2027results about "Visual data mining" patented technology

The invention discloses a computer big data information processing system, which comprises a data acquisition layer, a data processing layer and a data processing layer, wherein the data acquisition layer is used for accessing structured, unstructured and streaming data by using a multi-source adapter and Apache NiFi, executing format standardization, and extracting basic metadata and semantic tags through a rule engine and an NLP model; the metadata intelligent management layer integrates four modules, namely a federal learning framework for realizing cross-domain dynamic classification labels, an intelligent contract for real-time uplink storage evidence blood relationship change, a Neo4j combined graph neural network for constructing a knowledge graph for mining implicit association, and a reinforcement learning engine for optimizing a storage strategy based on frequency and risk indexes; the distributed storage calculation layer is used for processing batch and real-time metadata by adopting a Cassander + MinIO mixed framework and Spark / Flink, and dynamic partition balance performance is realized; and the application service layer is used for outputting functions of blood relationship query, classified browsing, compliance report and the like through a Vue.js portal and a Spring Cloud micro-service API (Application Program Interface) to form a full-link closed loop.

The invention relates to the field of environment monitoring, discloses an ecological protection red line holographic dynamic monitoring and early warning method and system, and aims to solve the defects of an existing monitoring and early warning mechanism in the aspects of timeliness, data integration and intelligent analysis. According to the method and the system, multi-source heterogeneous data are acquired and fused, a space bottom line digital model is constructed, space-time situation awareness analysis and change abnormity identification are performed, risk assessment early warning triggering is performed, and early warning issuing and processing feedback are managed. According to the invention, high-precision holographic acquisition and fusion of multi-source data can be realized, the accuracy and timeliness of change abnormity identification are improved, passive early warning is changed into active early warning, a monitoring disposal closed loop is formed, supervision intelligence and treatment efficiency are improved, and ecological safety is guaranteed.

The invention discloses a project performance evaluation and risk early warning method for multi-source heterogeneous scientific research data, and relates to the technical field of scientific research project management, and the method comprises the steps: collecting the multi-source heterogeneous scientific research data, cleaning, converting, filling missing values, and storing in a unified format; extracting performance and risk features, and fusing to obtain a fused feature set; combining an analytic hierarchy process, an entropy weight method and the like to construct a dynamic weight performance evaluation model; constructing a multi-modal risk early warning model by adopting multiple algorithms and optimizing a threshold value; collecting data in real time to update a feature set, and dynamically adjusting the model; and visually outputting a result, generating an improvement suggestion, and forming closed-loop feedback. According to the method, the multi-source data processing efficiency and evaluation accuracy are improved, the risk early warning timeliness and adaptability are enhanced, a management closed loop is formed, and the problems of difficult data integration, evaluation lagging, insufficient early warning and the like of a traditional method are solved.

The invention relates to a coal mining safety prediction visualization method and system, and the method comprises the steps: determining a sensor deployment scheme based on mine geological structure information and operation environment characteristics; collecting multi-modal monitoring data according to the sensor deployment scheme, and generating a fusion data set of time-space alignment; extracting corresponding spatio-temporal features, and generating a corresponding risk assessment matrix based on the spatio-temporal features; constructing a four-dimensional tensor field containing a time dimension, and generating a dynamic risk visual image based on the four-dimensional tensor field; in the dynamic risk visual image generation process, receiving a feedback instruction input by an expert, and updating the coal mine safety domain knowledge graph by adopting a fuzzy cognitive mapping mode based on the feedback instruction; and optimizing the space-time convolutional network, updating the dynamic risk visualization image, obtaining an updated risk visualization image result, and executing hierarchical early warning processing. According to the method, the richness and accuracy of coal mining safety prediction visualization can be improved.

The invention relates to the technical field of data integration, and particularly discloses a perfluoro / polyfluoroalkyl substance multi-source exposure data integration risk assessment system, which is characterized in that environmental exposure data of perfluoro / polyfluoroalkyl substances is acquired through a multi-source environmental sensor array, and a PFAS multi-mode exposure feature database is established; carrying out pollution source isotope fingerprint analysis, and obtaining source contribution rate distribution maps of three pollution sources of industrial emission, surface runoff and atmospheric settlement through a nonlinear source analysis algorithm; constructing a three-dimensional geographic information dynamic migration model according to the source contribution rate distribution map, and generating a multi-medium dynamic migration flux matrix; a composite risk assessment model is established based on the multi-medium dynamic migration flux matrix, probability risk assessment is executed in combination with an ecological toxicity threshold database, and a space gridding risk grade map is output; the method not only fills the blank of the prior art in the aspects of multi-medium dynamic modeling and nonlinear source analysis, but also provides powerful technical support for environmental pollution control and ecological risk prevention and control.

