581 results about "Visual interface" patented technology

The invention discloses an intelligent contract vulnerability detection and repair system based on a heterogeneous graph neural network, and belongs to the technical field of block chain security, and the system comprises a contract analysis module, a multilayer graph construction module, a heterogeneous graph neural network module, a vulnerability feature library, a vulnerability recognition engine, an automatic repair module and a visual interface. After the source code of the intelligent contract is input, code analysis and standardization are completed by a contract analysis module; the multi-layer graph construction module constructs a contract internal heterogeneous graph, an inter-contract interaction graph and an ecosystem relation graph based on a graph theory; the heterogeneous graph neural network module learns a vulnerability feature mode; the vulnerability recognition engine combines the vulnerability feature library to realize vulnerability classification and risk assessment; the automatic repairing module generates a repairing scheme; and the visual interface realizes detection progress monitoring, result display and encrypted report export. The intelligent contract vulnerability detection and restoration system based on the heterogeneous graph neural network provided by the invention provides technical support for block chain digital asset security and ecological stability.

The invention discloses a large language model auxiliary optimization strategic decision-making system and a large language model auxiliary optimization strategic decision-making method. The system comprises six core modules. The dynamic knowledge fusion module constructs a three-layer distributed knowledge network, constructs an entity association weight matrix through a bidirectional Transform model based on an attention mechanism, and realizes knowledge dynamic association in combination with a time attenuation factor and a hybrid coding technology. The large language model module performs field fine tuning by adopting incremental pre-training and low-rank adaptation technologies, and introduces an exclusive word segmentation list to improve professional analysis precision. The full-process intelligent writing module covers submodules for report generation, revision and the like, and supports full-life-cycle management of reports. The strategic decision intelligent deduction module integrates scene impact factors, and realizes multi-scene deduction through reinforcement learning and Monte Carlo tree search. The interaction display module provides a visual interface, and the multi-mode interaction module realizes full task chain management. According to the invention, real-time knowledge support and intelligent deduction capability are provided for strategic decision making, and decision making efficiency and accuracy are improved.

The invention discloses an interpretability analysis and decision sharing verification method and system for a rectal cancer prognosis model, and relates to the field of medical artificial intelligence interpretability. The method comprises the following steps: carrying out gradient weighting class activation mapping analysis on a prognosis model to generate an image thermodynamic diagram; calculating the contribution degree of the multi-modal features by using an SHAP interpreter; an integrated visual interface is constructed, and patient data, model prediction and the explanation result are presented to a doctor together; the doctor performs independent risk assessment based on the interface information; finally, decisions of doctors and the model are compared, and model auxiliary efficiency is evaluated. Through a doctor-model decision sharing verification mechanism which is explained and innovated in a multi-level mode, the transparency and clinical credibility of the complex AI prognosis model are remarkably improved, the value of time sequence data in dynamic risk assessment can be verified, and clinical landing application of the AI model is powerfully promoted.

The invention provides a user behavior tracking and portrait generation system, which is characterized in that multi-source original behavior data is acquired through a data acquisition module, and a standard behavior event stream is generated through cleaning and standardization; the behavior modeling module is used for carrying out cross-event association and self-defined time window combination modeling on a standard event flow based on a configurable rule engine to generate a complex event flow; the real-time processing and calculation module performs real-time aggregation calculation on the complex event stream, generates a real-time behavior index, a trigger signal and an incremental portrait snapshot in combination with a preset rule, and pushes a behavior trigger signal to a downstream service system; the user portrait management module dynamically updates user tag weights and values according to the real-time indexes, and generates a target user portrait tag library and a lightweight tag change event stream; the data storage and query module stores data of each link; and the visual configuration and operation and maintenance module issues a configuration instruction through a visual interface, and monitors full-link operation and task scheduling. And real-time accurate portrait construction and instant service response are realized.

