355 results about "Assessment data" patented technology

The invention relates to the technical field of data acquisition, and discloses a multi-protocol extensible data acquisition system architecture and method with a unified interface standard, and the architecture comprises a data source management module which is used for storing data source configuration information and distributing protocol identifiers; the protocol adaptation module comprises an analysis unit and a matching unit and is used for realizing data format conversion and protocol compatibility verification; the data conversion module is used for generating target data through format conversion and semantic mapping; the data verification module and the anomaly detection module are used for comparing and monitoring data integrity based on an integrity algorithm and a threshold value; the data quality monitoring module and the early warning module are used for comparing and evaluating data quality through a consistency model and a threshold value; and the result output module transmits the early warning information to a target system. The method comprises the steps of data source configuration, protocol adaptation, data conversion, integrity and quality monitoring, early warning and the like. The system expansibility and the data reliability are improved, and the method is suitable for multi-scene data acquisition.

The invention relates to the technical field of water and fertilizer control, in particular to a water and fertilizer integrated control system and method based on the Internet of Things. The method comprises the following steps of obtaining environment measured data, historical environment data and regional geographic information of a farmland region, performing spatial modeling and time sequence learning on the farmland region, and constructing a farmland digital twinborn model; simulating the state of an area without sensors by using a farmland digital twinborn model to obtain virtual sensing node data; collecting multispectral image data of crops, and extracting physiological feature data of the crops; and constructing a crop physiological state model by utilizing the environment measured data, the virtual sensing node data and the crop physiological feature data, and generating crop physiological state evaluation data. Through multi-source data fusion and three-dimensional visualization integration, data-driven accurate regulation and control and whole-process intelligent management of the water and fertilizer integrated system are realized, and the intelligent level of irrigation and fertilization and the resource utilization efficiency are comprehensively improved.

The invention provides a reservoir water ecological health diagnosis method and system, and relates to the technical field of reservoir ecological monitoring, and the technical scheme is characterized in that the method comprises the steps: obtaining water quality parameters, biological indexes and environmental data collected by distributed sensors in a reservoir; according to the water quality parameters, the biological indexes and the environmental data, generating reservoir ecological health assessment data through a data fusion algorithm; calculating a reservoir ecological health assessment index according to the reservoir ecological health assessment data; according to the reservoir ecological health assessment index, generating a reservoir ecological health state assessment result; judging whether the ecological state of the reservoir is abnormal or not according to the evaluation result of the ecological health state of the reservoir; and when the ecological state of the reservoir is abnormal, generating an early warning signal. The reservoir water ecological health diagnosis method and system provided by the invention have the advantages that multiple ecological pressure factors are comprehensively considered, and a complex water ecological system is rapidly and accurately evaluated.

The invention discloses an electrophysiology and hemodynamics multi-mode intelligent wearable system and a data evaluation method, and belongs to the technical field of biomedical engineering, the system comprises an optical module, a flexible stretchable electric signal module and a central module; the optical module is used for collecting hemodynamic signals including an oxyhemoglobin change signal, a deoxygenated hemoglobin change signal and a pulse wave signal by combining a near-infrared light signal with hemodynamics; the flexible stretchable electric signal module collects electric signals, including electroencephalogram signals, electromyographic signals, electrocardiosignals and electro-oculogram signals, of all parts through electrodes; the central module is used for digitalizing and preprocessing the hemodynamic signal and the electric signal of each part, fusing multi-modal data, evaluating data quality and predicting a dominant external event influencing the data quality; and meanwhile, data quality and dominant external events are output to the terminal to feed back and adjust acquisition parameters of the optical module and the flexible stretchable electric signal module, so that the effectiveness and practicability of monitoring are remarkably improved.

The invention discloses a dynamic weight aggregation federated learning method and system for credit risk assessment, and the method comprises the steps: firstly, calculating the cosine similarity of each client model and the last gradient of a global model, so as to assess the consistency of model parameters; secondly, the distribution difference is quantified by calculating the data statistic difference between each client data and the global data, so that the diversity of the data is evaluated; further, a contribution degree comprehensively considering model parameter similarity and data distribution difference is obtained by combining a hyper-parameter with cosine similarity and data distribution difference; and finally, dynamically adjusting the weight of each client in global model updating according to the contribution degree of each client, so that the model pays more attention to the client with higher data quality, thereby improving the overall model performance. The federated learning method is especially suitable for processing non-independent identically distributed data, optimizes the generalization ability of the model, and is suitable for credit risk assessment in the financial field.

