16 results about "Research system" patented technology

The invention provides a financial research report generation method based on a large model. Comprising a data collection module, a data analysis module and a report writing module. The data collection module is used for receiving a predefined data collection task and an autonomously generated data collection task, then inputting the tasks into a deep search agent, and constructing a structured multi-modal memory for a search result for storage; the data analysis module constructs a data analysis agent, and realizes the generation of a structured multi-modal small report through cooperation of a financial calculation tool, a chart generation tool and a reference addition tool in an actor-reviewer iteration mode in which a large language model is matched with a visual language model; and the report writing module constructs a report writing agent to obtain a chapter first draft and then inputs the chapter first draft into the post-processing agent to obtain a final report. The problems that an existing deep research system and a large language model agent in the financial field are lack of financial field knowledge, limited in multi-modal ability, limited in research and report generation depth and comprehensiveness and the like are solved.

The application relates to the technical field of the cross of artificial intelligence and behavior science, in particular to a market research system based on multi-source data integration and psychological analysis, which comprises a processing module, an RAG module, a retrieval module, a summary module, an analysis module and a verification module; the processing module processes feedback data of market research; the RAG module retrieves to obtain multi-modal data; the retrieval module retrieves to obtain data samples; the summary module extracts data features; the analysis module analyzes the data samples and generates analysis conclusions; and the verification module verifies the results of the analysis module. The application generates multi-modal data of feedback data in the Internet through the retrieval module, and according to the obtained data samples, the analysis module analyzes to obtain analysis conclusions by combining virtual user models of psychology and / or sociology, so that the problem that the system has weak theoretical support and single data dimension is avoided.

The invention relates to the technical field of robots, automatic driving and industrial internet of things, in particular to a multi-source data fusion visualization system which comprises a unified data access layer, a time-space synchronization engine, a customizable fusion visualization panel and a visualization information interaction module by expanding a Foxglove platform. The unified data access layer accesses and standardizes multi-source heterogeneous data, the time-space synchronization engine realizes data time alignment and space registration, the customizable panel flexibly displays multi-dimensional data, and the interaction module realizes man-machine operation and hardware feedback. The system solves the problems of multi-tool fragmentation, difficulty in data synchronization, visualization fixation and lack of self-research system adaptation in the prior art, adapts to a lightweight self-research system of an ARM embedded platform, and improves the research, development and debugging efficiency of robots and automatic driving equipment.

The invention discloses an information interaction method, device and equipment applied to an investment and research system, and a storage medium, and relates to the technical field of information interaction, and the method comprises the steps: obtaining interaction information of a user in a preset instruction window; determining a matching degree between the interaction information and each preset business processing module in the investment and research system, and determining a target business processing module according to each matching degree, each preset business processing module corresponding to each business function page in the investment and research system; obtaining a preset processing rule of a target business function page corresponding to the target business processing module; and processing the interaction information through the target business processing module according to a preset processing rule to obtain a processing result. The target business processing module can be automatically determined according to the matching degree of the interaction information, so that manual switching and searching among a plurality of business function pages by a user are avoided, and the convenience and efficiency of user operation are improved.

The invention belongs to the field of information technology and nuclear power engineering management cross technology, and particularly relates to a multi-reactor nuclear power station knowledge management intelligent platform and method based on a block chain technology. Comprising a cloud computing and big data driven knowledge storage integration module which is a function block shared by all block chain nodes on a chain; the block chain enabled decentralized collaborative network comprises a multi-node trust mechanism module and an intelligent contract rule base; the intelligent knowledge management module driven by artificial intelligence comprises an intelligent knowledge pushing module, an intelligent editing and research system and an active pushing and synchronous updating module; an Internet of Things and edge computing integration module; and a one-key copy block chain node regeneration module. The method is used for realizing knowledge integration, resource sharing, risk management and control and efficient cooperation in the global strategy of the nuclear power project.

The invention relates to cross application of an artificial intelligence technology in the field of market investigation, in particular to a technology for generating simulated human equipment by using an AI (artificial intelligence) big language model and performing dynamic interactive investigation, which comprises the following steps of: acquiring and processing original data containing user characteristic information to form a standardized, high-quality and low-noise data set; defining a human device parameter system, and based on the data set and by utilizing an AI large language model, generating a plurality of simulated human devices which have corresponding attribute characteristics and can carry out context association dialogue according to each group of human device parameters, so as to form a simulated human device library; generating an investigation questionnaire based on to-be-investigated target content, selecting a target simulation person from the simulation person library, sending the investigation questionnaire to the simulation person to simulate a real interview, and performing multiple rounds of investigation to obtain interaction data; and generating an investigation report based on the interaction data, so that a target market user group can be dynamically simulated in a large-scale and low-cost manner, and new products, new concepts and new schemes can be quickly fed back.

The invention relates to the technical field of computer systems, in particular to a material research system and method based on a multi-agent game, and the system comprises a man-machine interaction module, a scheme generation module, a review module, an arbitration module, a scheme execution module and a knowledge base module: the man-machine interaction module generates a task instruction according to a user demand; the scheme generation module is used for generating a plurality of candidate schemes; the review module performs multi-view cross review and risk interception on the candidate schemes; the arbitration module is used for processing opinion conflicts among multiple agents; the scheme execution module is used for executing an experiment and collecting data; and the knowledge base module is used for providing static knowledge support and closed-loop backflow of dynamic experimental data for the system. According to the method, multi-target conflicts, knowledge uncertainty and theoretical and practical differences in material research and development are converted into a structured and computable dynamic game process, so that the comprehensiveness of scheme generation, the preciseness of review and the success rate of experimental conversion are systematically improved.