The invention discloses a lithium battery full life cycle quality tracing system based on digital twinning, and relates to the technical field of lithium battery quality tracing, and the system comprises a physical entity layer which integrates multiple types of sensors and detection equipment to collect full-link data; the digital twinning modeling layer is used for constructing a multi-scale model to map a battery state; the data acquisition and transmission layer is used for realizing data real-time transmission preprocessing through an edge gateway and an encryption protocol; the data storage and management layer is used for establishing a data warehouse by using a distributed database and performing backup; the intelligent analysis and decision-making layer integrates an algorithm to realize anomaly detection, performance prediction and tracing; the visualization and interaction layer is used for providing a multi-terminal visualization and interaction function; and the block chain evidence storage layer constructs an alliance chain to ensure that the data cannot be tampered. According to the invention, full-life-cycle data connection and credible tracing of the lithium battery are realized, the quality problem positioning efficiency is improved, intelligent early warning and optimization capabilities are provided, the operation threshold is reduced, and industrial quality control and green development are facilitated.

The invention relates to the technical field of data governance, and discloses a data governance method based on an intelligent decision engine, which comprises the following steps: carrying out business semantic classification and marking on preliminarily processed real-time streaming data, and constructing a data portrait library; constructing a dynamic topological graph, learning an abnormal propagation rule based on a graph neural network, analyzing an influence range and establishing an influence grading mechanism; performing multi-dimensional quality evaluation on the data, and generating a dynamic data quality score and a grading strategy; constructing a data quality historical problem and reason case library, and generating a quality anomaly root cause judgment and influence quantification report by using a large language model agent; generating a candidate strategy set, and selecting an optimal governance strategy from the candidate strategy set by establishing a multi-objective optimization model; and performing compliance test and conflict identification on the optimal governance strategy by using a large language model agent, and dynamically adjusting the decision weight of a rule engine by using a reinforcement learning algorithm to realize a closed loop of data governance and dynamic learning.

The invention discloses a GIS interactive visualization processing method and system for geographic coordinate data, and relates to the field of GIS and the technical field of computers. The method comprises the following steps: collecting multi-source geographic coordinate data, preprocessing the multi-source geographic coordinate data, and standardizing the preprocessed multi-source geographic coordinate data to obtain target multi-source geographic coordinate data; loading the target multi-source geographic coordinate data to a GIS map, and displaying the target multi-source geographic coordinate data through different layers; automatically detecting and marking data quality based on a display interface corresponding to the GIS map; and correcting the detected problem data based on a GIS map by adopting an interactive data correction mode. According to the method and the device, the technical problem of low data processing efficiency caused by difficulty in intuitively reflecting the spatial distribution characteristics and the association relationship of the data because the current geographic coordinate data treatment method mostly depends on the traditional data processing means and presents the data in the forms of texts and tables is solved.

The invention relates to the technical field of carbon emission monitoring and environment perception, and discloses a user-side carbon emission real-time monitoring and tracing system, which comprises a multi-source data integration module, which is used for acquiring microenvironment parameters related to carbon emission in real time; the microenvironment feature analysis module is used for analyzing the feature parameters of the traffic road section through a microenvironment perception algorithm and establishing a microenvironment feature library; the environment relation modeling module is used for constructing a vehicle performance and microenvironment relation model and calculating an environment adjustment coefficient; the dynamic carbon emission calculation module is used for generating a carbon emission estimated value; the abnormal recognition and early warning module is used for recognizing an abnormal emission mode under a specific microenvironment combination and constructing an early warning mechanism; the carbon emission map building module is used for building an urban microenvironment carbon emission influence map; the carbon footprint analysis and report module generates a refined carbon footprint report through a microenvironment factor contribution degree quantitative decomposition algorithm; according to the method, through microenvironment influence decomposition and visual display, a carbon emission result has good interpretability.