The invention discloses an intelligent breeding method for commercial crops based on big data analysis, and relates to the technical field of agricultural breeding, the method comprises the following specific steps: seed multi-modal data acquisition and processing: acquiring physical characteristic data of seeds, acquiring physiological indexes and genome information data through biochemical experiments and gene sequencing, and determining the seed multi-modal data according to the physiological indexes and the genome information data; carrying out pretreatment on the raw materials; according to the method, after multi-modal data are integrated and preprocessed, a seed vigor accurate evaluation model is constructed by using deep learning and data fusion technologies, the seed vigor level can be measured more accurately, and meanwhile, the electric signal change of the early growth stage of crops is monitored in real time by using high-precision plant electric signal acquisition equipment, so that the accuracy of the seed vigor evaluation is improved. And a correlation model of the electric signal characteristics and multiple traits of crops is established, and fusion analysis is performed on seed vigor evaluation data and plant electric signal data, so that the breeding efficiency is greatly improved, and powerful support is provided for cultivation of high-quality varieties.

The invention discloses an intelligent safety inspection system for a construction site, and relates to the technical field of construction inspection, multiple data sources of the construction site are obtained through a data acquisition module, and a data fusion and processing module dynamically optimizes heterogeneous data through time synchronization, format standardization and noise filtering in combination with a self-adaptive weighted fusion algorithm, so that the construction site safety is improved. The intelligent analysis and early warning module evaluates the data difference degree based on machine learning, adopts clustering analysis to mine an abnormal mode for high-difference data, carries out safety risk identification on low-difference data, and dynamically adjusts an early warning strategy. The terminal interaction module pushes the inspection result and the early warning information to the mobile terminal APP, the monitoring center display screen and the voice broadcast device, so that a manager can remotely check the construction condition and quickly make a decision, the intelligent level of construction site safety inspection can be remarkably improved, efficient and accurate potential safety hazard recognition and dynamic early warning are achieved, and the safety inspection efficiency is improved. And the safety accident risk is effectively reduced.

The invention provides a data quality detection and improvement system for a large language model, and relates to the technical field of code quality management. The data analysis and characteristic extraction module is used for extracting structured and semantic characteristics of codes and constructing a code distribution diagram; the multi-dimensional quality detection module comprehensively evaluates the data set quality from three aspects of semantic diversity, structural consistency and error mode; the code optimization and verification module generates an optimization suggestion based on a detection result, and verifies the effectiveness of an optimization scheme through dynamic evaluation and unit testing; the feedback and self-adaptive optimization module is combined with developer feedback and runtime performance test to dynamically adjust a repair strategy, and the complex code repair efficiency is improved through quantum computing auxiliary path search; according to the method, full-process automation from quality detection to optimization verification is achieved, the method is suitable for multi-dependency and multi-module complex code repair tasks, and the quality and efficiency of the code life cycle are improved.

Computer-based techniques for performing systematic literature reviews are provided. Some embodiments include an SLR system including various components that interoperate to generate regulation-compliant SLR reports regarding an issue based on user-defined parameters. In several embodiments, the SLR system may integrate various artificial intelligence techniques to facilitate generation of SLR reports. For example, various SLR systems disclosed hereby may utilize generative pre-trained transformers to assist in aspects of systematic literature reviews, such as literature database queries, literature screening, data question generation, level of evidence classification, qualitative assessments, data extraction, and report generation.

The invention relates to the technical field of power equipment monitoring, and discloses a hydropower station high-altitude equipment fault intelligent identification system based on multi-sensor fusion, which collects multi-modal data in real time and evaluates data quality by deploying multi-source sensors at key parts of high-altitude equipment. Extracting multi-scale features of each modal, performing normalization processing, calculating a fusion weight based on feature saliency and data credibility, and performing weighted fusion and dimension reduction on the multi-modal features; based on the fusion feature vector, intelligent matching analysis of fault features and intelligent identification of fault types are carried out; a fault identification result is obtained; in addition, the system also comprises safety monitoring of overhead working personnel, and realizes closed-loop management from fault identification to safety maintenance. According to the invention, early weak faults can be accurately identified, and the safe operation level of equipment and the intelligent degree of operation safety management are improved.

