683 results about "User friendliness" patented technology

The invention relates to the technical field of process automation, in particular to an RPA service automation method capable of enabling a large language model MCP. The method comprises the following steps: acquiring user input data, and performing intention understanding through a multi-round intention recognition model according to the user input data to obtain semantic instruction data; performing standard semantic protocol conversion according to the semantic instruction data to obtain standard semantic protocol data; performing flow chart node matching according to the standard semantic protocol data to obtain flow chart node data; and generating a business process according to the flow chart node data to obtain business process data. According to the method, the multi-round intention recognition capability of the large language model and the standard semantic protocol conversion are fused, so that the accurate mapping from the natural language to the business process is realized, and the intelligent level and the user friendliness of the RPA system are improved. Through process node matching and process logic verification, the execution effectiveness of the automatic generation process is ensured, and the labor cost and configuration errors are reduced.

The invention discloses a sugarcane yield prediction method and system based on machine learning, and relates to the technical field of intelligent agriculture. Through comprehensive application of technical means of data acquisition, preprocessing, feature extraction, model construction, training, prediction, decision support and the like, accurate prediction of the sugarcane yield is realized. According to the method, multi-source data is combined, key features are extracted by using an advanced machine learning algorithm, and a high-performance prediction model is constructed. Through historical data training and model parameter optimization, prediction accuracy and stability are improved. Meanwhile, the system provides a user-friendly interactive interface, and collects user feedback to continuously improve the model. The method is suitable for the field of agriculture, especially for sugarcane yield prediction, solves the problem that traditional methods such as experience estimation and statistical model prediction are inaccurate, realizes high-precision prediction through technologies such as machine learning, and has important significance for promoting agricultural sustainable development.

The invention discloses a digital intelligent service system for enterprise services, which belongs to the field of enterprise digital services and comprises a user demand analysis module, an intelligent data adaptation module, a service resource matching module, a service efficiency evaluation module and a user-friendly interface. The user demand analysis module is used for semantic analysis and classification decision making; the intelligent data adaptation module identifies and analyzes the protocol type, and establishes an intelligent data transmission channel; the service resource matching module carries out resource pre-screening and accurate matching; the service efficiency evaluation module tracks an identifier and captures a four-dimensional index system in real time, and the dynamic evaluation unit realizes service state grading early warning through a sliding window algorithm; according to the invention, accurate demand identification is realized, the response speed and the data transmission efficiency are improved, the user satisfaction is improved, the service matching accuracy is enhanced, the resource utilization efficiency is optimized, the service capability and the customer experience are improved, and maximization of economic benefits and social values is realized.

The invention relates to the field of legal service management, and discloses a legal service management system based on a block chain, and the system comprises the following modules: a block chain network, an intelligent contract module, a data storage module, a user interface module, a feedback and monitoring module and a user management module, the non-tampering property and the transparency are ensured; the intelligent contract module automatically executes contract terms and supports intelligent management; the data storage module adopts a hierarchical structure, and on-chain data and off-chain data are stored in a distinguished manner, so that the storage and access efficiency is optimized; and the user interface module provides user-friendly operation experience through a visual tool. By using the block chain technology, all contract execution and compliance audit data are encrypted and stored in a distributed mode, it is ensured that tampering is avoided and whole-course traceability is achieved, and a user and related mechanisms can verify the authenticity and integrity of the contract data at any time.

The invention relates to the field of financial risk management, and discloses a financial panoramic risk management and control system, the system integrates a data layer, a machine learning layer, an application layer and an interaction layer, and aims to provide comprehensive and efficient risk management for enterprises, the data layer is responsible for collection, preprocessing and storage of multi-dimensional financial data, and the machine learning layer is responsible for interaction with the interaction layer. The machine learning layer trains a fund chain and supply chain risk prediction model by using the data to realize scientific risk assessment, the application layer performs real-time risk analysis and early warning to ensure that an enterprise timely deals with potential risks, and the interaction layer provides a user-friendly interface and strict authority management to ensure data security and convenient operation, so that the system has a wide application prospect. The system not only improves the efficiency and accuracy of risk management and control, but also strengthens the ability of an enterprise to control panoramic financial risks, effectively prevents omission and misjudgment, and assists the enterprise to stably operate in a complex and changeable market environment.