The invention relates to an emergency command decision assessment method based on a four-dimensional visual cloud platform, and the method comprises the steps: collecting historical cases and heterogeneous sensing data in a structured manner, extracting multi-dimensional features, such as event types, influence factors, response processes, space-time and causal chains, carrying out the normalization processing, mapping the features into a dynamic ontology library, and carrying out the decision assessment of the emergency command. And realizing structured expression and semantic association of cross-case knowledge. On the basis, AI-driven semantic structure migration and graph neural network characteristic migration are utilized, most relevant knowledge fragments are quickly matched for new events, a prediction model is generated in a self-adaptive mode, and model dynamic optimization is achieved in combination with real-time perception data. According to the technology, the accuracy and generalization ability of knowledge migration in the emergency response process are effectively improved, continuous self-adaptive situation prediction and high-reliability decision support are realized, and the real-time performance and intelligence of an emergency command system are enhanced.

The invention provides a data weaving device supporting cross-domain data fusion analysis, and the device comprises a cross-domain data access storage module which is used for carrying out the distributed asynchronous intake processing of an original cross-domain data set, so as to generate an original data storage pool; the multi-dimensional data preprocessing module is used for performing multi-dimensional data cleaning and standardization processing on the cross-domain data in the original data storage pool to generate a standardized cross-domain data set; the cross-domain data association fusion module is used for performing cross-domain association fusion processing on the standardized cross-domain data set to generate a cross-domain fusion data set; the structured storage module is used for performing structured storage and analysis modeling processing on the cross-domain fusion data set to generate a cross-domain data fusion analysis result; and the fusion analysis result output packaging module is used for performing visual output and interface packaging processing on the cross-domain data fusion analysis result so as to generate an interactive cross-domain data fusion analysis output result. The device adapts to efficient processing requirements of cross-domain data.

The invention relates to the technical field of risk control and data analysis, in particular to a risk control real-time feature platform calculation method and system based on a big data technology. The method comprises the following steps: firstly, acquiring multi-source data in real time through a parallelization mechanism; executing three-layer cleaning based on a streaming engine; dynamically generating numeric and associated feature vectors by adopting a sliding window; loading a pre-training model to carry out risk assessment on the feature vector and outputting a third-level risk event; executing a hierarchical response strategy: transaction blocking, manual auditing and auditing release; a layered framework is adopted, and incremental model training and deployment are supported; and real-time monitoring and dynamic configuration functions are provided. According to the invention, millisecond risk identification and response are realized, and risk control timeliness and accuracy are significantly improved.

The embodiment of the invention discloses a report generation method and device, computer equipment and a readable storage medium, and the method comprises the steps: displaying a graphical user interface to prompt a report requester to input report demand information; report demand information is obtained, semantic analysis is carried out on the report demand information through a large language model LLM to obtain report generation indication information, and the report generation indication information at least comprises a data range, a data type, a data statistical parameter and a report display type; searching a database through the LLM to obtain a plurality of business data matched with the data range and the data type, and obtaining business indexes of the plurality of business data based on the data statistical parameters through the LLM; and determining report basic parameters based on the report display type through the LLM, and outputting a target report based on the report basic parameters, the multiple pieces of business data and the business indexes. By adopting the method, the technical threshold of data analysis processing can be reduced, the report generation efficiency is improved, and the method is simple, efficient and high in applicability.

The invention discloses a data analysis method and system based on a large model. The method comprises the steps that natural language query of a user is received; performing semantic coding and intention analysis on the natural language query based on a pre-trained large language model; based on metadata retrieval of vector similarity, obtaining metadata related to natural language query semantics from a vector database; generating corresponding structured query parameters through the large language model in combination with the obtained metadata and the natural language query; according to the structured query parameter, generating an executable structured query language statement; and executing the structured query language statement to obtain a data query result. According to the method, the problems of insufficient semantic comprehension ability, low metadata retrieval precision and poor query generation controllability in the prior art are solved.

The invention relates to the technical field of forest fire management, in particular to an integrated forest fire intelligent analysis method and system. The system comprises a background service system, a central intelligent analysis system and a mobile intelligent analysis system. The background service system is deployed in a cloud computing server cluster and is used for uniformly storing personnel information, fire scene information and geographic information data and realizing multi-source data fusion and authority management through a standardized API (Application Program Interface); the central intelligent analysis system is deployed in a high-performance computer, integrates a forest fire danger auxiliary decision-making model, a forest fire spreading trend prediction model, a force distribution dynamic display module and a collaborative plotting module, and supports fire spreading prediction and real-time decision-making instruction issuing based on multi-dimensional data such as weather, terrain and vegetation; the mobile intelligent analysis system realizes fire spreading trend analysis, mobile plotting and instruction receiving in an offline environment, supports offline data caching and calling in an emergency scene, and effectively improves forest fire emergency response efficiency and resource scheduling accuracy.