The invention discloses a medical review and publication quality control system based on deep learning and medical knowledge, and relates to the technical field of medical information processing, and the system comprises a medical knowledge enhancement module which is used for carrying out the named entity recognition and relation extraction technology based on a multi-source fusion medical knowledge system, constructing a structured medical knowledge graph and carrying out intensive training; the multi-dimensional examination and analysis module is used for performing multi-dimensional evaluation on the manuscript based on the medical knowledge graph; the intelligent interaction and feedback module is used for displaying the evaluation result of each dimension through a visual interface; and the publishing quality management and control module is used for sequentially executing whole-process publishing supervision of standardized monitoring, quality inspection and abnormal intervention on the manuscripts passing the examination and analysis. The manuscript reviewing efficiency is greatly improved, and the requirements of high-frequency and rapid publishing of medical scientific research are met; the problem of review difference caused by subjective factors of a manuscript reviewer is solved, and the stability and reliability of the assessment result of the same manuscript are ensured through a standardized and quantitative assessment system.

The invention provides a business path tracking and fault tracing method and device for a video monitoring system, and relates to the technical field of video monitoring fault diagnos.The video monitoring system is divided into a plurality of layers, and multiple types of data acquisition probes are deployed at key nodes of each layer; when a user initiates a video request, generating a Trace ID to be spread along with a video streaming signaling, and reconstructing an end-to-end service path in combination with node information captured by a probe; associating and fusing the multi-dimensional performance data by taking the TraceID as a key, and establishing an end-to-end total delay decomposition and dynamic health baseline; and positioning a root cause node based on the weighted directed graph, the node anomaly confidence score and the fault propagation consistency, displaying a path, data and a traceability result through a visual interface, and generating a precise alarm. According to the method, service link visualization is realized, traditional equipment alarm is upgraded to service fault root cause positioning, the troubleshooting efficiency is improved, and the method is suitable for an isomerized large-scale video monitoring system.

The invention discloses an automatic monitoring device and method for an open pit coal mine slope, particularly relates to the technical field of mine safety monitoring, and is used for solving the problem that existing equipment and methods are insufficient in monitoring precision and real-time performance. Slope displacement, vibration, stress and visual image data are collected in real time through a multi-source sensor array; performing cross-modal feature extraction and noise suppression on the multi-modal data to generate a structured time sequence feature vector and spatial gridding image feature data; fusing the time sequence and the visual data based on a space-time alignment algorithm and an edge calculation framework to generate high-precision space-time synchronization data; performing deep correlation analysis through a multi-head attention mechanism by using an AI large model, and outputting slope deformation characteristic data and a stability risk assessment value; and when the risk value exceeds the preset threshold value, real-time early warning is triggered, and an interactive monitoring report is output through a three-dimensional visual interface, so that the problem that the existing equipment and method are insufficient in monitoring precision and real-time performance is effectively solved.

The invention discloses an intelligent monitoring and evaluating system for the metal health state of a generator set, and belongs to the technical field of state monitoring of power generation equipment. The system comprises a data acquisition and preprocessing module, a data fusion and feature extraction module, a metal health state evaluation module, a residual life prediction and fault tracing module and a visual intelligent decision support module. The method comprises the following steps of: extracting cross-scale damage characteristics by fusing macroscopic operation data and microscopic nondestructive testing signals; calculating a comprehensive health index by adopting a physical mechanism model and data-driven model adaptive weighted fusion mode; dynamic residual life prediction and failure reason intelligent traceability are realized; and finally, graded early warning and maintenance decision suggestions are provided through a three-dimensional visual interface. According to the method, the problems of single monitoring dimension, model isolation and static prediction in the prior art are solved, and comprehensive, high-precision and interpretable evaluation and predictive maintenance support of the health state of the metal part are realized.

The invention discloses a frozen soil temperature feature recognition algorithm and a moisture and electric field state prediction model, and the method comprises the steps: synchronously collecting temperature, moisture, resistivity and meteorological data through arranging a multi-depth sensor array, and constructing a multi-source data set with time-space alignment; utilizing continuous wavelet transform and cross-modal coherence analysis, and combining a hidden semi-Markov model to extract a depth-periodic characteristic profile; a time domain fusion Transform model embedded with physical constraints is adopted to realize frozen soil multi-parameter physical consistency prediction and uncertainty quantification; and finally, outputting a prediction result through a visual interface and setting an automatic alarm. The problem of cycle identification caused by weak and non-stable deep frozen soil signals is solved, the prediction accuracy and the physical rationality are remarkably improved, an end-to-end solution from data quality control to early warning is formed, and the reliability and the practicability of frozen soil engineering monitoring are greatly enhanced.