The invention discloses a remote sensing question answering system based on a comparison-generation type pre-training model, which comprises the following steps of: firstly, collecting remote sensing images of tasks such as classification, semantic segmentation, target detection, image-text retrieval and image text generation as original data, and uniformly converting the original data into an image-text pair form; the category area proportion is calculated through segmentation processing, a target category and position information thereof are detected, and zero sample classification is performed through a CLIP model. Thirdly, inputting multi-source information into a multi-modal large language model, generating text description of an image according to a question, and completing construction of a remote sensing global visual question and answer data set; and meanwhile, based on the annotation box, cutting the picture and sending the picture into a multi-modal large language model to obtain a remote sensing local visual question and answer data set. Then, pre-training the comparison-generation type model from a coarse stage to a fine stage, so that the comparison-generation type model has global-local level remote sensing knowledge and visual question and answer ability; and finally, realizing question and answer interaction with the user by constructing a user-friendly system interface.

The invention discloses a high-order precision flood simulation method based on GPU acceleration, and relates to application of a parallel computing technology utilizing a graphic processing unit and a high-order precision numerical discretization method in flood simulation. A WENO reconstruction technology, an implicit time discretization scheme, depth average model innovation, a GPU parallel computing strategy, a terrain adaptability algorithm, a dynamic source item processing mechanism and a multi-source item coupling simulation technology are combined; simulation efficiency can be remarkably improved while high calculation precision is kept, and the method is particularly suitable for flood simulation under complex terrain conditions; through strict model verification and calibration processes and user-friendly software implementation, the accuracy and reliability of the method in practical application are ensured, the limitation of an existing flood simulation technology under large-scale and complex terrain conditions is effectively solved, and the high-order precision flood simulation method based on GPU acceleration is introduced, so that the high-order precision flood simulation method has a good application prospect. The simulation precision and efficiency are remarkably improved, and the dynamic process of the flood event is effectively predicted and analyzed.

The invention discloses an intelligent SQL (Structured Query Language) generation method and system based on multistage intention recognition. The method comprises the following steps: receiving a natural language query of a user; vector matching: carrying out vector matching based on a knowledge base to obtain Top-K candidate query objects, the knowledge base containing multilayer structure description information; a large language model intention understanding step: determining a final query object in combination with the candidate query object description; loading a branch workflow, analyzing a field and a table structure, and dynamically configuring a database table and field information; sQL generation: generating SQL statements conforming to grammatical rules, including automatic field addition, time condition conversion and field priority matching operation; and executing the SQL statement and returning a result, and if the result fails, recording a log to prompt correction. By combining a natural language processing technology with a database knowledge base, an efficient, accurate and user-friendly database query solution is provided.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a large model voice question and answer method based on historical dialogue information, which comprises the following specific steps: selecting a large language model GPT for pre-training; taking the historical dialogue information of the user as a current state; learning by using a deep Q network; setting a reward index based on the user satisfaction and the dialogue round; historical information is stored and utilized in combination with a long-term and short-term memory network; and guiding the updating of the large language model by using a DQN network. The method has the advantages that personalized response can be provided, the efficiency is improved, the user experience is enhanced, and high adaptability and accuracy are achieved; through the combined action of the characteristics, the overall performance of the voice question-answering system is remarkably improved, and the voice question-answering system is more effective and user-friendly in practical application.

The invention relates to the field of picture processing, and provides a method and device for generating a memory video and electronic equipment. And the electronic equipment displays a second display interface comprising a recall entrance area through a first operation of the user on the first picture, searches a picture matched with at least one character of the first picture through a second operation of the user on the recall entrance area, and finally generates a first recall video exclusive to the at least one character. Therefore, a condition for actively triggering the memory function is friendly to a user through the first display interface and the first operation, and a condition for generating the memory function is friendly to the user through the second display interface and the second operation; according to the embodiment of the invention, the user can execute the operation on the picture of the interested figure based on the own demand to generate the memory video, the actual demand of the user is met, and the user experience is better improved.