The invention relates to the technical field of industrial safety management, in particular to an intelligent security monitoring and responding method for a power generation enterprise. The method comprises the following steps: acquiring environmental data of a power generation enterprise; performing enterprise abnormal event detection on the power generation enterprise environment data to obtain enterprise environment abnormal event data; performing multi-source video linkage monitoring on the enterprise environment abnormal event data to obtain multi-angle video data; and performing abnormal event analysis according to the enterprise environment abnormal event data and the multi-angle video data to obtain abnormal event risk assessment data so as to perform intelligent security monitoring and response auxiliary operation of the power generation enterprise. According to the method, the abnormal event detection and analysis capability is improved, and the safety and the operation efficiency of an enterprise are also remarkably improved.

The invention relates to the technical field of power supply system health assessment, in particular to a health assessment method and system of a power supply system based on artificial intelligence. The method comprises the following steps: acquiring data of a power supply system, estimating initial performance parameters of the power supply system, evaluating an initial running state of the power supply system, and acquiring initial state data of the power supply system; performing power supply equipment load operation simulation based on the initial state data, and predicting a fault evolution trajectory; the transmission quality attenuation degree of the power supply system is estimated by analyzing the fault evolution trajectory of the power supply system, the loss increase trend of a transmission line is detected, and the performance decrease trend is evaluated in combination with the attenuation degree; evaluating health attenuation data of the power supply system according to the performance reduction trend; transmitting the data to an artificial intelligence model for deep learning training to obtain accurate power supply system health state evaluation data; according to the invention, health analysis is carried out on the power supply system, so that the power supply system is safer and more stable.

The invention discloses a multifunctional safety helmet management system and method based on the Internet of Things, relates to the field of safety production, and solves the problems that a traditional safety helmet is single in safety management function, insufficient in data processing precision and the like. A multi-dimensional state data sequence is continuously collected through a three-axis acceleration sensor, a temperature and humidity sensor, a positioning sensor, a vital sign sensor and the like integrated on the safety helmet terminal; terminal monitoring characteristics including an acceleration module value, a position drift distance and a physical sign fluctuation index are constructed, data reliability is evaluated through weighted fusion of dynamic fluctuation values, and an abnormal terminal is isolated. And carrying out space-time calibration on the reliable data to generate a unified coordinate system trajectory, analyzing and identifying abnormal behaviors through group trajectory consistency, and constructing a regional safety risk map in combination with a signal blind area coverage rate, thereby realizing safety risk level prediction based on historical data and real-time trajectory matching. According to the invention, comprehensive real-time monitoring of the state of the operator is realized, and the intelligent level of safety production management is improved.

The invention discloses a BIM application method and system in cost management. The method comprises the steps of BIM model construction, cost data integration, engineering quantity list and cost report generation, collaborative management, AI real-time optimization, digital twinborn early warning management, design change and contract text analysis, edge calculation cost management, block chain data guarantee and the like. The system comprises a plurality of modules such as a BIM model construction module and a cost data integration module. According to the method, software is utilized to generate a BIM model, cost data is integrated, data quality is evaluated before a report is generated, multi-specialty and multi-participant authority is cooperatively managed, AI real-time optimization, digital twinborn early warning, a natural language processing engine analyzes a change document, cost is processed through edge calculation, safety protection is achieved, and data is guaranteed in combination with a block chain. Compared with the prior art, the construction cost calculation accuracy is improved, personal errors are reduced, the association between the component and the construction cost data is enhanced, the change response efficiency is improved, and the data transmission delay is reduced.

The invention discloses a course recommendation method and system for intelligently building an education platform, and relates to the technical field of intelligent education informatization, and the method comprises the steps: building a knowledge graph, and completing the multi-level association of tasks and knowledge points; analyzing the assessment data, identifying weak knowledge points of the trainees, and setting score threshold fusion post weights; generating a course recommendation result on the basis of recognizing weak knowledge points of students, and optimizing recommendation logic in real time by adopting feedback; according to the method, a knowledge graph model associated with three layers of tasks, knowledge points and posts is constructed, student examination performance and post skill requirements are fused, and a course recommendation path construction mechanism driven by a multi-dimensional weight is realized; a dynamic feedback and real-time scoring algorithm is adopted, closed-loop logic of recommendation, assessment and re-recommendation is established, recommendation individuation and post matching degree are effectively improved, and the problems that knowledge points in an existing platform are not traceable, post adaptability is weak, and a recommendation strategy is single are solved.