The invention discloses an intelligent communication content adaptation system and method based on user intention recognition. The system integrates and processes texts, voices, emoticons and unstructured behavior data through a multi-modal input analysis module; the deep learning intention recognition engine adopts a triple attention mechanism, current input and weighted historical interaction features are fused, and multi-level intention classification including basic operation, semantic targets and emotion driving is output; the real-time emotion state analysis module fuses acoustics, semantics and physiological indexes to generate a dynamic emotion matrix; the content adaptation decision engine is based on the intention confidence and the emotional state; and the multi-channel output optimization module performs cooperative adjustment on the speech synthesis rhythm, the text abstract and the visual interface according to the speech synthesis rhythm and the text abstract. According to the method, the perception precision of the deep intention and emotion of the user in a complex scene is remarkably improved, the individuation and multi-channel adaptive optimization of the response content are realized, and the communication efficiency and the user experience are effectively improved.

The invention relates to the technical field of software development, in particular to a zero-code protocol analysis and full-link visualization commissioning and testing method for a heterogeneous terminal, which comprises the following steps of: acquiring protocol configuration information of the heterogeneous terminal input by a user through a visual interface, analyzing communication parameters and message rules in the protocol configuration information, and performing full-link visualization commissioning and testing on the protocol configuration information. Constructing a standardized protocol model instance; and initializing a communication server according to the communication parameters in the protocol model instance, and establishing a one-to-one mapping binding relationship between the network monitoring port and the protocol model instance. According to the method, the data flow of a network monitoring port is monitored, the corresponding protocol model instance is called based on the protocol routing rule to execute bidirectional data automatic conversion and full-link adjustment and test, a transparent test channel which is running as configuration is constructed, and the black box operation defect that rule definition and effect verification are separated in the past is overcome; and fusion and integration of massive stock terminals to a unified service platform are realized.

The invention discloses a bridge health monitoring system which comprises a sensing layer, a transmission layer, a processing layer and an application layer which are in communication connection in sequence. The sensing layer synchronously collects structural mechanics, environmental influence and traffic load data through multi-source heterogeneous sensing nodes, and the sensing nodes adopt a solar energy and vibration energy double-source energy supply and low-power-consumption mechanism; the transmission layer adopts a'wireless private network + edge gateway 'mixed mode, and has data caching and breakpoint resuming functions; the processing layer analyzes data through a deep learning fusion algorithm based on an attention mechanism, and realizes dynamic early warning threshold adaptive adjustment in combination with a Bayesian reasoning model; and the application layer provides a visual interface, graded early warning and targeted maintenance decision suggestions. The system achieves the precise monitoring of the full life cycle of the bridge, improves the evaluation accuracy and system stability, reduces the operation and maintenance cost, provides scientific support for the safe operation and maintenance of the bridge, is suitable for the health monitoring scenes of various bridge types, and greatly improves the accuracy of the evaluation of the health state of the bridge.

The invention belongs to the technical field of dike breach emergency rescue, and discloses a dike breach breach potential intelligent deduction and submerging probability visualization system and method and a medium. The engineering intervention deduction engine is constructed on the basis of a physically guided neural operator, takes a two-dimensional multi-physical reconstruction field containing pile body positions, material distribution, a flow velocity field and terrains as input, and directly outputs a water flow velocity-water depth physical field time history in a future time period; the online self-evolution engine is used for triggering fine adjustment of the model by comparing a deduction result with the deviation of real-time monitoring data; and the uncertainty quantification visual interface is used for dynamically displaying the deduction result in the form of a probabilistic submerging thermodynamic diagram. According to the method, a deduction framework integrating physical constraints and neural operators is created for the first time, the technical problems that traditional numerical simulation calculation is low in efficiency and pure data driving methods are physically inconsistent are solved, the unification of minute-level deduction speed and physical rule following is achieved, and real-time and reliable scientific decision support is provided for dike breach emergency rescue.