The invention belongs to the technical field of data visualization, and particularly relates to a dynamic visualization generation method, system and device based on user behaviors and context awareness and a medium, and the method comprises the steps: generating a structured operation sequence after standardizing original input data; performing time sequence modeling on the operation sequence to generate a user behavior semantic vector, and generating a joint feature vector by adopting an attention mechanism; pre-loading an input data set, and generating a candidate view set in combination with the user intention preference in the joint feature vector; calculating view scores through a layout optimization function, and screening an optimal view scheme with the highest score; dynamically simplifying or enhancing the chart component according to the equipment performance and context parameters in the joint feature vector; calling a rendering engine to output a view, and monitoring a user interaction event; and updating the strategy network through a PPO algorithm, and optimizing a subsequent view generation path. The problem of unsmooth interaction caused by a static template is avoided, and the user experience is remarkably improved.

The invention relates to a land space planning and surveying and mapping engineering collaborative measurement method, which comprises the following steps: collecting multi-source surveying and mapping data of a target area, and constructing a live-action three-dimensional semantic model bearing ground feature semantics through fusion processing; key planning elements are extracted based on the model, the spatial relation of the key planning elements is quantified, and a spatial relation graph with geometric entities as nodes and the spatial relation as edges is generated; the planning management and control terms are formalized into computable logic assertions, and a machine executable planning rule base is constructed; performing collaborative traversal and logical reasoning on the spatial relation graph based on the rule base, automatically comparing and identifying violation situations, and generating a planning conflict report; and carrying out fusion mapping on the report and the three-dimensional model to generate a three-dimensional visual review layer for intuitively indicating the position, type and degree of the violation. According to the method, deep fusion of surveying and mapping data and planning rules is realized, planning conformity review can be automatically and intelligently completed, and the problems that the prior art depends on manpower, and is low in efficiency and different in standard are effectively solved.

The invention discloses an ecological restoration effect evaluation method for a land and space comprehensive improvement area, and relates to the technical field of ecological environment monitoring. A terrain structure data set and a moisture dynamic data set are obtained after data analysis and image feature extraction; the method comprises the following steps: carrying out terrain disturbance evaluation by constructing a terrain disturbance response index Rtz, carrying out hydrological back-up state evaluation by constructing a hydrological back-up trend index Gsh when the terrain has an unsteady disturbance region, carrying out ecological adaptation evaluation by constructing an ecological adaptation comprehensive index SSZ when the hydrological back-up meets the standard, and generating a landform base map of a renovation region by calling DEM (Digital Elevation Model) data. And each evaluation result is subjected to visual partition display through GIS space rendering, and a repair effect report is automatically generated. According to the method, multi-dimensional quantitative evaluation of terrain disturbance, hydrological refilling and ecological adaptability of the renovation area is realized.

The invention relates to the technical field of computer application, and particularly discloses a chemical industry park safety risk assessment method based on an agent model. The method comprises the following steps: constructing a multi-agent collaborative perception framework, and fusing multi-source heterogeneous data of equipment, environment, materials and personnel to form a park panoramic view under a unified space-time reference; establishing an agent behavior model library embedded with the chemical process mechanism and the safety interlocking logic; an intelligent agent decision strategy is optimized through deep reinforcement learning, and multi-target training is carried out by taking a safety index as a reward function; executing dynamic risk deduction and accident chain simulation in a digital twin environment, and quantifying risk probability and consequences in combination with Monte Carlo sampling; and finally, a visual thermodynamic diagram and an interpretable risk assessment report are generated, weak links are identified, and intervention suggestions are provided. According to the technical scheme, dynamic, accurate and prospective evaluation of the safety risk of the chemical industry park can be realized, and the early warning timeliness and the evaluation reliability are remarkably improved.

The invention discloses an industrial building business service management method and device and a medium, and belongs to the technical field of building service management, and the method specifically comprises the steps: constructing a multi-dimensional data fusion model; defining cost, progress, quality and security dimension data ranges and acquisition nodes, and storing the data ranges and the acquisition nodes in a model database after standardization; based on the standardized data of the multi-dimensional data fusion model, analyzing a dimension internal relationship by using an association rule mining algorithm, defining a dimension mapping relationship, and integrating to form an association rule base; establishing a multi-dimensional linkage analysis module; the module is established by taking a model database as a data source and a multi-dimensional data association rule base as a logic support, and a threshold triggering mechanism and a cross-link data calling function are set; constructing a business collaborative decision support module; business requirements of multiple departments are integrated; a multi-dimensional data visualization monitoring platform is built; and designing a linkage trend chart based on a result of the multi-dimensional linkage analysis module.

