183 results about "Interactive analysis" patented technology

The invention relates to methods and systems for integrating generative artificial intelligence (AI) capabilities into Software as a Service (SaaS) platforms. It comprises maintaining AI agents with varying credentials, enabling their interaction with alphanumeric data in table structures, and implementing a hierarchical access control scheme. The system displays table structures, provides interfaces for user inputs, and allows AI agents to be added as platform users. The generative AI agents can analyze data, identify actions, and perform tasks autonomously. The invention also includes methods for proactive information gathering, interactive analysis of AI outputs, and management of AI resources as limited assets. This approach enhances SaaS functionality by enabling AI-driven task completion, data analysis, and decision-making while maintaining data security and user-specific access controls.

The invention relates to the field of government affair work order intelligent processing, in particular to a government affair work order intelligent processing method and system based on space-time semantic clustering and a large language model. According to the scheme, unified data feature modeling is conducted on a work order to be processed, an improved DBSCAN clustering algorithm is executed on the work order through a weighted space-time semantic three-dimensional distance measurement formula, and combined clustering of space, time and semantic features is achieved; calculating priority scores of the work orders, and dynamically allocating scheduling resources according to the clustering scale and the priority of the work orders; based on a retrieval enhancement generation technology of an RAG framework and an FAISS vector retrieval library, historical similar work orders are matched, a few-sample learning case is generated, and two sets of differential treatment schemes are generated by controlling temperature parameters of a large language model; visual display and interactive analysis of work order clustering are realized through an interactive GIS platform; and establishing a quality feedback closed loop of work order reconstruction. The method is suitable for intelligent government affair work order processing.

Data platforms described herein are configured to monitor a compute environment and facilitate interactive analysis of multifaceted security threats within the compute environment. Such a data platform may determine that one or more assets within the compute environment are possibly being targeted by a multifaceted security threat and present an interactive user interface. The user interface may be configured to display an identifier indicative of the multifaceted security threat, a set of selectable evidence items each associated with a different facet of the multifaceted security threat and assessed based on the monitoring of the compute environment, and a presentation pane for displaying information. As such, the data platform may detect a selection of a particular evidence item from the set of selectable evidence items and, in response to the selection, populate the presentation pane with information related to the particular evidence item. Corresponding methods, systems, and products are also disclosed.

The invention provides a cross-border e-commerce big data analysis system and method, and the method comprises the steps: obtaining multi-dimensional original business data of a cross-border e-commerce platform, carrying out the real-time collection through a distributed data collection system, and obtaining a structured business data set; data collected in real time is cleaned, converted and structured, a unified data model is constructed, and integration of heterogeneous data sources is achieved; storing the processed structured data in a time sequence database to provide data support for real-time analysis; performing real-time aggregation and statistical analysis on the newly added data to generate business index and key performance index data; a Lambda framework is adopted, batch processing and stream processing are combined, the historical data and the real-time data are subjected to full-amount analysis, and an analysis result is obtained; based on an analysis result, a data mining algorithm is adopted to identify a service mode and predict a future trend; a multi-dimensional data cube is constructed, multi-dimensional and multi-granularity data exploration and interactive analysis are supported, and management decision making is assisted.

The invention discloses an automatic medical risk screening system, which relates to the technical field of medical information and comprises a data acquisition module, an intelligent analysis module, a risk early warning module, an intervention management module, a complaint management module and a data visualization module. According to the medical risk automatic screening system provided by the invention, risk data sources in a hospital HIS system are collected in real time and are preprocessed and intelligently analyzed, so that the system can more accurately identify potential risk patients and provide timely early warning prompts for medical staff, comprehensive management of medical risks is realized through each module, and through PDCA circulation, the medical risk screening efficiency is improved. According to the technical scheme, the system automatically generates disposal suggestions, distributes disposal tasks, evaluates the intervention effect and optimizes early warning rules, a continuously improved management process is formed, and a multi-dimensional interactive analysis interface is also provided, so that medical staff can intuitively understand information such as risk distribution, intervention effect tracking and complaint causes in each inpatient area.

