intelligent sensing function; dynamic action scoring and intelligent behavior evaluation are realized, actions are captured in real time by using high-precision action capture equipment, an instant score is generated by comparing with a standard, and dynamic feedback is provided; and real-time optimization and learning migration of the virtual character model are realized, user operation habits are captured, virtual character actions are optimized, and multi-scene migration and adaptation are realized. The method is suitable for VR-based 500kV standardized switching operation work, and the training authenticity and efficiency are improved.

The invention discloses an interactive simulation method for calculating aging parameters of a superconducting cable and a superconducting cable system.The system comprises the steps that a cable body electromagnetic transient model, a cooling system transient thermal model and a three-dimensional multi-field finite element model are built, and cable material characteristics, environment parameters and operation condition data are input; a model interaction interface is constructed through a simulation platform, data interaction and coupling among multiple models are realized, simulation parameters are dynamically adjusted, accurate matching of model step length and dynamic characteristics of the system is ensured, and aging parameters of the superconducting cable system under complex working conditions are calculated. According to the method, the operation state of the superconducting cable is evaluated by analyzing the mixed data, aging analysis of the superconducting cable system under multiple working conditions is carried out, and decision support is provided for system maintenance.

The invention discloses a smart home control system and method based on a graph attention network, and belongs to the technical field of smart home. The method comprises the steps that S10, multi-source data from a smart home system are collected, and real-time data are collected through a plurality of sensors and a user interaction interface; s20, constructing a graph structure model by using the multi-source data; s30, calculating a correlation weight between the nodes by using an attention mechanism, and generating an optimized equipment control strategy; s40, generating an equipment control instruction according to an output result of the graph attention network; s50, based on user operation feedback, continuously adjusting and optimizing the graph attention network model through a self-supervised learning mechanism; and S60, continuously monitoring the environment parameters and the equipment state, and updating the equipment control strategy in real time. The method has the beneficial effects that efficient fusion of multi-source data, intelligent coordination of user preferences, function coordination of equipment and self-adaptive adjustment of users and environments can be realized.

Disclosed herein are methods and systems to evaluate cost values for different radiotherapy treatment plans using external AI models. A method comprises presenting a user interface providing an interaction interface between a plurality of medical professionals communicating regarding a radiation therapy treatment of a patient during a tumor board meeting or a radiotherapy treatment planning process; receiving, from the interaction interface, a first input comprising a first patient attribute of the patient and a second input corresponding to the radiation therapy treatment of the patient; executing a machine learning language processing model using the first input and the second input to predict a task associated with generating a treatment plan for the patient; receiving, from the interaction interface, a third input; and when the third input does not correspond to the predicted task, presenting an indication of the predicted task.

The invention discloses an intelligent interactive Agent system based on Langchain and an implementation method, and relates to the technical field of natural language processing and artificial intelligence. Comprising the steps of 1, establishing an intelligent interactive Agent system by using an interface and an integrated tool provided by a Langchain framework, 2, managing calling of various tool modules and services through a central scheduling module, and dynamically registering and unbinding the tool modules by using the interface provided by the Langchain framework, and 3, processing user input by using a large language model through a process management module, and establishing an intelligent interactive Agent system. 4, a series of tool modules are integrated through the integrated tool management module, the tool modules comprise a text search tool, a weather query tool and a video information acquisition tool, each tool module works independently or is in linkage with other tool modules, and the tool modules are connected with the integrated tool management module. And 5, managing a user interaction interface through a front-end management module, supporting a user to query and control in a natural language, displaying a processing progress and a processing result in real time, and providing feedback and help information.

The invention discloses a fault diagnosis method and system for a coil cutting all-in-one machine based on a large language model, and relates to the technical field of equipment fault diagnosis, and the system comprises a table data intelligent processing module, a knowledge base construction module, a diagnosis reasoning module and a user interaction module. The table data intelligent processing module is used for carrying out automatic fault mode labeling and description standardization on a cutting and rolling all-in-one machine fault diagnosis case library provided by a user; the domain knowledge graph construction module is used for integrating the standardized table database and automatically constructing a domain knowledge graph; the diagnosis reasoning module is used for performing fault diagnosis reasoning based on a large language model and a knowledge graph; and the user interaction module provides a multi-modal user interaction interface and supports visual display of fault diagnosis. Therefore, by adopting the fault diagnosis method and system for the cutting and winding all-in-one machine based on the large language model, the intelligent level of fault diagnosis can be improved, the knowledge base construction and expansion cost can be reduced, and the usability and maintainability of the system can be enhanced.