The invention discloses an RPA work order processing system, a system architecture and a work order processing method, and the system comprises a user interface subsystem which is used for collecting information inputted by a user; the work order generation and management subsystem is used for managing creation of the work order; the resource allocation and scheduling subsystem manages and allocates work orders through a process automation robot; the state monitoring and notification subsystem tracks a work order processing state through a process automation robot and notifies a related informing person when the state changes; the user feedback and data analysis subsystem is used for collecting user feedback information; the data analysis engine is used for extracting insights from the work order data according to statistics and machine learning technologies and providing support for management decision making; according to the method, the problem of low-efficiency workflow and user experience caused by the existing technical problems is solved, the workflow is optimized, high efficiency, transparency and user friendliness of the work order processing flow are realized, and meanwhile, the clear responsibility and the customizability of the flow are ensured.

The invention discloses a self-adaptive resource scheduling method for improving cluster reconstruction efficiency, and relates to the field of resource scheduling distribution, and the method comprises the steps: monitoring the resource use data of each node in a cluster in real time through a monitoring agent, and obtaining the health state of the node through a heartbeat mechanism; collecting input task requests, predicting the resource demand quantity of each task, and performing preliminary queue processing on the tasks to obtain a task queue group; setting a resource competition constraint according to the task queue group and the resource use data and the health state of each node, obtaining dynamic resource scheduling corresponding to each task by using an optimization algorithm, and allocating the tasks to each node; a resource scheduling dynamic graph is constructed, a visual interface is set, and the resource scheduling dynamic graph is arranged on the visual interface and used for displaying resource scheduling, providing a user-friendly interface and realizing high-efficiency scheduling of adaptive resources in a cluster reconstruction process.

The invention discloses an intelligent interactive thematic map generation system and method based on a large language model. Comprising a large language model module, a thematic map template library, an intelligent data source management module, an intelligent cartographic engine, an interactive optimization module, a user interaction configuration module, a configuration library, an external service interface module, a model data quality verification module, a thematic map personalized correction module and the like. A user interactively selects a template, specifies a data source and describes drawing requirements through a natural language, LLM drives an intelligent drawing engine to generate a thematic map, fine adjustment and real-time optimization of the user are supported, and user-friendly, efficient and flexible thematic map making is achieved. Meanwhile, the system has the functions of data quality verification, personalized configuration, interactive history learning and the like, a powerful tool is provided for non-professional users to quickly customize and finely adjust thematic maps, and the intelligent level and adaptability of thematic map making are greatly improved.

The present invention encompasses systems, computer program products, and methods for machine interpretation of security data. It identifies various data sources providing metrics and parameters, which include system logs, network traffic data, user activity records, and application logs. The system retrieves these metrics and parameters through an application programming interface and transforms them from unstructured to structured data. This structured data is then featured and stored. A dynamic consolidated matrix, known as the Constraint Specification Matrix (CSM), is generated from these features. A machine learning model is trained to discern correlations and patterns within the CSM's features. Lastly, the system transmits instructions to present these correlations and patterns via a user interface on a user device, allowing for user-friendly visualization and interpretation of the analyzed security data.

The invention provides an intelligent temperature control method for a heating kettle. The method comprises the steps that various sensors are integrated inside and outside the kettle to collect various data of the inside and the environment of the kettle in real time; constructing and training a hybrid deep learning model based on the combination of a convolutional neural network and a long-short-term memory network, and deploying the trained hybrid deep learning model into a control system of the kettle; carrying out data fusion and synchronization and real-time denoising, and carrying out real-time feature extraction on the denoised sensor data; dynamically adjusting heating power, and detecting water temperature abnormity; and a user-friendly interface design and a remote control function are designed. According to the intelligent temperature control kettle system combining deep learning, fuzzy logic control and sound wave sensing technologies, high-precision temperature control, intelligent analysis and personalized service are achieved through comprehensive application of multiple advanced technologies, and therefore the user experience is remarkably improved.