The invention relates to the technical field of training simulation, and discloses a VR-based gas safety emergency training system, which comprises a three-dimensional scene construction module, an interactive data acquisition module, an interactive data processing module, an examination data analysis module and an examination evaluation module, entity drilling is replaced, the same scene can be repeatedly trained for infinite times, and the training cost is remarkably reduced; the VR technology provides multi-sensory stimulation, the intuitive cognition of students on danger is enhanced, the safety awareness and the emergency response capability are effectively improved, and no danger exists; by collecting operation data of students, the system automatically calculates key coefficients such as equipment operation precision, process compliance, disposal timeliness and path planning rationality, and scientific quantification and accurate scoring of training effects are achieved; and automatic grading evaluation is carried out according to a grading result, and a customized remedy module is triggered for students with insufficient abilities, so that a'training-assessment-intervention 'closed loop is formed, and the overall training efficiency is improved.

The invention discloses a BIM-based bridge construction monitoring method and system, and belongs to the technical field of bridge construction. Construction time deviation characteristics and structure response deviation characteristics are extracted, a drift index is calculated to evaluate the binding error degree between data and components, and a differential processing strategy is implemented based on the drift level; and for high-risk data, a similarity scoring mechanism is introduced, an intelligent matching algorithm is adopted to identify an optimal component and complete rebinding, and finally accurate storage of the data and dynamic updating of a BIM model state are realized, so that the binding accuracy of the construction monitoring data, the risk identification capability and the model linkage efficiency are effectively improved, and the construction quality is improved. And the intelligent management and decision support level of bridge construction is enhanced.

One embodiment of a method comprises continuously collecting cross-sector data related to geopolitical risk from a worldwide network to update a risk assessment dataset the comprises a series of risk assessment states for a plurality of geopolitical entities in time increments; selecting forecasting risk assessment data from the risk assessment dataset; processing the forecasting risk assessment data using an inquisitive artificial intelligence engine to identify a pattern and trend in the forecasting risk assessment data and use the pattern and trend to forecast risk assessment variable values for an first entity; and generating a user interface comprising an interactive map for a user, the interactive map embodying the forecasted risk assessment variable values to display a forecasted risk for the first entity to the user in association with the first entity in the user interface.

The invention discloses a water feed pump fault diagnosis system, which belongs to the field of data analysis and is characterized in that real-time operation data of a water feed pump are acquired by adopting a synchronous acquisition strategy, an operation database is constructed, and when a data record is newly added, detection and self-adaptive judgment are performed to determine an early warning decision; when abnormal early warning of the water feeding pump is detected, screening a fault assessment set for fault identification based on the operation database, and performing information fusion on fault assessment data to obtain a fault assessment feature set; and performing comprehensive time sequence analysis on the preliminary fusion data of each fault evaluation subset to obtain a key part fault evaluation score so as to judge a fault, for the key part judged as the fault, obtaining a fault source by constructing a time axis, and constructing a fault propagation path in combination with a correlation coefficient matrix. The technical problems of synchronization and exception handling during collection of multi-source information, targeted screening and effective integration during fusion, and discrimination and traceability during fault diagnosis are solved.

The invention belongs to the technical field of video quality evaluation, and particularly relates to a video quality evaluation method based on spatio-temporal feature fusion. Comprising the following steps: acquiring a video quality evaluation data set, preprocessing the video quality evaluation data set, and processing preprocessed video data by adopting a time feature extraction module to obtain short video features and long video features; processing the preprocessed video data by adopting a spatial feature extraction module to obtain high-level semantic features and distortion features; fusing the short video features, the long video features, the high-level semantic features and the distortion features by using a feature fusion module to obtain fused features; inputting the fusion feature into a multi-layer perceptron for processing to obtain a video quality score; calculating the total loss of the model and continuously adjusting model parameters according to the total loss of the model to obtain a trained video quality evaluation model; performing video quality evaluation by using the trained model; according to the method, the correlation between the spatial-temporal features and the inter-frame features is effectively utilized, so that the accuracy of quality evaluation is improved.