The invention relates to the technical field of deep learning, and particularly discloses a museum exhibit deep research system fused with a multi-modal large model. The system comprises a multi-modal data aggregation module, a cross-modal semantic alignment module, a research path generation module, a dynamic argumentation construction module and a research conclusion generation module, through multi-modal data fusion, semantic alignment and intelligent path planning, an argumentation structure is automatically constructed, and a standard research conclusion is generated. The whole-process intelligent support of exhibit research is realized, and the research efficiency and systematicness are improved.

The invention discloses a legal management research system for AIGC generation error risk division. The system comprises a dynamic error data acquisition and test module, a risk level evaluation and traceability module, a legal responsibility system and adaptation module, a user cognitive intervention and feedback module and a collaborative optimization and strategy iteration module. Collecting and preprocessing AIGC model generation content; constructing an evaluation matrix of error risks, dividing risk levels, and tracing error causes; on the basis of the risk level, legal terms are associated through a semantic matching algorithm, responsibility rules for developers, platforms and users are constructed, and a responsibility traceability chain of block chain evidence storage is generated; generating an authenticity tag, embedding the authenticity tag into an AIGC model to generate a content sample, pushing the content sample to a user, and collecting feedback data; iterating each module parameter based on a reinforcement learning algorithm; according to the method, AIGC model generation content is linked with legal responsibility rules, technical traceability is combined with execution support, and accurate intervention is designed for AIGC model generation error features.

The invention discloses a student companion teaching research system based on computer simulation, and relates to modeling, simulation experiments and data analysis of student companion teaching behaviors. The system is composed of a student companion teaching behavior strategy simulation module, a social simulation module and a data collection and analysis module, can simulate various student interactive behaviors, and performs experimental analysis on the influence of emotion, experience, neighbors and other factors on the behaviors. A core experiment framework of the system is formed by five behavior selection strategies (based on emotions, win-win people and input people exchange, the highest accumulated reward, most of historical behaviors of opponents and most of neighbors) and three network structures (full connection, grids and small world networks), the complex dynamic state of student companion teaching can be efficiently simulated, and factors influencing the interactive behaviors of the students are revealed. The system adopts an agent modeling technology, and each student is regarded as an independent agent and can autonomously select behaviors and update emotional states in interaction. Experimental results show that a behavior selection strategy and a network structure have significant influence on student interaction behaviors, for example, an emotion-based strategy can better encourage companion teaching in a full-connection network, and existence of a fixed behavior agent also affects a behavior mode of a whole group. The invention provides an efficient and flexible research platform for exploring the relationship between the student companion teaching behaviors and various factors, and provides a reference basis for the school to optimize the companion teaching environment.

Some embodiments provide a method for generating a graphical user interface (GUI) for a research system. The method receives a request from a user of the research system for information about a particular category. The method generates a chart that displays a set of events associated with the particular category over a particular period of time. The method incorporates the chart into a GUI for the particular category for transmission to the user. Some embodiments generate a list of events associated with the particular category and generate a GUI that displays the list of the events. Each event is represented in the list by a title of a document identified by the research system as representative of the event.

The invention discloses an intelligent risk analysis and research system and method based on a browser plug-in, and relates to the technical field of financial science and technology. The system comprises a visual process arrangement interface, a process engine and an AI model. The system receives a modular risk control node process arranged by a user through a visual interface, and is driven and executed by a process engine. The core of the method is that in the process of process execution, a system can respond to an interrupt waiting node or a user natural language instruction to suspend the process and wait for interaction; the instruction intention can be analyzed to realize flow skipping or backtracking; after the nodes are executed again, the AI model carries out comparative analysis on execution results and generates a report; and finally integrating node outputs to generate a structured risk control conclusion. According to the method, the problems of low efficiency, lack of deep insight and flexibility of a traditional risk control process are solved, intelligent risk analysis of man-machine cooperation is realized, and the method is particularly suitable for financial risk management scenes such as commercial factoring and the like.

The invention relates to the technical field of artificial intelligence and behavioral science crossing, in particular to a market research system based on multi-source data integration and psychological analysis, which comprises a processing module, an RAG module, a retrieval module, a summarization module, an analysis module and a verification module. The processing module is used for processing feedback data of market research; the RAG module carries out retrieval to obtain multi-modal data; the retrieval module performs retrieval to obtain a data sample; the summarization module performs data feature extraction; the analysis module analyzes the data sample and generates an analysis conclusion; and the verification module verifies the result of the analysis module. The multi-modal data of the feedback data is generated in the Internet through the retrieval module, and according to the obtained data sample, the analysis module performs analysis by combining a psychological and / or sociology virtual user model to obtain an analysis conclusion, so that the problems of weak theoretical support and single data dimension of the system are avoided.

The embodiment of the invention provides a space-time research and judgment method, a research and judgment system, electronic equipment and a storage medium. The method comprises the following steps: acquiring network access data corresponding to an entity to be researched and judged, and processing according to a preset feature extraction rule to obtain basic feature information and associated feature information; constructing a spatial-temporal feature sequence according to the basic feature information and the associated feature information, and inputting the spatial-temporal feature sequence into a trained feature recognition model to obtain behavior feature information; comparing the behavior characteristic information with behavior characteristic conditions in a behavior rule base to obtain a characteristic comparison result; according to a feature comparison result, when it is determined that the entity to be researched and judged meets a preset research and judgment condition, determining an expanded network entity according to the associated feature information; and according to the research and judgment result of the entity to be researched and judged and the expanded network entity, generating and outputting a space-time research and judgment result. According to the invention, the time-space research and judgment of the target entity and the associated network space thereof are realized, and the comprehensiveness and accuracy of identification are improved.