The invention discloses a bridge management and maintenance decision-making system and method based on multi-agent collaborative optimization, and the system comprises a monitoring agent which is deployed in a cloud server and is used for obtaining abnormal data in a bridge structure and environment data; the diagnosis agent is used for evaluating the health state of the bridge by utilizing a built-in knowledge base, a built-in machine learning model and a built-in physical model based on the abnormal data; the decision-making agent is used for generating a plurality of candidate maintenance schemes based on an evaluation result, and screening out an optimal scheme by integrating the comprehensive utility of each scheme and the resource matching degree score of the resource scheduling agent on each scheme; the resource scheduling agent generates a construction plan according to the optimal scheme; the coordination / communication agent is used for ensuring efficient cooperation among the agents through a communication protocol and a negotiation mechanism among the agents; the diagnosis report, the optimal scheme and the construction plan are integrated and presented to a bridge manager through a human-computer interaction interface; and collaborative optimization of bridge management and maintenance decisions is realized through continuous feedback and self-learning.

The invention provides a design method and system of a touch interaction interface. Wherein user behavior habits are collected, key elements are extracted, a user participation degree evaluation system is constructed, and a behavior habit analysis report is generated; carrying out situation modeling processing by using a situation awareness layout optimization algorithm, carrying out adaptability analysis by adopting an environment adaptation technology, and generating environment adaptation interface configuration; a long-term preference tracking algorithm is used to record and learn personalized preference settings to add personalized components, a progressive interface evolution method is used to carry out progressive evolution processing, an interactive feedback mechanism is introduced step by step, an interactive module is added, and an optimized layout scheme is generated; and constructing a learning library according to the user behavior habits, importing interaction behavior data to perform behavior pre-judgment, adjusting interface elements and a response mode, and generating a touch interaction interface optimization strategy. According to the technical scheme provided by the invention, the man-machine interaction fluency and the user experience of the touch interaction interface are improved.

According to the student personalized learning path generation method based on the neural network, a data acquisition module is deployed on a teaching platform, a learning terminal and an interactive interface, and multi-dimensional data such as student learning duration, interactive frequency and wrong question records are acquired in real time. A knowledge graph is constructed based on a course outline and a prior textbook structure, and a graph neural network GNN is utilized to dynamically adjust association weights of nodes and edges of the graph neural network GNN to reflect weak knowledge areas of students. A Bi-LSTM encoder is constructed for the collected data to generate a behavior feature vector, and the behavior feature vector and a knowledge graph node embedded vector are aligned and fused through an attention mechanism to obtain student personalized multi-modal representation. And taking the representation and the knowledge graph node weight as an environment state, selecting a next knowledge point to be learned as an action space, designing a reward function by integrating multiple indexes, updating a target by using a deep Q network, and training a strategy network to generate a personalized learning path. The trained strategy is deployed as micro-service, a path is displayed according to knowledge module sorting, and related parameters are iteratively updated according to student feedback to improve the recommendation effect.

The invention relates to an intelligent CNC (computer numerical control) machining method which comprises the following steps: dynamically monitoring a tool-workpiece interaction interface in a CNC machining process through a multi-dimensional torque sensor array to obtain a machining process feature data set, and analyzing a tool motion track in real time to obtain a tool motion state feature quantity; secondly, performing multi-scale analysis by adopting a wavelet packet decomposition technology, and determining processing quality evaluation data; and if the data does not reach the preset standard, performing microstructure reconstruction on the surface of the workpiece based on the data, and generating a workpiece processing state characteristic spectrum. Then, comprehensively analyzing the atlas by utilizing a multi-objective optimization technology to obtain a processing parameter optimization sequence; and finally, implementing closed-loop feedback control on the numerical control system according to the optimized sequence, and generating a real-time processing control instruction. The key problem of how to improve the automation level and the machining precision in the CNC machining process through an intelligent means is solved.

The invention provides a content generation method and device, a computing device, a medium, a system and a program product. The content generation method comprises the following steps: displaying a user interaction interface, wherein the user interaction interface comprises a canvas area; providing at least one element box in the canvas area; receiving first user intention information input in the first element box by a user; in response to a running operation of a user for the first element box, acquiring a first content material according to the first user intention information by utilizing a preset intelligent agent corresponding to the first user intention information; and generating target content according to the first content material. According to the content generation method and device, the computing device, the medium and the system disclosed by the invention, the problem that the content generation requirements of some complex scenes cannot be met due to single-line dialogue between the user and the intelligent agent is solved, and the interactivity between the user and the intelligent agent can be improved so as to meet the requirements of more application scenes.

