294 results about "System evaluation" patented technology

A computerized system for dynamic cybersecurity policy using AI-based contextual adaptive learning includes an AI system that evaluates business contexts, risk tolerance, and productivity impact to generate threat intelligence assessments. The system includes a Contextual Adaptive Learning module that dynamically adjusts cybersecurity policies based on threat assessments to create security workflows. A Cybersecurity Mesh Development module that integrates policies across security frameworks. A Dynamic Scenario Catalog module that updates policy adjustments based on threat intelligence. An Automated Workflow Orchestration module that creates and refines security workflows for optimal efficiency. A Policy Recommendation and Automation module that generates prioritized security recommendations and automates policy changes based on organizational risk profiles and current security controls. This system harmonizes security policies while considering business context, risk, and productivity impacts.

The invention provides an intelligent automobile test case automatic generation and evaluation system, device and product, and relates to the technical field of intelligent automobile test.According to the system, domain knowledge support is provided through a test knowledge base, and a demand understanding module is combined with a fine-tuning large model to deeply analyze demands; function points are extracted, and hidden scenes such as sensor faults and multi-system cooperation are identified; the test case generation module is based on a special prompt template and few-sample learning, a complete case containing elements such as purposes, steps and data is generated by fusing a vehicle model configuration library, and the specialty and the performability are ensured; and the evaluation module realizes objective quality evaluation through multi-dimensional quantitative scoring of demand coverage rate, scene integrity, risk coverage degree, normalization and the like. All the modules cooperate to realize intelligent generation and system evaluation of test cases, and the automation level, coverage range and reliability of intelligent automobile testing are improved.

The invention discloses an unmanned aerial vehicle random patrol strategy system evaluation method in a confrontation environment. The method comprises the steps of setting an unmanned aerial vehicle intelligent patrol attack and defense confrontation system and a target steady-state distribution model of the unmanned aerial vehicle intelligent patrol attack and defense confrontation system; determining the average strategy entropy of the patrol person; determining conditional probability differences of the patrol persons; determining a transfer strategy dispersion degree of the patrol person; a patrol strategy comprehensive structure difference index is determined; determining a single-time-point key state average relative error; determining the average relative error of the time average key state; and determining a time-weighted key state average relative error. According to the method, the comprehensive structure difference index of the difference between the single-state transition matrix and different matrixes is quantified, and a balanced framework is provided to evaluate the overall unpredictability of the strategy. A multi-dimensional evaluation system based on key state and time weighting is designed, and time importance is directly fused into error calculation through a key state screening mechanism.

The invention discloses an intelligent item selection recommendation system of a live broadcast room based on AI digital people, relates to the technical field of intelligent item selection recommendation, and solves the technical problems of generating a dynamic and high-confidence matching scheme based on highly matched commodities and adjusting a combination strategy in combination with a real-time scene and user feedback. Through the multi-dimensional weighted calculation of the feature matching score, the crowd matching score and the scene association score, the hidden integrating degree of the commodity and the user demand is quantified, the highly matched commodity is screened out, the invalid recommendation is reduced, the comprehensive confidence degree of the commodity combination is calculated based on the association rule algorithm, the personalized matching scheme conforming to the real-time scene is generated, and the user experience is improved. A high-potential scheme is screened through a self-adaptive threshold value, the matching rationality and transformation potential are improved, a comprehensive feedback processing module is introduced, a user is supported to customize combined commodities, and optimization suggestions are provided through system evaluation; and for user change feedback, generating hidden collocation based on a user portrait, and realizing real-time iteration of a recommendation scheme.

The invention discloses a power supply service intelligent management system, and relates to the technical field of intelligent power grids, and the system comprises a power grid holographic sensing module which obtains multi-dimensional unstructured data of a power system, extracts core features through cross-domain fusion analysis, and generates a power grid real-time operation state map; the equipment health twinning module is used for constructing an equipment health model in combination with a digital twinning technology and outputting an equipment fault early warning signal and a residual life prediction value; the customer energy efficiency service module is used for analyzing the association relationship and then generating a personalized energy efficiency optimization scheme and a power utilization suggestion; and the dynamic scheduling decision module is used for generating a power grid optimal scheduling strategy and an emergency response scheme. The power grid holographic sensing, digital twinning technology, dynamic scheduling, block chain and encryption technology are utilized, the power system is monitored in real time, equipment health is evaluated, faults are predicted, power utilization, energy conservation and emission reduction are optimized, data safety and stable operation of the system are ensured, and the cooperation efficiency of power enterprises and users is improved.