The invention presents an energy management system for power distribution networks. It features a hierarchical network with multi-level metering nodes, each measuring energy usage. Data from these nodes are transmitted via a secure communication gateway to a cloud-based platform, which includes servers for processing and storage. A key component is a machine learning algorithm within the server, designed to analyze energy data, normalize and transform inputs, and identify anomalies. The algorithm generates anomaly scores for each power meter, reflecting potential operational issues. A user interface, accessible through client devices, displays the processed data and anomaly scores. This allows users to effectively monitor and manage the energy distribution, making informed decisions for optimization. The system enhances the efficiency and reliability of power distribution, offering advanced analysis and user-friendly monitoring capabilities.

The embodiment of the invention provides an interaction method and device for multimedia content, a storage medium and a computer program product. The method comprises the steps of displaying a dialogue interface used for generating multimedia content in response to a trigger operation; in response to the received request for generating the multimedia content, displaying a multimedia content outline associated with the multimedia content to be generated in the dialogue interface; and displaying the generated multimedia content based on a multimedia generation instruction, where the multimedia generation instruction indicates confirmation of a multimedia content outline or confirmation of an edited multimedia content outline in the dialogue interface. According to the method disclosed by the embodiment of the invention, the multimedia content outline can be provided for the user before the multimedia content is generated, and the user can edit the multimedia content outline through the user-friendly interaction interface so as to obtain the multimedia content meeting the personalized requirement, and the user experience is further improved.

The invention relates to the technical field of mixed gas distribution, and discloses a carbon dioxide mixed gas configuration system and a control method thereof, and the carbon dioxide mixed gas configuration system comprises a gas storage tank, a high-precision intelligent sensor module, a control system module, a user interface and a mixing unit. The gas storage tank stores high-purity carbon dioxide and mixed gas, the mixing unit is a mixing chamber, the gas flow is accurately controlled through the flow control valve, and mixing in a preset formula proportion is achieved. By integrating a high-precision sensor, automatic control and a user-friendly operation interface, accurate proportioning, stability and high-efficiency preparation of mixed gas are realized. The system has the characteristic of high automation, and realizes accurate proportioning, stability and high-efficiency preparation of mixed gas through accurate control of gas flow, real-time monitoring and feedback adjustment and a user-friendly operation interface. Meanwhile, the system considers cost effectiveness, environmental protection requirements and safety, and a reliable mixed gas configuration solution is provided for enterprises.

The Energy Asset Financing marketplace is an innovative digital platform designed to bridge the investment gap in global energy funding and promote clean energy. The marketplace connects global investors and asset owners offering customized financial instruments and increasing access to finance. It utilizes advanced technologies like blockchain, AI, and data analytics to ensure innovation, seamless operations, and personalized user experiences. Asset owners submit funding proposals. The marketplace prioritizes financially viable assets through rigorous evaluation processes promoting sound investment opportunities. Investors can explore various investment opportunities and actively participate in financing energy assets aligned with their objectives. The platform offers a user-friendly interface, comprehensive information on financial instruments and energy assets, and supports secure transactions and multiple currencies. Tokenization technology allows for fractional ownership and trading of energy assets. Tokens also serve as a reward for sustainable practices. To summarize, the marketplace revolutionizes energy asset financing fostering a sustainable investment ecosystem.

The invention discloses a petroleum industry personnel behavior safety video monitoring system based on artificial intelligence, and the system comprises a front-end equipment layer which is used for collecting physical environment data; the edge computing layer is deployed on a local server of a factory and is used for preprocessing and preliminarily analyzing the data acquired by the front-end equipment layer; the cloud analysis layer is used for carrying out deep analysis on the data uploaded by the edge calculation layer by utilizing deep learning and natural language processing technologies; the cloud analysis layer can integrate data from the front-end equipment layer, the edge computing layer and the cloud analysis layer; and the application service layer is used for presenting the result of the cloud analysis layer to a user in a user-friendly manner. According to the method, video spatio-temporal features are extracted through the CNN-BiLSTM fusion model, risk behaviors such as no helmet wearing and illegal operation are accurately identified, and the false alarm rate is reduced; the NLP analyzes the work order to construct the knowledge graph, the knowledge graph is matched with the video behavior event in a space-time manner, the risk score is dynamically evaluated, and the comprehensive early warning accuracy is improved.