The invention relates to an ecological environment inspection and detection information management method and system based on artificial intelligence, and the method comprises the following steps: carrying out the inspection and detection of water quality, air and soil samples collected by an ecological environment monitoring station, and obtaining environment detection data; performing environmental element association calculation based on the data to obtain element association data, and generating an environmental element distribution diagram through spatial-temporal distribution mapping; tracking a pollutant migration rule by using the distribution map, extracting pollutant migration characteristic data, and carrying out environmental impact assessment according to the pollutant migration characteristic data to form an environmental impact assessment report; according to the method, the monitoring area is subjected to risk distribution division according to the report, area environment risk distribution data is obtained, a targeted ecological environment management scheme is generated based on the data, and the technical problems that in the prior art, an effective correlation analysis means is lacked, and migration and transformation rules of pollutants among different media are difficult to reveal are solved.

The invention provides an intelligent data consanguinity tracking and visualization method based on graph calculation, and the method comprises the steps: carrying out the data structure analysis and metadata extraction of original data assets, so as to generate a standardized data asset package; performing graph node attribute definition on the data entities in the standardized data asset package, and performing graph edge attribute definition on the association relationship between the data entities to generate a first data blood relationship model; performing blood relationship path mining on graph nodes and graph edges in the first data blood relationship graph model to obtain a basic blood relationship path set, and performing quantitative calculation and feature labeling on path association strength in the basic blood relationship path set to generate a second data blood relationship graph model; and performing visual rule mapping on graph node attributes and graph edge attributes in the second data blood relationship graph model to construct a standardized visual data set and generate a data blood relationship visual interaction interface according to the standardized visual data set.

The invention relates to the technical field of digital villages, in particular to a digital village construction business data analysis method and system, and the method comprises the following steps: obtaining a field detail comparison mapping role and a label, analyzing the field difference and relation to obtain a field reference set, recognizing the field sequence and relation to obtain a field path sequence column, and obtaining a field path sequence column; and extracting a time position matching stage transaction field processing fragment set, reading a position scanning number to obtain a behavior field structure list, and tracking a field line number extraction text to obtain a business data analysis field set. According to the method, semantic association is established by matching field text content, an attribution level is constructed, a circulation path is restored by relying on field positions, continuous fragments are divided by fusing time intervals and stage identifiers, a parallel advancing track is extracted according to a calling range and serial number arrangement, and context content is extracted by tracking field data lines. A data structure view capable of supporting cross-stage, multi-role and multi-context analysis is constructed, and the coverage range and organization ability of field behavior extraction are enhanced.

The invention discloses a scenarized hierarchical management and control method for an education application in a data space, and the method comprises the steps: obtaining a multi-modal input content in a corresponding preset period after the starting of the current time in response to a starting instruction of the education application in a target data space; calling a corresponding analysis strategy according to the content type of the multi-modal input content; extracting target features from the multi-modal input content based on an analysis strategy; according to an education scene corresponding to the target data space, obtaining a matching result of the target feature and a target database; determining a corresponding data space risk level according to a matching result; and calling and executing an application management and control strategy corresponding to the data space risk level. According to the method, education application hierarchical management and control adaptive to different scenes can be provided, the management and control precision is high, meanwhile, automatic analysis and management and control processes are achieved, and the method is suitable for scenes such as classroom teaching management, after-class and extracurricular training, remote examination and family interactive learning.

The invention discloses a complex system data visualization modeling method based on GIS and topological graph fusion, and relates to the technical field of data visualization modeling, and the method comprises data fusion modeling, space-time anomaly reasoning, state propagation modeling and multi-dimensional visualization enhancement. The method comprises the following steps: performing unified access, cleaning and standardization processing on operation data, topological relation data, geographic space data, function configuration data and environment data of a complex system, and constructing a unified data model fusing geographic attributes and topological attributes; realizing abnormal root cause reasoning and spatial constraint propagation modeling of a system state by using a convolutional time sequence modeling method combined with a graph neural network; a dynamic evolution rule of a node state is described through a time gating mechanism, and interactive display is realized; according to the method, global visualization of the operation state of a complex system, dynamic backtracking of an abnormal propagation path and hierarchical analysis of key nodes can be realized, and the intelligent monitoring, situation awareness and decision support capabilities of the system are improved.