The invention discloses a data governance strategy dynamic execution system based on active metadata and AI recommendation, and relates to the technical field of data governance, and the system comprises an active metadata sensing layer which is used for actively monitoring and capturing metadata real-time changes of various data sources, and reporting the metadata real-time changes in a standardized data format; the intelligent analysis decision-making layer is used for receiving the standardized metadata, taking a preset knowledge base as a basic support, performing metadata association analysis by relying on an AI recommendation module, generating a governance strategy and converting the governance strategy into an executable instruction; the strategy dynamic execution layer is used for receiving an executable instruction, performing task splitting, priority ranking and dependency management through a workflow scheduler, and calling a corresponding executor to automatically complete execution of a governance strategy; and the unified management and control portal layer is used for providing a visual interface for an administrator so as to carry out treatment strategy approval, global monitoring, blood relationship analysis, audit query and manual intervention. According to the invention, intelligent generation and automatic execution of the data governance strategy can be realized.

The invention relates to an intelligent bid evaluation expert extraction method and system in the technical field of bidding and tendering information management. The method comprises the following steps: S1, constructing an expert multi-dimensional portrait; s2, receiving review project information, analyzing and calculating relevancy between a project demand vector and each expert capability vector, and screening candidate experts; s3, performing intelligent scheduling and priority ranking according to the historical response rate, attendance rate and evaluation of the candidate experts; s4, carrying out credible evidence storage on key data of the extraction process by utilizing a block chain, and ensuring tampering prevention and traceability of the extraction process and expert information; s5, at the appointed time and place before bid opening, decrypting and reviewing expert sensitive information under supervision, and completing confirmation and notification of a final expert group; the system comprises an expert database management module, a semantic matching module, an intelligent scheduling module, a block chain evidence storage module, a security decryption module and a visual interface. According to the extraction method and the system thereof, the precision, the intelligence and the security of expert extraction can be realized.

The invention discloses an automatic driving traffic accident intelligent analysis system based on sand table simulation, and relates to the technical field of vehicle automatic driving. The system comprises a sand table simulation scene construction module which is used for simulating a high-risk scene of an automatic driving traffic accident and providing a physical and digital twinborn combined experiment environment; the automatic driving data acquisition and perception module is used for acquiring vehicle sensor data in real time and realizing environment perception and behavior decision simulation; the traffic accident intelligent analysis core module is used for realizing accident cause analysis and responsibility determination based on multi-source data and a knowledge base; and the cloud control platform and data visualization module is used for monitoring sand table simulation data in real time and providing a visual interface and an interaction function. The system can simulate and analyze the performance of automatic driving in various complex traffic environments and perform analysis and prediction, the analysis and prediction accuracy is high, and the analysis effect is better.

The invention provides a multi-dimensional and dynamic digital assessment system and assessment method. Comprising a support module (comprising an index knowledge base, an algorithm operation base and an evaluation model base), a multi-source index fusion center (for constructing a three-dimensional data model and integrating a multi-dimensional data resource pool), a dynamic rule configuration engine (for realizing flexible configuration through a visual interface, a model adaptation mechanism and double-track verification) and a core business module (for managing assessment indexes, evaluating indexes and evaluating indexes). And evaluating the model and plan). The support module lays a basic resource layer, a fusion center constructs a data base, a configuration engine realizes flexible verification, the business module drives full-process execution, and full-process digital management from index creation, model configuration to examination execution is realized. The problems of iteration lag, multi-scene adaptation redundancy, weak data verification and the like of a traditional system are solved, index legality is guaranteed through static grammar detection and dynamic simulation operation, data traceability is achieved through a temporary database and full-link recording, and the dynamic response capacity, scene compatibility and data reliability of the assessment system are improved.