The invention belongs to the field of energy storage system evaluation, and particularly provides a compressed air energy storage system state evaluation method based on digital twinning, in the method, a multi-physics field coupling digital twinning model is constructed based on a compressed air energy storage system, and a time sequence modeling module based on an LSTM-Transformer hybrid architecture is built in the digital twinning model; based on the calibrated digital twinborn model, state evaluation is carried out on the compressed air energy storage system in combination with a preset evaluation dimension, simulation deduction data of the digital twinborn model and real-time operation data of a physical system are fused in the evaluation process, and an evaluation result is obtained and output; and based on an evaluation result, triggering an uncertainty quantification result based on an LSTM-Transform architecture to carry out graded state early warning. According to the method, the multi-physics field coupling digital twinborn model is constructed and dynamically calibrated, simulation deduction, real-time data evaluation and graded early warning based on uncertainty quantification are fused, and the compressed air energy storage system state evaluation precision, real-time performance and early warning credibility are improved.

The invention discloses a cultivated land ecological safety comprehensive evaluation method and system based on multi-model coupling. The method comprises the steps that a future multi-source data set of cultivated land to be evaluated in a future time period is set; performing grid division on the cultivated land to be evaluated by adopting a grid calculator in ArcGIS software to obtain a plurality of grid regions, and performing grid division on the future multi-source data set based on the plurality of grid regions to obtain a future multi-source sub-data set of each grid region; and predicting the future multi-source sub-data set of each grid region by adopting the constructed multi-ecological safety comprehensive evaluation function model, the spatial classification method and the constructed ecological safety comprehensive evaluation index calculation formula to obtain an ecological safety comprehensive evaluation index corresponding to each grid region. According to the method, the ecological function of the to-be-evaluated cultivated land in the future scene is simulated by coupling the multi-ecological safety comprehensive evaluation function quantity model, so that systematic evaluation on the cultivated land ecological function of the to-be-evaluated cultivated land in the future scene is realized.

The invention provides an intelligent driving system evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent driving, detection data of an intelligent driving system is collected, and the detection data comprises environment data and driving behavior data of each vehicle; performing causal reasoning according to the environment data and the driving behavior data in combination with a preset confrontation scene, and updating a scene key factor of each driving scene; performing user portrait processing according to the environment data and the driving behavior data, and updating the weight of the evaluation dimension decision model; and according to the scene key factors and the weights, combining with the environment data and the driving behavior data, applying an evaluation dimension decision model to carry out personalized scoring on each driving scene, and obtaining a personalized scoring result for optimizing the intelligent driving system. Accurate, dynamic and demand-fitting adaptive evaluation of the intelligent driving system is realized, so that the intelligent driving system is optimized.

The invention belongs to the field of power system evaluation, and discloses an integrated energy system multi-criterion energy efficiency evaluation method based on scene adaptive dynamic weighting, which comprises the following steps: acquiring an energy efficiency evaluation index model; actual operation data of the integrated energy system are collected and extracted to serve as initial index data; inputting the initial index data into the energy efficiency evaluation index model to obtain energy efficiency evaluation index data; and calculating the energy efficiency evaluation index data through a method of combining a grey correlation method and an approximate ideal solution sorting method to obtain a comprehensive evaluation index. And the comprehensiveness of comprehensive energy efficiency index evaluation is improved.

The technology relates to program monitoring, which can involve using metadata as part of span information evaluated by the system in order to identify a location of interest in user (source) code. This can be used to pinpoint the exact code location that participated in a trace being debugged. The span information may be enriched with the code location from which it originated. The technology is also able to avoid unnecessary execution of instrumented functions by creating an alternate code execution path. This alternate path gets the code path to a variation of the instrumented function, in which the variation has a different set of operations. Upon determination that an execution call path has been previously followed, the alternate path would be automatically called instead of the path with the original instrumented function.

The invention relates to a drug interaction prediction method and system based on multi-view comparative learning, and belongs to the technical field of natural language processing. According to the method, two channels of a drug molecular map and a biomedical knowledge map are constructed in parallel, structural and semantic features are extracted by using a pre-trained heterogeneous map neural network, and multi-view comparative learning guided by information gain is introduced for joint optimization, so that the generalization ability and robustness of the model to unknown drug pairs are enhanced. According to the method, system evaluation is carried out on the performance of the system in two types of prediction tasks (multi-type and multi-label) and three prediction scenes. Experimental results show that the method has excellent performance in all tasks and scenes. Further case analysis also verifies the effectiveness of the system in predicting the interaction type of the unseen drug pair.