The invention discloses a retrieval enhancement question and answer generation method and system based on a large language model in combination with a multi-agent cooperation mechanism. The method comprises the steps of S1, text preprocessing and semantic difference enhancement and amplification; s2, checking and complementing user questions; s3, evaluating problem complexity and selecting a generator; s4, text retrieval and answer generation; the system comprises an information enhancement processing module, a query understanding optimization module, a question complexity intelligent evaluation module and a collaborative answer generation module, and is used for realizing the method. According to the method, a multi-agent collaborative RAG framework of an information enhancement agent, an interaction analysis agent and a problem complexity evaluation agent is introduced, and semantic difference enhancement and amplification, query integrity verification and complementation and a dynamic generation strategy based on problem complexity are performed after hierarchical document partitioning are combined; and the performance of the system in the aspects of semantic distinguishing capability, query understanding precision, generation efficiency and reliability is comprehensively improved.

Presented herein are systems and methods that provide for improved computer aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to several image processing steps used for automated analysis of bone scan images for assessing cancer status of a patient. For example, improved approaches for image segmentation, hotspot detection, automated classification of hotspots as representing metastases, and computation of risk indices such as bone scan index (BSI) values are provided.

The invention discloses a sensor-based GIL pipe gallery expansion joint on-line monitoring system and method, and relates to the technical field of power equipment monitoring, and the method comprises the steps: collecting key state information and environmental parameters of an expansion joint through the deployment of an expansion joint sensor and an environmental sensor, and carrying out the preprocessing; performing deep fusion on expansion joint sensor data and environment sensor data, constructing a comprehensive state evaluation and prediction model, and analyzing the influence of different factors including environment, mechanical faults and material aging on the expansion joint state; correcting state parameters for environmental factors; for mechanical faults, fault types, positions and severity are identified, and corresponding early warning is triggered; aiming at material aging, monitoring and predicting performance degradation and residual life in real time, and formulating a maintenance strategy; the model performance is evaluated and updated regularly, an early warning threshold value is adjusted dynamically, and self-adaptive early warning is achieved; a data integration and visualization platform is developed, and visual display and interactive analysis of monitoring data are achieved.

The embodiment of the invention provides a fault diagnosis method and system for a thermal power plant auxiliary engine system based on a neural network, and the method comprises the steps: firstly extracting pressure data and flow data of an outlet pipeline of a water feed pump system from an edge side, and removing noise interference in the pressure data and the flow data through data filtering processing; a data processing technology based on deep learning is introduced to carry out multi-scale time sequence analysis on pressure data and flow data of the feed pump system so as to capture time sequence change characteristics of the pressure data and the flow data, and then bidirectional interaction analysis is carried out on the pressure time sequence characteristics and the flow time sequence characteristics so as to obtain the time sequence change characteristics of the feed pump system. The dynamic response relation of the outlet pipeline pressure relative to the flow change is excavated, and whether the feed pump system breaks down or not is intelligently recognized according to the dynamic response relation. Therefore, real-time monitoring and accurate diagnosis of the feed pump system can be realized, the accuracy and timeliness of fault diagnosis are improved, and meanwhile, the intelligent level of fault identification is improved.

The invention relates to the technical field of intelligent retail and big data analysis, and discloses a multi-retail store sales volume prediction method and system based on an improved Transform architecture, and the method comprises the steps: collecting historical retail store sales data, historical weather characteristics and holiday and festival data, carrying out the correlation, and carrying out the preprocessing of the collected data; dynamically constructing and training a store sales volume prediction model based on a deep learning neural network, and obtaining gated store-level features and product cluster features which have important influence on sales volume prediction through a multi-level attention mechanism; and fusing external covariables with the gated store-level features and the product cluster features to enhance the prediction capability of the model, and predicting the sales volume of the multiple retail stores based on the trained store sales volume prediction model. According to the multi-retail store sales volume prediction system realized through the method, more comprehensive and more accurate sales volume prediction is realized through interactive analysis of stores and products and comprehensive modeling of external environment variables.