A system, method, and computer programmable product for assessing a virtual interaction is provided. The system is configured to retrieve assessment data, wherein the assessment data comprises at least one of: a plurality of assessment parameters, and a weightage score associated with each of the plurality of assessment parameters. The system is further configured to retrieve response data of a candidate associated with the assessment data. The system is configured to generate, using a trained AI model, a score for the response data based on the assessment data. Further, the system is configured to obtain user input based at least on the score of the response data and update the weightage score associated with at least one of the plurality of assessment parameters based on the user input, wherein the AI model is re-trained based on the updated weightage score.

The invention discloses a black land water and soil resource bearing capacity evaluation system based on big data, which relates to the technical field of agricultural production and comprises a data acquisition module, a data preprocessing module, an evaluation index calculation module, a bearing capacity evaluation model module and a result analysis and display module. The data acquisition module is used for acquiring soil data, water resource data and social economic data of black land. According to the evaluation system for the bearing capacity of the water and soil resources of the black land, through integration of multi-source heterogeneous data, comprehensive and accurate evaluation of the bearing capacity of the water and soil resources of the black land is achieved, high-density deployment and real-time updating of the data acquisition module are achieved, the temporal-spatial resolution and reliability of an evaluation result are ensured, and the evaluation accuracy is improved. The problem of insufficient data acquisition density in the prior art is effectively solved, a data preprocessing and evaluation model construction technology is adopted, the dynamic adaptability and prediction precision of an evaluation model are improved, and visual and understandable chart display and decision support information are provided.

The invention relates to a wound nursing image intelligent evaluation system and a method thereof, which are applied to the field of medical image processing, and comprise an image acquisition module, a differential geometry-based feature extraction network module, a data analysis module and a user interaction module, the feature extraction network module based on differential geometry comprises a wound geometric characterization layer, a multi-scale feature analysis layer and a tissue classification decision-making layer, a two-dimensional image of the wound is mapped into a three-dimensional geometric surface, curvature features and differential invariants are extracted based on the differential geometry theory, accurate assessment of the wound is achieved, and the tissue classification decision-making efficiency is improved. The data analysis module generates nursing suggestions and evaluation results according to the extracted wound feature data, the differential geometry theory is innovatively applied to the field of wound evaluation, and the problem that the precision is limited when a traditional method is used for treating a wound with a complex shape and irregular edges is effectively solved; the system has the characteristics of high evaluation accuracy, strong anti-interference capability and high automation degree, and the efficiency and quality of wound evaluation and nursing are remarkably improved.

The invention discloses a data value evaluation method based on a data blood relationship, and relates to the technical field of data processing. The method comprises the following steps: constructing data blood relationship map data based on sensor metadata, communication protocol characteristics and a data blood relationship; obtaining a data value dynamic sorting result; constructing a monitoring index, importing the monitoring index into a tool to configure a data quality automatic monitoring tool, and obtaining a data exception intelligent detection result of the focused data node by using the data quality automatic monitoring tool; and performing data error repair and data processing flow optimization by using the block chain consensus and generative adversarial network to obtain a final data value evaluation result. According to the method, the data blood relationship graph can be efficiently constructed, the data value can be evaluated, the data quality can be monitored, and the data management strategy can be optimized, so that more accurate and reliable data support can be provided for decision making in intelligent traffic.

Described herein are methods and systems for evaluating datasets through a multi-faceted scoring approach that assesses data quality across multiple dimensions. A trust score for a dataset may be generated by a scoring engine and displayed on a user interface, providing a comprehensive assessment of the dataset's readiness for use in artificial intelligence applications. The trust score incorporates multiple dimensions including diversity, timeliness, accuracy, security, discoverability, and LLM-readiness, offering users quantitative insights into dataset quality. This scoring system enables organizations to identify high-quality datasets suitable for AI model training, reducing the risk of poor model performance due to inadequate data. The visualization of trust scores through intuitive interfaces allows data scientists, analysts, and other stakeholders to quickly assess and compare datasets, facilitating more informed decision-making in AI development processes.