The invention provides a carbon emission source and boundary identification and accounting method, system and device and a medium, and belongs to the technical field of carbon emission management. The method comprises the following steps: collecting enterprise organization related information, including an organization structure, a business range, a financial statement and production process flow data; performing text formatting processing on the related information of the enterprise organization, inputting the information into a pre-training generation type large model based on a Transform architecture for analysis, and identifying carbon boundary and carbon emission source information of the enterprise organization; constructing an accounting method library containing a plurality of carbon emission source accounting methods, and analyzing and inputting emission source types, industry ranges, accounting formulas and required data suitable for each accounting method; according to the identified carbon emission source information, matching and screening are carried out by synthesizing semantics and rules, and an applicable accounting method is matched in an accounting method library; and issuing an identification result and a matched accounting method, and displaying the carbon emission source information and the accounting method through a visual interface.

The invention provides a universal method for realizing multi-condition and search based on LDAP, and belongs to the technical field of data retrieval of directory service and identity management. A user defines query conditions including attributes, values and logical relationships through a configuration file, a visual interface or an interface; the system parses the query condition model into a query condition model supporting nested combination of AND, OR and NOT by using a parser, and performs legality check and error prompt; and then a generator dynamically generates a filtering statement conforming to the LDAP grammar specification according to the model, and query is executed through an LDAP client. In order to improve the performance, common condition caching and high-frequency statement pre-compiling optimization are introduced, and an asynchronous query mode is supported. And the query result is returned in the form of structured data, and is matched with a display interface to support screening, sorting and exporting, so that the flexibility and maintainability of multi-condition query are improved.

The invention relates to the technical field of regulation and storage pool operation management, in particular to an interactive control method and system for urban regulation and storage pool operation management. The method comprises the following steps: acquiring geometric structure parameters of the storage tank; setting dynamic boundary parameters based on the geometric structure parameters; wherein the dynamic boundary parameters comprise a safe water storage upper limit, a suggested emptying water level and a forced emptying water level; constructing a three-dimensional interactive visual interface containing a space-time constraint relation according to the dynamic boundary parameters; and in response to an interactive working condition switching instruction input in the three-dimensional interactive visual interface, performing virtual execution verification, and after the virtual execution verification is passed, converting the equipment linkage rehearsal sequence into a control instruction and issuing the control instruction so as to realize operation management of the urban regulation and storage pool. By constructing the three-dimensional water level dynamic boundary mapping and equipment linkage virtual rehearsal mechanism, visual perception of working condition switching and water hammer resistance safety verification are achieved, and the problems that the operation opportunity is difficult to judge and the hidden danger of misoperation is caused are solved.

The invention relates to the technical field of cost analysis, in particular to a visual municipal engineering cost analysis system which comprises an interval wireframe construction module, a construction node positioning module, a budget map grid generation module, a node budget linkage module and a map structure display module. According to the method, cost values of construction units are divided according to interval step lengths, sorting and median difference evaluation are introduced, node positioning is performed in combination with a coordinate mapping mode, and a binding relationship between data and space is formed, so that budget information is subjected to partition homing and ordered stacking in a two-dimensional map; the construction unit construction cost distribution, the budget weight and the graph structure are dynamically fused and displayed in a visual interface, the construction unit construction cost and budget change can be quickly and synchronously adjusted by means of a linkage mechanism of a construction interval and graph grid coordinates, and position updating and graph block rearrangement after node addition and deletion are supported. And the data classification statistical efficiency, the node budget positioning precision, the budget adjustment response speed and the integration degree of map information display are improved.