The invention discloses a territorial space planning method based on big data, and belongs to the technical field of territorial space planning. The method comprises the following steps of: 1, integrating territorial space comprehensive data and realizing standardized and normalized preprocessing and semantic association of the data; 2, precise expression and cross-scale conversion of spatial element semantics are achieved; 3, dynamically evaluating and quantifying the information distortion degree and uncertainty in the cross-scale semantic conversion process, and performing intelligent error correction; 4, realizing high-fidelity restoration and semantic consistency reconstruction of the information; 5, realizing an accurate and dynamic territorial space planning decision; 6, converting the cross-scale spatial semantic data into a visual and interactive visual form, and realizing intelligent presentation and interactive analysis of the spatial data; and 7, ensuring real-time performance, safety and openness of planning data, and realizing intelligent and dynamic management of territorial space planning.

The embodiment of the invention provides a network spoofing defense method and system based on AI virtual topology generation, and the method comprises the steps: continuously collecting multi-source heterogeneous data in a network, and constructing and dynamically updating a real network topology portrait based on the multi-source heterogeneous data; on the basis of a generative adversarial network model, adversarial training is carried out by taking the real network topology portrait as a training sample, the structure and characteristics of a real network are learned, and a dynamically changing simulation virtual network topology is generated; seamless fusion and dynamic deployment are carried out on the simulation virtual network topology and the real network, and a trapping environment is constructed; monitoring and recording an attack behavior of an attacker in the trapping environment, and performing deep interaction analysis on the attack behavior and generating threat intelligence; and based on the threat intelligence, dynamically optimizing a deception strategy and executing a closed-loop control response. According to the embodiment of the invention, the virtual topology which is highly similar to a real network but is completely imaginary can be dynamically generated by utilizing artificial intelligence.

The invention relates to the technical field of natural language processing, and discloses a special disease knowledge spectrogram construction and analysis system, which comprises a federal data acquisition module, a dynamic ontology mapping preprocessing module, a cross-source knowledge collaborative extraction module, a self-adaptive graph construction module, an intelligent dynamic updating module and an interactive analysis application module, the cross-source knowledge collaborative extraction module is used for collaborating multi-source data on the premise of guaranteeing data privacy, the dynamic ontology mapping preprocessing module is used for mapping knowledge representation of the multi-source data to a unified standard, and the cross-source knowledge collaborative extraction module is used for extracting medical entities and semantic relationships based on multi-modal data fusion. According to the method, through the cooperation of the longitudinal federated learning framework and the secure multi-party computing algorithm, the problem of multi-source medical data privacy collaborative computing is solved, and the advantages of safely aggregating multi-mechanism data and providing original data support for map construction on the premise of ensuring data privacy are achieved.

The invention discloses a concrete foundation pile visual information integration system and method based on 3D GIS and ultrasonic tomography fusion, the 3D GIS and ultrasonic tomography technology are fused, internal defects of a foundation pile are accurately positioned and visually presented, and the detection intuition and accuracy are remarkably improved. By constructing a three-dimensional information model, correlation analysis of foundation pile defects, structures and geologic body information is achieved, and engineers are assisted in comprehensively evaluating structural safety and risk levels. The system adopts an optimization algorithm and a multi-level framework, not only improves data processing efficiency, but also supports multi-dimensional interaction analysis, provides a scientific basis for operation and maintenance management and reinforcement design of the foundation pile, and effectively overcomes the defects that a traditional detection means is difficult to position, depends on experience and lacks unified management.

The invention belongs to the technical field of underground engineering and computer-aided engineering analysis, and particularly relates to an anti-seismic safety collaborative analysis method for multi-modal data of proximity tunnel engineering. By integrating engineering geology, structural design, construction monitoring and multi-level seismic oscillation data, a three-dimensional numerical model fusing geology and structural information is constructed. Firstly, refined simulation of the whole construction process and the operation static load is carried out, and a reference mechanical state is obtained; carrying out multi-task condition earthquake dynamic time history analysis on the basis, dynamically capturing dynamic response of surrounding rock and a structure, carrying out collaborative interpretation on static and dynamic analysis results, emphatically analyzing spatio-temporal evolution and connectivity risks of a tunnel anchor and an adjacent highway tunnel surrounding rock plastic zone, and extracting a plurality of quantitative collaborative indexes; and an interactive analysis report integrating a three-dimensional visual scene, a multi-dimensional comparison chart and a rule base-based safety interpretation conclusion is automatically generated, and systematic decision support is provided for seismic design, construction control and safety evaluation of proximity projects.