The invention presents an advanced soccer training system designed to revolutionize traditional practice methods through a synergy of technology and interactivity. It features an integration of sensors, Artificial Intelligence, and Augmented Reality technologies, providing real-time feedback, immersive simulations, and personalized training experiences. The system promotes skill development via data-driven insights and dynamic training environments, supported by mobile application connectivity for customized training regimens and performance analysis. Additional attributes include energy-efficient design, user-friendly transport mechanisms, and extensive multimedia capabilities like video recording and photo capture for skill review, establishing a novel paradigm in athletic training and development.

A vehicle safety alert system designed to monitor the interior of a vehicle and alert users about the presence of unattended individuals or pets, such as children or the elderly, left behind inside the vehicle is disclosed. The system includes a smart alert device which can be in a variety of portable forms including stuffed toys and is equipped with a plurality of sensors including an ignition sensor, a motion sensor, a temperature sensor, a sound sensor, and a camera to capture comprehensive visual data of the vehicle's interior. The device utilizes a processor to analyze sensor data and determine the presence of unattended individuals or pets, sending alerts to a user device through a communication network. Alerts can be audio, textual, or video messages, including real-time footage. The system includes a user-friendly application to configure alert preferences and emergency contacts, enhancing the system's utility and user convenience.

The invention provides a code generation method based on an artificial intelligence low-code system. The code generation method can be applied to the technical field of artificial intelligence. The method comprises the following steps: packaging a pre-trained artificial intelligence large model into an artificial intelligence model service to obtain a model application program interface; according to the model application program interface, deploying an artificial intelligence model service into a production environment; based on a production environment, integrating an artificial intelligence model service into a workflow engine of a low-code platform by utilizing a model application program interface so as to obtain an artificial intelligence low-code system; and automatically generating application program codes based on user application requirements by utilizing an artificial intelligence low-code system. According to the artificial intelligence low-code system, automatic decision support is provided, and a more intelligent, user-friendly, efficient and safe low-code application development platform is provided. The invention further provides a code generation device and equipment based on the artificial intelligence low-code system, a storage medium and a program product.

The invention provides a long-range visual question and answer and multi-modal reasoning task agent construction method. For input images and natural language questions, generating answers through orderly calling of an external tool set; the construction process of the intelligent agent is divided into three stages: a global planning stage: analyzing user requirements through a global planning navigator, and screening tool subsets; in the tool autonomous execution stage, visual details are supplemented, background knowledge is retrieved and accurate operation is carried out in the multi-step process by surrounding three types of tools through a tool autonomous executor, and a returned tool result is used for assisting the next step of decision making; in the response synthesis stage, the reasoning process is combed through a model response synthesizer, and user-friendly and clear-format responses are sorted; and finally, the model response synthesis module extracts and obtains answers from the reasoning track and outputs the answers. The problems of global planning insufficiency and visual context forgetting generally existing in complex task reasoning of an existing multi-mode large language model are solved.

The invention discloses a real-time process mining method based on data analysis, which belongs to the technical field of data analysis, and comprises the following steps: providing a user interface, allowing a user to configure input parameters of a data acquisition task, including a target website URL (Uniform Resource Locator) and an acquisition frequency; the data acquisition module is used for realizing pre-definition and comprises a webpage crawler module which is used for automatically accessing and capturing contents of a target website and pre-processing the contents; an API calling module is provided and used for obtaining data from a third-party service or a data provider; the database query supporting module is used for directly extracting data from a database and carrying out encryption transmission on the data; monitoring the state and performance of the data acquisition task in real time; when abnormity or performance reduction is detected, the system automatically triggers an alarm; according to the method, the technical threshold of process mining is remarkably reduced through a user-friendly interface.