The invention relates to an intelligent ship water diversion method and system based on RTK and inertial navigation fusion, and the method comprises the steps: firstly, deploying and calibrating an RTK base station at a wharf commanding height, generating a differential correction in real time, and broadcasting the differential correction to a shipborne end; utilizing RTK surveying and mapping equipment to collect shoreline feature points, adopting a cubic spline interpolation algorithm to construct a continuous and smooth three-dimensional shoreline curve model, and fusing wharf geographic information to generate a shoreline visual map with geographic coordinates; establishing a ship coordinate system, converting inertial navigation attitude data into the coordinate system through a rotation matrix and a translation vector, fusing the inertial navigation attitude data with RTK position data, and outputting a high-precision ship pose; fusion data are transmitted through a 5G network, a shore end converts the fusion data into a local plane coordinate system and generates a real-time dynamic visual interface, the real-time dynamic visual interface is pushed to a tug terminal through an RTSP protocol, water diversion operation is assisted, high-precision perception, visual guidance and shore ship cooperation of the ship berthing process are achieved, and the water diversion safety and the intelligent level are improved.

The invention discloses a visual interface display method and system for medical communication, and belongs to the technical field of medical communication visualization. The method comprises the following steps: acquiring an operation type, calling a corresponding scene template, synchronizing an image, completing three-dimensional reconstruction and generating an interactive anatomical model; main view real-time rendering is carried out, multi-dimensional data linkage display is realized, and a remote connection signal is obtained; when the remote connection is successful, allowing an expert to label the anatomical model; when abnormity is detected, risk early warning is triggered; calculating a network quality index, performing weighted calculation, and generating a network quality score; when the network quality score does not meet the communication condition, key anatomical feature points are extracted, and feature vectors are generated; traversing a feature database of the anatomical model, and matching with the feature vectors; positioning a focus area in the main view field, and executing area replacement logic; calling a medical network topology library, and screening alternative networks; and when no single network in the topological structure meets the requirement, starting a link aggregation mechanism.

The invention provides a data consanguinity management system supporting multi-source heterogeneous data dependency analysis. The system comprises an automatic data analysis module, a consanguinity collecting and updating module, a fine-grained dependency analysis module and an interactive consanguinity analysis module. Wherein the automatic data analysis module is used for acquiring multi-source heterogeneous data and automatically analyzing the multi-source heterogeneous data to generate target standardized metadata; the blood relationship acquisition and updating module generates blood relationship data through static analysis, dynamic analysis and message queue acquisition; the fine-grained dependency analysis module performs dependency analysis from the table level and the field level to generate fine-grained dependency analysis data; and the interactive blood relationship analysis module performs interactive tracing based on the data and constructs a visual interface. Through cooperation of the four modules, automatic processing, fine-grained dependency analysis and real-time dynamic updating of multi-source heterogeneous data are achieved, and the accuracy and efficiency of data management are improved.

The invention discloses a hoisting equipment distribution visualization and monitoring method, and relates to the technical field of industrial hoisting safety, and the method comprises the following steps: generating a synchronously associated multi-source fusion data set; constructing a three-dimensional basic model of the hoisting operation area; dividing the three-dimensional dynamic model into a base layer, an equipment layer, a key component layer and a data layer by adopting a self-adaptive hierarchical rendering algorithm, adjusting the rendering precision of each layer according to a priority coefficient, and generating an equipment distribution visual interface; identifying an abnormal state of the equipment and positioning a fault position, and triggering a corresponding grading early warning signal according to an abnormal grade; and based on the abnormity type and the fault position corresponding to the early warning signal, a targeted disposal suggestion scheme is generated. The real-time monitoring, fault early warning and three-dimensional dynamic visualization of the hoisting equipment are realized by fusing space-time alignment, multi-source data synchronization, a digital twinning technology and a self-adaptive rendering algorithm, and the equipment safety and the operation efficiency are remarkably improved.

The invention relates to the technical field of thunder and lightning monitoring and protection, in particular to a thunderbolt positioning and energy analysis method and system based on a lightning rod monitoring network. The method comprises the following steps: collecting and verifying a lightning current waveform and a microsecond timestamp in real time, and measuring grounding resistance regularly; the terminal carries out filtering analog-to-digital conversion on the signal and extracts characteristic parameters, after packaging, the priority is set according to the current amplitude, and the priority is uploaded to the cloud platform; the cloud platform is associated with multi-terminal synchronous data, when the number of effective terminals is not less than three, coordinates of a thunderbolt point are calculated, integral operation is performed on a lightning current waveform in combination with actually measured grounding resistance to quantify single-time lightning stroke energy, and historical data are analyzed by using a long-short-term memory network model to realize equipment health diagnosis and life prediction. And displaying the thunderbolt point distribution thermodynamic diagram and the state evaluation report through a visual interface. According to the invention, the whole process management from data acquisition to intelligent decision making is realized, and the accuracy and predictability of lightning monitoring and protection are improved.