The invention discloses a software supply chain vulnerability assessment method based on multi-Agent collaboration and dynamic hypergraph learning, which is used for opening a link between vulnerability assessment and repair and realizing full-life-cycle collaboration linkage. For the problem of vulnerability assessment and repair splitting, the method covers the core capabilities of static analysis (SAST), dynamic detection (DAST), interactive analysis (IAST), intelligence analysis and the like. Evaluation results of various agents are output through standardized vulnerability portraits, and a subsequent repair strategy is driven to be automatically generated and executed, so that whole-process closed-loop linkage and fine control of'discovery-evaluation-repair-verification 'of vulnerabilities are realized.

The invention discloses a marine geological environment multi-dimensional data reconstruction and dynamic visualization mapping method and system, and belongs to the technical field of marine information technology and data visualization. In order to solve the problems that in the prior art, standard data asset structure is isolated, heterogeneous data deep fusion is difficult, and mass data visualization performance is bottleneck, the method mainly adopts the following technical scheme that standardized multi-source data is received, a data volume mapping rule is established, discrete observation data is reconstructed and fused into a unified and continuous three-dimensional data volume, and the three-dimensional data volume is obtained; and executing a three-dimensional space pattern recognition algorithm on the three-dimensional data volume to recognize a feature entity, and providing on-demand query and multi-resolution access services through a visual mapping interface. According to the method, efficient automatic modeling and high-performance interactive analysis of mass and multi-dimensional marine geological environment data can be realized.

The embodiment of the invention provides a server test platform, method, device and equipment and a storage medium, an interaction analysis system of the server test platform is used for receiving to-be-tested information input by a user, performing semantic analysis on the to-be-tested information to obtain a semantic analysis result, and sending the semantic analysis result to the server test platform; the semantic analysis result is used for determining a target test to be executed on the server test platform; displaying a test result of the target test in the interactive analysis system according to a target form through the target abnormal mode and the multi-dimensional dynamic association data; the three-dimensional association model is used for extracting multi-dimensional dynamic association data about the target test in the process of executing the target test; identifying a first abnormal mode appearing in the target test through the multi-dimensional dynamic association data; the prediction analysis model is used for predicting a second abnormal mode occurring in a target test corresponding to the multi-dimensional dynamic association data; the knowledge management system is used for determining a diagnosis scheme of a test result through the knowledge graph, so that the test efficiency and the test effect are improved.

The invention discloses an AI engine docking decision-making method based on a 5G new call, and the method comprises the steps: carrying out the call service, and analyzing the call information of a user; the AI engine provides an intelligent interaction analysis capability; the media docking module is used for receiving a function instruction of calling service logic, providing basic media capability and making and displaying media content according to user operation; the BM module is used for storing user services and setting data; wherein the call service synchronizes a call instruction, audio and video media stream information and user behavior data to the media docking module, and receives a media instruction. According to the method, real-time multi-mode interactive perception and dynamic AI engine docking can be realized, so that the bottleneck in the prior art is broken through.

The invention relates to methods and systems for integrating generative artificial intelligence (AI) capabilities into Software as a Service (SaaS) platforms. It comprises maintaining AI agents with varying credentials, enabling their interaction with alphanumeric data in table structures, and implementing a hierarchical access control scheme. The system displays table structures, provides interfaces for user inputs, and allows AI agents to be added as platform users. The generative AI agents can analyze data, identify actions, and perform tasks autonomously. The invention also includes methods for proactive information gathering, interactive analysis of AI outputs, and management of AI resources as limited assets. This approach enhances SaaS functionality by enabling AI-driven task completion, data analysis, and decision-making while maintaining data security and user-specific access controls.