According to the efficient labeling method, device and system for the large-scale point cloud data, the medium and the program product, the large-scale point cloud data can be efficiently processed through the octree segmentation and intelligent segmentation technology, and memory consumption is remarkably reduced; an efficient visualization module is utilized, the calculation and storage requirements of a client side are reduced, and a user can carry out point cloud labeling without high-performance hardware; in addition, various intelligent labeling tools are integrated, so that the labeling process is more user-friendly, efficient and accurate. Therefore, multiple defects in the prior art are overcome, an efficient, intelligent and resource-friendly point cloud labeling solution is provided, and a new solution is provided for large-scale point cloud data processing and labeling.

The invention provides a charging pile intelligent scheduling system and method, and the system comprises a user management module, a charging pile management module, a real-time monitoring module, an intelligent scheduling module, a data analysis and report module and a system management module, and has the technical characteristics of intelligent scheduling, real-time monitoring, user friendliness, data analysis and optimization and the like. By reasonably dispatching the charging piles, the utilization rate of the charging piles is improved, the waiting time of users is shortened, and intelligent distribution of the charging piles is performed according to user demands and prediction data. The charging piles are intelligently dispatched according to the user requirements and the real-time data, so that the maximum charging pile utilization rate and the maximum user satisfaction degree are achieved. The system analyzes and optimizes data such as user requirements and charging pile states, provides a reasonable charging pile scheduling scheme, can perform real-time adjustment according to data changes, and improves the flexibility and adaptability of the system.

The invention provides a development method and a development system of a finance and tax business demand generation system. The method comprises the steps of data integration and analysis, business logic abstraction and modeling, intelligent template generation engine, user-friendly interface and interactive design, automatic generation and verification, and continuous learning and optimization. Development of the finance and taxation business system is completed by using the method of the finance and taxation business demand generation system, an application interface and logic are rapidly established in a dragging mode through a preset component and a visual development interface, the development period is shortened, and rapid conversion of business demands is achieved; the interface style, the function module and the data processing logic are adjusted and optimized through simple operation; a unified development environment is provided, switching and adaptation work among different environments is reduced, and the error risk is reduced; the quality and the maintainability of the software are improved through a standardized development process and a component library; the development efficiency is improved, the labor cost is reduced, and the software development cost is saved.

The invention relates to the technical field of 3D development, and discloses a Three.js-based 3D scene low-code construction method and scene construction platform, and the method comprises the steps: a client obtains the operation information of a user, and sends the operation information to a server; the server side is used for mapping the operation information into the structured JSON Schema, updating the JSON Schema on the basis of the operation information, and carrying out persistent storage on the JSON Schema; and the server sends the JSON Schema corresponding to the preview request to the client, so that the client performs real-time rendering. According to the method provided by the embodiment of the invention, the graphical operation interface is provided, so that non-professionals can easily construct the 3D scene without mastering complex programming or graphical knowledge, and therefore, the user-friendly degree of the development process is improved, and the 3D scene construction difficulty is reduced.

This invention relates to systems and methods for real-time dynamic classification and orchestration of test automation components in distributed DevOps environments. The system features an Auto Identify Automation (AIA) engine that leverages supervised learning, Multi-Modal Artificial Intelligence (AI), and Generative AI technologies. It includes a Smart Scenario Designer interface that allows users to author test scenarios using handwriting and voice inputs, which are processed in real-time by AI-driven handwriting recognition, voice recognition, and Natural Language Processing (NLP). The system dynamically suggests relevant automated components via a smart bubble pane, facilitating rapid scenario creation. The architecture is tool-agnostic and scalable, with a Shared Workbench Engine that supports real-time collaboration and conflict resolution. The system continuously adapts and improves, ensuring that the automation suite remains consistent, up-to-date, and aligned with evolving software requirements, enabling efficient and user-friendly management of complex test automation processes.