The invention relates to a data AI analysis management method and system based on a production element association map. The method comprises the steps that a multi-source heterogeneous production data flow covering the whole industrial production cycle is obtained; constructing a whole-process production element association map through an entity recognition and relationship extraction technology; actual operation indexes of the production nodes are calculated in real time and compared with a reference threshold value, and potential production bottleneck nodes are accurately recognized; upstream associated node data are backtracked, historical data in the same period are combined to be input into the bottleneck root cause diagnosis model, and core influence factors are accurately obtained; generating an optimal scheduling strategy according to the core influence factors and issuing the optimal scheduling strategy to a production execution system; according to the scheme, the multi-source heterogeneous data of the whole period of industrial production can be effectively analyzed and managed, accurate regulation and control of the production process are achieved, and the production efficiency and the product quality are improved.

The invention relates to the technical field of data processing, in particular to an intelligent supervision method and system based on a data visualization platform, and the method comprises the steps: collecting multi-source water conservancy data through dual-channel redundancy check, converting the multi-source water conservancy data into a standardized space-time matrix, carrying out the data cleaning through a containerization adaptation and variational auto-encoder, and marking the confidence; hierarchically storing the data based on a confidence threshold, and generating a routing strategy through reinforcement learning to distribute data fragments; calculating a flood peak evolution prediction result by using space-time diagram convolution, calculating an output risk assessment value by combining a Bayesian network and long and short-term memory, and activating federal learning parameter updating when the confidence coefficient is insufficient; the digital twin model loads physical constraint parameters to deduce a flood control scene, and a scheduling instruction set and a rehearsal animation are generated through multi-objective optimization; and dynamically rendering to generate an interactive visual interface, associating a causal deduction path, and triggering federal model parameter updating by user feedback, thereby realizing dynamic collaboration of the forecasting and early warning rehearsal plan function chain.

The invention relates to the field of smart city management, and discloses a multi-source data fusion and treatment method for a CIM platform, and the method comprises the steps: sorting the current situation of city spatial data, and carrying out the unified access and classification of the data; carrying out unified conversion on the data, and carrying out merging and layer sequence arrangement; carrying out unified space coding on the geographic space object, and constructing a coding rule; the granularity is divided into construction granularity and expression granularity, data are fused through spatial association, and unified expression of multi-scale data is achieved; extracting spatial semantic information, establishing a mapping relation between a unified address and a CIM model, and realizing semantic expression of a place name and the address; constructing a pyramid model, and realizing fusion of the building information model and the CIM; and performing graph falling processing on the government affair data to form a thematic data base plate associated with the CIM model. According to the method, efficient access, unified processing and deep fusion of the multi-source data are realized, and the integration and availability of the data in the CIM platform are improved.

The invention relates to a port water area ship navigation risk distribution calculation and visualization method and device based on AIS and GIS data fusion, and the method comprises the following steps: 110, obtaining ship AIS data, and carrying out the preprocessing of the ship AIS data, thereby obtaining the preprocessed ship AIS data, and the preprocessing comprises the standardization, feature extraction and abnormal point detection; step 120, carrying out port water area grid construction, and carrying out grid mapping and legality screening on the preprocessed ship AIS data; step 130, performing port water area static risk assessment, port water area dynamic risk assessment and port water area propagation risk assessment on the port water area, and performing port water area comprehensive risk assessment on the basis to obtain an assessment result; and step 140, drawing a port water area risk thermodynamic diagram based on the evaluation result to realize risk distribution visualization. According to the invention, efficient and scientific decision support can be provided for port safety management.

The invention relates to the technical field of big data processing and analysis, in particular to a commodity traceability management method and system based on big data. The method comprises the steps of determining a data range and association logic of each type of events by constructing a semantic event system of a commodity life cycle, performing data acquisition, preprocessing and credibility evaluation at edge nodes and generating an evidence header, and further converting data into multilayer verifiable commodity fingerprints of an L1 edge abstract, L2 event level fusion and L3 full link fusion, the method comprises the following steps: realizing feature fusion and dynamic incremental updating, then performing distributed notarization and multi-party verification on fingerprints through a federated anchor point mechanism to ensure that a full link is traceable and cannot be tampered, and finally supporting full link traceability query and anomaly tracking based on a unique commodity identifier. And closed-loop traceable management is realized through visual display and multi-role authority management. According to the invention, the reliability, interpretability and cross-organization trust of commodity traceability are effectively improved.