The invention relates to the technical field of data processing, and discloses a full-life-cycle-oriented engineering technology data governance method and a full-life-cycle-oriented engineering technology data governance system. The method comprises the steps that project object attributes are divided into an anchor point attribute set and an extended attribute set, a locking mark is added to the anchor point attribute set, the extended attribute set is layered according to stages to obtain a data object meta-model, a dependency relationship mapping table is established according to the data object meta-model to achieve automatic verification when the attributes are changed, and the attribute change is completed. And establishing a spatial topological graph and a process graph to diagnose inconsistent defects, establishing a weighted graph to quantitatively analyze change influences, evaluating data quality according to scene types, and intelligently complementing missing attributes. According to the method, the integrity and consistency of cross-stage transmission of engineering data, the real-time performance and accuracy of multi-professional data collaboration, the depth and automation degree of data quality diagnosis, the scientificity and comprehensiveness of change impact analysis and the flexibility and efficiency of data utilization are improved.

The invention relates to the technical field of data management, and discloses a business and financial data governance optimization method for main data dynamic management, which comprises the following steps: step 1, carrying out multi-source data acquisition, including business system data acquisition, financial system data acquisition and other channel data acquisition, step 2, pre-processing the acquired data, numbering and storing, and step 3, carrying out data management on the acquired data. 3, calculating a data quality index, a data change condition, a data value and a data comprehensive coefficient based on the stored data set, and 4, performing feedback according to the data comprehensive coefficient, so that various data sources inside and outside an enterprise can be comprehensively covered, a data island phenomenon is reduced, and meanwhile, the quality and credibility of data are improved; the data comprehensive coefficient is comprehensively evaluated by combining the data quality index, the data change condition and the data value, the data level is comprehensively reflected, a comprehensive perspective is provided for enterprises to see the data, and the enterprises can better understand and manage the data and find potential problems and opportunities.

The invention relates to the technical field of intelligent teaching, and provides a self-adaptive personalized teaching system based on AI and a knowledge graph, and the system comprises a knowledge graph construction module, a student portrait module, a self-adaptive recommendation module, a teaching interaction module, and a management module. The knowledge graph construction module comprises a data processing unit, a knowledge extraction unit and a graph storage unit; the data processing unit is used for carrying out preprocessing such as word segmentation and stop word removal on the teaching text; and the knowledge extraction unit is used for extracting knowledge point entities and relationships between the entities from the preprocessed text through a natural language processing technology. The knowledge points are subjected to fine-grained modeling through the knowledge graph, the AI algorithm is combined to analyze student learning behaviors and evaluation data, knowledge vulnerabilities and learning characteristics of students can be accurately captured, the error rate is lower than that of a traditional method, the self-adaptive recommendation module generates personalized learning paths based on the reinforcement learning algorithm, and the learning efficiency is improved. And repeated learning of students on invalid knowledge points is avoided.

The invention relates to the technical field of engineering digital management, in particular to an engineering project digital asset management method and management platform. The method comprises the following steps: performing engineering digital asset quality evaluation processing on engineering digital asset data to generate engineering digital asset quality evaluation data; performing engineering digital asset collaborative application heterogeneity feature analysis based on the historical engineering digital asset application data to generate engineering digital asset collaborative application heterogeneity feature data; carrying out the optimal distribution strategy analysis of the full-life-cycle engineering digital asset application on the full-life-cycle engineering digital asset application data through the engineering digital asset collaborative application heterogeneity feature data, and generating a full-life-cycle engineering digital asset application optimal distribution strategy; and based on the engineering digital asset quality data and full-life-cycle engineering digital assets, applying an optimal distribution strategy to execute engineering digital asset intelligent management operation. According to the invention, intelligent operation and maintenance optimization management of engineering project digital assets is realized.

The invention relates to a scene-based data asset evaluation method and system. The method comprises the following steps: step 1, evaluating a scene in which data assets can be used; 2, calculating the contribution degree of a single determined scene; 3, single evaluation is carried out to determine the number of scenes; 4, calculating a scene correction coefficient; 5, evaluating a data asset value; according to the method, evaluation is carried out by adopting the scene number, the scene contribution degree and the correction coefficient, the requirements and evaluation of a cost method, a benefit method and a market method for data quality are reduced, the core of data asset evaluation is powerfully grasped, and an accurate and reliable basis is provided for data asset evaluation.