The embodiment of the invention discloses a terminal application behavior data analysis method and computer equipment, and the method comprises the steps: obtaining an interaction behavior data set of an RPA terminal application in a preset time window, the interaction behavior data set comprising a plurality of interaction behavior sequences, each interactive behavior sequence comprises at least one user interface operation event and a corresponding system response event; performing behavior track analysis processing on the interactive behavior data set, and extracting an interface circulation feature and an operation intention feature of each interactive behavior sequence; generating an interface optimization strategy according to the relevance between the interface circulation feature and the operation intention feature, wherein the interface optimization strategy comprises an interface layout adjustment rule and an interface response logic optimization rule; and feeding back the interface optimization strategy to a background management system of the RPA terminal application. Therefore, the problem that an existing RPA application interaction interface is insufficient in design and optimization can be effectively solved, and the usability of the interface and the response capability of the system are improved.

The invention discloses a multi-agent training method and system fusing a knowledge graph. The system comprises a knowledge graph management module, an agent training module and an interaction and feedback module. And the knowledge graph management module is responsible for organizing, updating and the like of the knowledge graph and covers data acquisition, cleaning, storage, construction, updating, query, reasoning and feedback collection. The agent training module comprises an environment simulator, a plurality of learning modules, a knowledge graph interaction module, a strategy generation module and a feedback mechanism, and helps an agent to learn and optimize a decision strategy in a simulation environment. The interaction and feedback module is provided with an interaction interface, a feedback calculation module, a knowledge graph association module and a performance monitoring and visualization module, and is used for realizing communication and performance evaluation between the intelligent agent and the environment; and the interaction and feedback module realizes environment interaction, feedback calculation, knowledge graph association and performance monitoring evaluation and adjustment.

A computing system is provided, including processing circuitry configured to cause an interaction interface for a trained generative model to be presented, in which the interaction interface is configured to communicate a portion of a user interaction history. The processing circuitry is further configured to receive, via the interaction interface, an input for the trained generative model to generate an output. The processing circuitry is further configured to send a command to create, via the trained generative model or another trained generative model, a whiteboard based on the user interaction history and receive the created whiteboard. The processing circuitry is further configured to generate a prompt based on the whiteboard and the instruction from the user and provide the prompt to the trained generative model. The processing circuitry is further configured to receive a response from the trained generative model and output the response via the interaction interface.

The invention provides an electric power tower state real-time monitoring and common fault identification system based on a digital twinborn technology. According to the system, a high-precision digital twinborn model module is constructed, and a sensor network module is integrated so as to acquire key data of a tower in real time. The data processing center module utilizes an advanced clock synchronization technology to ensure data precision, cooperates with the common fault identification system module and the health state evaluation module, and adopts finite element analysis and Paris laws to accurately evaluate the health condition of the tower. The system further comprises an intelligent maintenance decision support module which provides a scientific maintenance strategy. In addition, the data visualization platform module and the user interaction interface module enhance the user experience, so that the system is not limited to monitoring and evaluation, and optimization of maintenance decision and individuation of user interaction are also realized. The overall system design pays attention to real-time performance, accuracy and intelligence, and aims at improving the operation and maintenance efficiency and safety of the electric power tower.

The invention provides an intelligent e-commerce behavior event decision-making method and system fusing multi-source perception, and the method comprises the steps: obtaining a user behavior data set, a commodity attribute data set and an environment context data set through a preset data collection interface, and carrying out the intention recognition processing of multi-source data; generating an intention feature set containing preliminary intention features and refined intention features, then generating an interactive guidance strategy tree containing node branch weights and strategy execution priorities based on the intention feature set, and performing dynamic path adjustment processing on the interactive guidance strategy tree according to a real-time feedback data set to obtain an optimized strategy tree set; and finally, pushing the optimization strategy tree set to a target interaction interface to activate an interaction guide operation, thereby providing personalized and intelligent interaction guide for the user by fusing multi-source sensing data, deeply understanding the intention of the user and dynamically adjusting a decision strategy, and improving the operation efficiency of an e-commerce platform and the satisfaction of the user.

The invention provides a table data processing method which can be applied to the field of artificial intelligence. The table data processing method comprises the steps that table data input by an object through an interactive interface and an associated processing request are input into a preset model, a tool calling demand corresponding to the processing request is generated, and the tool calling demand is sent to a task processing engine; tool information returned by the task processing engine is input into a preset model, multiple target tools are obtained, and the multiple target tools comprise a reading tool and a processing tool; under the condition that it is determined that the task processing engine completes table data reading through the reading tool, a reading result and function information of the processing tool are input into a preset model, a processing task corresponding to the processing request is obtained, and the processing task is sent to the task processing engine; and in response to the received execution result from the task processing engine, displaying the execution result on the interactive interface. The invention further provides electronic equipment, a storage medium and a program product.