The invention discloses a multi-system adaptive switching radio direction finding method and system. The method comprises the following steps: acquiring signal modulation characteristic parameters and electromagnetic environment interference characteristic data to construct a system evaluation criterion, identifying a system mismatch sensitive area, and generating an interference weight distribution diagram and a system coverage margin; performing system competitive advantage decline analysis on the two to generate a switching urgency level and construct a hierarchical switching index set; obtaining a degradation offset coefficient through performance degradation trend tracking, and performing threshold correction on the real-time switching index to generate an adaptive switching index and a switching cooperation parameter; and tracking a system performance evolution trajectory based on the switching cooperation parameters and the interference weight distribution diagram, identifying an optimal system migration trigger point, completing optimal direction finding system selection and outputting an incoming wave direction measurement result. According to the invention, adaptive sensing of electromagnetic environment change and dynamic optimization of system switching are realized, and the accuracy and continuity of wave direction measurement in a complex interference environment are improved.

A system generates domain-expert agents for a particular domain. The system generates a hierarchy of topics for the domain by forming structured query inputs and requesting a machine learning-based language model to produce topics and associated sets of search terms. A knowledge store is built for the domain by identifying, for each topic, facts represented symbolically and / or in natural language. For at least one topic, programs comprising instructions for executing domain-specific procedures are generated and stored as symbolic and / or natural language programs. The knowledge store is evaluated to determine an expertise level for a domain-expert agent. If the knowledge store meets a threshold of knowledge, a deployment package is created comprising the knowledge store, and the domain-expert agent is deployed. The deployed agent utilizes the knowledge store together with a machine learning language model to address and solve problems specific to the domain.

The invention provides a radar system integrity evaluation parameter adaptive optimization method based on dynamic iteration, and relates to the technical field of radar system evaluation, and the method comprises the steps: collecting the operation data of a radar system in real time, executing the dimension reduction processing, and extracting a key evaluation parameter and a performance reference value; the performance deviation is used as a state variable, and a parameter value range is used as an action variable to optimize an evaluation parameter; a sliding time window is initialized, confidence is calculated and clustered, time sequence change characteristics are extracted, evaluation parameters are dynamically corrected, self-adaptive optimization of the evaluation parameters is achieved, and accuracy and timeliness of integrity evaluation of the radar system are improved.

The invention provides a virtual reality body rehabilitation system. The virtual reality body rehabilitation system comprises a virtual domain system, a body feeling stimulation system, a body feeling evaluation system, an equipment domain system and a central control module. The virtual domain system specifically induces the sense of ownership, the sense of autonomy and the sense of position by creating a virtual environment of a virtual avatar, real-time action mapping and adaptation rehabilitation tasks; the body feeling stimulation system takes visual stimulation as a core and is matched with linkage of various kinds of sensory stimulation, so that the authenticity of body experience is enhanced; the body feeling evaluation system evaluates real-time body feeling and provides reliable data support for regulation and control. On the basis of the physical cognition theory, the virtual reality technology, the multi-mode sensing technology, the neuroscience and the rehabilitation medicine principle are fused, multi-channel feeling collaborative stimulation such as vision, body feeling and touch feeling is achieved by constructing the immersive virtual environment, a patient is induced to generate physical experience, abnormal body representation is remodeled, nerve plasticity and function recovery are promoted, and the rehabilitation effect of the patient is improved. The patient is helped to return to normal life and society.

The invention discloses a multi-dimensional dynamic trust evaluation method and system for a new energy power terminal, and the method comprises the steps: extracting the universal features of the terminal based on terminal log interaction data, extracting special knowledge evidence according to an equipment level perception layer and a network layer, and converting all features into 0-1 standardized values; when a terminal accesses for the first time, the static attribute of the terminal is complementarily collected, so that an initial trust baseline is established and an initial trust value is given; firstly, an IoT device interaction diagram is constructed, nodes are terminal devices, attributes are knowledge evidence vectors, edges are device direct interaction relations, and weights of the edges are defined by historical interaction quality; fusing the equipment knowledge evidence and the interaction relationship through a node2vec algorithm to generate a low-dimensional embedded vector; and finally, calculating the cosine similarity of the device vectors, multiplying the cosine similarity by the interaction frequency proportion to obtain the direct trust degree of the 0-1 interval, and quantifying the direct trust relationship between the devices. Performing trust evaluation on the message flow dimension; and historical interaction behavior trust evaluation and timeliness optimization.

The application discloses a kind of based on distributed control's rail transit traction power supply optimization method, comprising: obtaining environmental parameter and correcting insulation and carrying capacity, obtain correction result;According to main substation, section, catenary section and backflow node position constructs distributed control unit and graph structure;The correction result, traction load and graph structure are input into graph attention network, and output voltage, temperature rise and insulation risk;Based on prediction and constraint, execute power supply system evaluation, generate power supply topology;Power supply topology is issued to distributed control unit, and local control parameter is generated;Distributed control unit communication cooperates to generate consistent control parameter;According to consistent control parameter, section switch, power supply arm switching and backflow path adjustment are executed.The application realizes the accurate prediction and collaborative control of traction power supply system, improves power supply stability and operation safety, has the advantages of high power safety, strong power supply reliability.