The invention provides a man-machine interaction safety dynamic early warning method based on digital twinning and behavior prediction, and the method comprises the steps: S1, collecting the real-time data of a working site through a sensing layer, and enabling the data to comprise the personnel position, equipment state and environment information; s2, constructing a digital twin model based on the acquired data, wherein the model maps the dynamic state of a working site in real time; s3, generating a personnel behavior track and an equipment action range through a prediction algorithm, and calculating a dynamic risk field to evaluate space-time conflicts; s4, according to the risk value of the dynamic risk field, triggering a multi-stage early warning mechanism to reduce the risk of the operation field; and S5, displaying the real-time state and risk information in the digital twinborn model through a visual interface. According to the invention, through deep fusion of digital twinning and dynamic risk prediction, real-time monitoring and accurate prevention and control of the safety risk of the operation site are realized, and the safety management efficiency and the operation safety are greatly improved.

The invention provides a power plant carbon emission data full life cycle management method and device, and relates to the technical field of data processing, and the method comprises the steps: collecting production, fuel and coal quality test system multi-source data in real time through a standard interface, and forming a dynamic data flow; predicting the carbon content of the fire coal element based on a BP neural network, and calculating the carbon emission by combining an emission factor method; carrying out back calculation on the discharge amount by using a mass balance method, analyzing and verifying the relevance between data and an accounting result through multiple regression, and triggering correction when an error exceeds a threshold value; a double-stage attention deep learning network is adopted to predict the carbon price in a rolling mode, a carbon asset dynamic analysis result is generated in combination with a quota estimation model, real-time emission data, quota surplus and shortage and the carbon price trend are displayed through a visual interface, and graded early warning is conducted on abnormal data. According to the method, full-life-cycle automatic management is realized, the data acquisition real-time performance and accounting precision are improved, the data authenticity and traceability are guaranteed, and the carbon asset management decision support capability is optimized.

The invention provides a medical data sharing interface based on a standardized API and a low-code construction method. The method comprises the steps that a set of standardized medical core data models is predefined; a unified data sharing service API layer is constructed, an adapter used for being in butt joint with a heterogeneous medical data source and converting the heterogeneous medical data source into data matched with a predefined model format is configured, and an API interface is generated based on the predefined model; a component library is preset through a visual interface configuration platform, each component in the component library is bound with a field of a predefined model, the components are arranged and / or combined in a dragging mode, and a data binding relation between the components and an API interface is configured; and analyzing and generating a structured interface description file according to the information of visual interface construction and configuration, dynamically loading the interface description file through an engine when a client runs, calling an API (Application Program Interface), and rendering a final user interface. According to the scheme, the development cycle can be shortened, the ability threshold of developers can be reduced, and good expandability is achieved.

The invention discloses a hydropower station intelligent supervision method based on AI analysis, and relates to the technical field of hydropower station data analysis. The hydropower station intelligent supervision method and system based on AI analysis comprises the following steps: S1, collecting ecological environment parameter information, and establishing an ecological environment database; s2, establishing an ecological demand model based on historical data and biological rules, and executing ecological adaptation judgment; s3, ecological deviation evaluation is executed on the ecological environment data with the qualified ecological adaptation judgment result; s4, ecological environment data, an ecological adaptation judgment result and an ecological deviation evaluation result are integrated, and ecological release regulation analysis is carried out; and S5, providing a visual interface to display the change state of the ecological response adaptation value in real time. The problems that ecological perception is insufficient, regulation and control depend on fixed rules, supervision lacks intelligent response and closed-loop feedback, and dynamic adaptation cannot be achieved according to real-time ecological data and seasonal requirements are solved.