The invention discloses a multi-dimensional data association analysis system and method based on unified modeling, and relates to the technical field of big data intelligent analysis. Comprising the following steps: 1, constructing a semantic model; step 2, carrying out query compiling and optimization; 3, performing query execution and scheduling; 4, interactive analysis and visualization are carried out, wherein a multi-dimensional report designer MRD is used for providing end-to-end full-process visualization display, and interactive drilling and narrative analysis are supported; step 5, performing closed-loop optimization; according to the method, the complexity of an underlying data structure is shielded through the semantic model, and automatic correlation analysis of a cross-fact table is supported, so that business personnel can independently complete deep data exploration and decision support without mastering professional technologies such as SQL (Structured Query Language) and the like.

The invention provides an intelligent face document personalized recommendation method and system. The method comprises the following steps: firstly, collecting multi-dimensional face document demand data (including historical consumption, real-time demand and preference change data) and face document supply data (including real-time supply, feature change and consumption feedback data) of a user; constructing a demand evolution trajectory based on the user demand data, and presenting a demand change trend and an association relationship; constructing a supply feature time sequence association set based on the supply data, and presenting a supply feature association mode and a change rule; calling an artificial intelligence model for interactive analysis to generate a dynamic demand supply matching rule; according to the method, the rule is iteratively optimized by using the user feedback data, and the personalized recommendation result of the face file is finally generated, so that the accurate dynamic matching of the demand and the supply is realized, and the user satisfaction and the face file operation benefit are improved.

The invention discloses a construction method of a single-cell multi-omics data analysis system based on a containerization technology, and the construction method of the single-cell multi-omics data analysis system based on the containerization technology comprises the following steps: constructing a single-cell multi-omics analysis modular toolkit; a production mirror image is constructed on the high-performance cluster through a Single container engine, and deployment of a production environment is completed; a single-cell multi-omics automatic analysis platform is built through a snakemake process engine; and a JupyterLab interactive analysis platform for exploratory analysis of the single-cell multi-omics data is constructed. According to the single-cell multi-omics data analysis system construction method based on the containerization technology, the data acquisition link in the analysis process is accelerated, an automatic working process is formed to solve the problem of complex process, and the actual requirements of multiple users on a high-performance computing cluster for scientific exploration and analysis of single-cell data are met.

The invention relates to the technical field of railway engineering, in particular to a track smoothness influence factor correlation analysis method which comprises the following steps: taking track gauge deviation, unevenness, horizontal irregularity, track direction irregularity and curvature change rate corresponding to track smoothness as parameter components; calculating a reference value and an allowable threshold value between the parameter components by using a Gaussian mixture model, and determining the weight of each parameter component; identifying degradation characteristics of each parameter component under the time sequence; using the updating time of the comprehensive degradation degree as a key node of each parameter component by using a linear weighting form; verifying the association probability of each key node and the maintenance record, setting an early warning parameter set, and setting the change trend of each key node according to the number of continuous early warning times in the early warning parameter set; performing interaction analysis based on the change trend of each key node, and determining an early warning range boundary of each parameter component under parameter accumulation; the accuracy and efficiency of track smoothness analysis are realized.

The invention provides a geological exploration data visualization dynamic processing method and system, and relates to the technical field of intelligent geological exploration, and the method comprises the steps: constructing a prior three-dimensional geological structure model and a forward substitution model; constructing a multi-source joint loss function based on forward modeling output of the forward modeling substitution model and geological survey data; based on a multi-source joint loss function, performing layer-by-layer reasoning reconstruction on geological point cloud parameters in the prior three-dimensional geological structure model to obtain a dynamic three-dimensional geological parameter set; performing fusion rendering and interaction analysis on the dynamic three-dimensional geological parameter set to obtain a visualization result of a fusion geological structure and multi-field evolution information, and constructing a scene deduction component based on the dynamic three-dimensional geological parameter set and a forward substitution model; according to the geological situation sensing and deduction early warning method and device, high-precision geological situation sensing and deduction early warning can be achieved through deep fusion of the forward modeling model constrained by physical information and the layered dynamic inversion algorithm.