The invention relates to the technical field of booster station monitoring systems, and discloses a booster station operation and maintenance work video auxiliary monitoring system comprising a three-dimensional perception interaction layer used for collecting equipment state data and providing a man-machine interaction interface and connected with an edge intelligent fusion layer through a wired or wireless transmission channel; and the edge intelligent fusion layer is used for locally analyzing and caching the state data. Through standardized interface interconnection of the three-dimensional perception interaction layer, the edge intelligent fusion layer and the cloud collaborative management layer, a collaborative working mode of data acquisition, local analysis and cloud optimization is formed, the architecture design breaks through the dependence of a traditional scheme on cloud centralized processing, data preprocessing sinks to the edge layer, the network transmission pressure is effectively reduced, and the network performance is improved. The local intelligent analysis capability can still be maintained when the network fluctuates, and compared with the delay problem caused by full data uploading in the prior art, the system response real-time performance and the availability under the network disconnection scene are remarkably improved.

The invention provides a VR scene adaptive rendering method based on AI and multi-modal perceptual interaction, and the method comprises the steps: firstly obtaining a perceptual signal set of a current interaction stage of a user through a multi-modal interaction interface, including user interaction actions, visual attention and scene physical feedback signals, and then analyzing the set to obtain a sensing signal set of the current interaction stage of the user; the method comprises the following steps: generating user concerned area features and scene dynamic sensitive area features, then determining a rendering area priority sequence and a detail retention reference through a rendering resource allocation model based on the user concerned area features and the scene dynamic sensitive area features, and adjusting a resource scheduling rule and a quality control rule of a VR rendering system according to the result. And executing the adjusted rule to generate the current frame of rendering picture, and updating the decision logic of the rendering resource allocation model according to the change trend of the interactive feedback of the user to the current frame of picture and the physical feedback of the scene, thereby realizing the dynamic self-adaption of VR scene rendering, improving the rendering efficiency and quality, and enhancing the user immersion.

The invention discloses an automatic control etching system and method for a printed circuit board, and relates to the technical field of circuit boards, and the method comprises the following steps: 1, an operator puts a to-be-etched PCB into an etching groove, and inputs target etching parameters through a human-computer interaction interface; 2, the multi-dimensional sensor module continuously monitors key parameters in the etching tank, and data is transmitted to the central controller; 3, according to the data provided by the sensor, the central controller calculates a real-time etching rate by using a nonlinear kinetic model; 4, when the real-time etching rate deviates from the target rate, the system starts an adaptive control algorithm for adjustment; 5, when the system detects that the set etching depth or width reaches a target value, the etching process is automatically stopped, and key data are recorded; and step 6, the system analyzes based on the stored historical data, provides optimal etching parameters and adjustment strategies for different types of PCBs, and displays the data in real time through a human-computer interaction interface module.

The invention discloses a tourism service agent system and method based on a multi-modal large model. The system comprises five parts: a user interaction interface, which is used for receiving a user request and returning a response; the agent center is used for performing intention understanding, task planning and response generation through a multi-modal large language model; and the tool calling module is used for executing specific API business operation. According to the intelligent tourism service system, the work of each module is coordinated through the intelligent agent center, a complete closed loop from user intention understanding to service execution is realized, accurate, reliable, whole-course and personalized intelligent tourism service can be provided, and the problems that a traditional tourism service system is single in function, inaccurate in information and lack of action ability are effectively solved.

The invention is suitable for the technical field of data processing, and provides a three-dimensional scene data loading and displaying method and electronic equipment. The method comprises the steps that to-be-processed three-dimensional scene data is spatially divided into data blocks of a plurality of precision levels, the number of the data blocks of each precision level is multiple, and all the data blocks can be independently stored and loaded; establishing a spatial index structure of all data blocks by adopting a spatial index technology; obtaining an operation applied to the interactive interface of the user side by a user, and determining a view range and a zoom level of the three-dimensional scene data needing to be loaded in the interactive interface according to the operation; and determining a target data block according to the zoom level, the view range and the spatial index structure, and sending the target data block to a user side for loading and displaying. According to the method, the data access and loading efficiency can be improved, the loading delay is reduced, and real-time rendering is ensured.