The invention relates to the technical field of virtual reality application, in particular to a virtual reality assisted urban and rural spatial layout visualization planning system, which comprises a data acquisition and preprocessing module, a three-dimensional modeling module, a virtual reality visualization module, a planning analysis module and an interaction and feedback module. Wherein the data acquisition and preprocessing module is used for acquiring and preprocessing urban and rural spatial data; the three-dimensional modeling module is used for constructing a three-dimensional urban and rural model based on the preprocessed spatial data; the virtual reality visualization module is used for importing the three-dimensional urban and rural model into a virtual reality environment to generate a VR visualization scene; the planning analysis module is used for performing spatial layout analysis and outputting a planning analysis result; and the interaction and feedback module is used for receiving user interaction input and updating the planning scheme in real time. According to the urban and rural spatial layout planning method and system, by integrating the processes of data preprocessing, three-dimensional modeling, virtual reality visualization and dynamic interactive analysis, visual expression and real-time optimization of urban and rural spatial layout planning are achieved.

The invention relates to a large sample exploratory experiment conclusion macro-micro interaction verification method and system, the method is used for constructing a'macro-interaction-micro 'three-layer linkage analysis framework, and the framework comprises a macro conclusion layer, an interaction analysis layer and a micro instance layer; the interaction analysis layer is used for connecting the macroscopic conclusion layer and the microscopic instance layer; the method comprises the four steps of automatic discovery and presentation of a macroscopic conclusion, interactive deep exploration and verification based on the macroscopic conclusion, macro-micro bidirectional linkage and sample screening, and concrete redisk and causal verification of micro instances. Through the method, interactive verification of a macroscopic conclusion and a microcosmic instance is realized, and the interpretability and credibility of the conclusion are remarkably improved. According to the method, a macroscopic and microcosmic barrier is broken through, a cognitive closed loop from'knowing the course 'to'knowing the course' is constructed, and a more robust basis is provided for decision making.

The invention discloses a spatial intelligent scene early warning method and system based on three-layer cooperative constraint, relates to the field of spatial modeling, and solves the problem that the spatial intelligent scene early warning method is poor in early warning effect. S2, establishing a scene three-dimensional coordinate system and a model three-dimensional coordinate system according to an acquisition result, performing interactive analysis on the scene three-dimensional coordinate system and the model three-dimensional coordinate system, and obtaining regional laser point division data according to an analysis result; s3, performing scene intelligent analysis on the target early-warning area according to the early-warning area real-time interaction model, issuing space intelligent early warning according to an analysis result, and establishing an early-warning area real-time interaction model on the basis of the model edge sampling points. According to the invention, the accuracy of a space intelligent early warning result can be improved.

This application discloses a method, device, and electronic device for displaying energy flow in a power plant, belonging to the field of new energy power plant technology. The method includes: generating an energy flow diagram corresponding to the current power plant configuration and displaying it on an interface; the energy flow diagram includes multiple visual elements, each visual element including at least source nodes and carrier nodes representing power plant equipment, and path elements representing the energy flow relationship between source nodes and carrier nodes; responding to user interaction with any node or path element, determining the energy path where the interacted node or path element is located; updating the rendering state of the energy path on the interface to make the energy path appear locally focused relative to other energy paths. This application achieves energy path-level visualization and interactive analysis based on power plant equipment topology, improving the accuracy of expressing power plant energy flow relationships and the efficiency of analyzing multi-dimensional operational data.

The invention relates to the technical field of high-current particle beam diagnosis, in particular to a high-energy ion beam three-dimensional reconstruction method and system based on secondary electron emission signals. According to the technical scheme, the method comprises the steps of data preprocessing and conversion, geometric space up-sampling, point assignment generation and model boundary division and output. According to the method, the spatial sparsity of original data is overcome through geometric upsampling, the fidelity of physical attribute reconstruction is remarkably improved by utilizing a topological structure based on a minimum spanning tree and a primary function frequency superposition model, automatic and accurate division of beam boundaries is realized according to a physical threshold value, an end-to-end automatic processing flow is formed, and the method has the advantages that the method is simple and convenient to operate and high in practicability. And outputting a visual three-dimensional model supporting interactive analysis, systematically solving the problems of data sparsity, interpolation distortion and boundary fuzziness in the prior art, and realizing high-precision and high-efficiency reconstruction and visual analysis of the three-dimensional form of the high-energy ion beam.