This disclosure relates to an evaluation method, system, and electronic device for a medical question-and-answer system. The method involves inputting patient information into the system to obtain a predicted diagnosis; inputting the actual diagnosis and the predicted diagnosis into a medical entity recognition model to obtain a first medical entity and a second medical entity; calculating the similarity of the feature vectors of these entities with standard entries in a standard medical terminology database to obtain a first standard entry most similar to the first medical entity and a second standard entry most similar to the second medical entity; matching the second standard entry with the first standard entry; and evaluating the performance of the medical question-and-answer system based on the matching results. Thus, when evaluating a medical question-and-answer system, even when the predicted diagnosis and the actual diagnosis are inconsistent or have logical inclusion relationships, the system can effectively resolve the complex logical connections between medical terms, significantly improving the accuracy of the evaluation.

The application relates to the technical field of medical information, and discloses a postoperative pain rehabilitation nursing data management system for a rehabilitation medical department, which comprises nine processing modules. A multidimensional data dynamic acquisition module is responsible for collecting postoperative pain related data of patients. A cross-platform data interaction module realizes data intercommunication and synchronization among multiple platforms in the system. A data encryption module performs encryption processing on collected sensitive data. A data analysis module calculates a pain comprehensive score and a rehabilitation progress index. A pain risk real-time early warning module performs real-time monitoring on the pain condition of a patient. An intelligent intervention scheme generation module generates a personalized pain intervention scheme. A pain rehabilitation evaluation module performs systematic evaluation on the pain rehabilitation process of a patient. A nursing feedback module collects feedback information of a patient on pain nursing service. A system emergency disaster recovery module provides a system-level disaster recovery backup and emergency response mechanism.

The application discloses a fire-fighting robot operation management system, and relates to the technical field of program control.The system comprises an information input program and an information processing program, and further comprises a data analysis program.The data analysis program outputs a fire condition index, a fire development prediction index and an environmental risk level index based on cleaned fire condition related data, fire development data and environmental risk data.The application realizes multi-dimensional comprehensive evaluation of the state of a fire site through the fire condition index, realizes multi-dimensional coupling analysis of future fire spread through the fire development prediction index, and realizes dynamic and accurate evaluation of comprehensive environmental risk through the environmental risk level index.The weight is dynamically adjusted through a program upgrade component, the evaluation logic can be optimized according to real-time data or historical experience of different fire site scenes, the evaluation result is highly matched with the actual dangerous situation, the problem of rigid evaluation of the existing system is solved, and the adaptability and reliability of the system in a complex and changeable fire site environment are improved.

A head-wearable apparatus improves user interactions with virtual interface elements in augmented reality (AR) environments. The apparatus tracks hand movements in 3D space, calculating velocity vectors and positions of fingers. For each virtual interface element, it determines a UI-to-finger vector and calculates alignment with the finger's velocity vector. Interaction zones are dynamically adjusted based on this alignment and velocity magnitude. The system evaluates consistency between finger movement and element locations to predict intended targets. Interactions are triggered when fingers enter adjusted zones of predicted targets. This approach reduces erroneous selections and improves interaction accuracy, even for closely-spaced elements. The invention applies to various AR scenarios, enhancing user experiences in applications like gaming and education.

The invention discloses an electrified flexible source load adjustable potential evaluation method considering cold load characteristics, and particularly relates to the technical field of electric power system evaluation and control, and the method comprises the steps: S1, obtaining the environment and equipment parameters of a cold load monomer, S2, constructing an electric-thermal coupling refined model considering a comfort level elastic interval, and S3, constructing an electric-thermal coupling refined model considering a comfort level elastic interval; the method comprises the steps of S1, obtaining a plurality of monomers, S3, calculating the adjustable potential of the monomers and generating a constraint envelope line representing the dynamic attenuation characteristics of the monomers, S4, obtaining a regional cluster potential evaluation result through aggregation according to the spatial dimension and the time scale, and S5, uploading the result to a power grid dispatching system for security defense and intelligent dispatching of a power grid of 750 kilovolts and above. According to the method, accurate quantification and dynamic representation of the adjustable potential of the cooling load are realized, the blank of cognition of a large power grid on the distributed cooling load is filled, and the flexible resource utilization level and the operation safety of the power grid are remarkably improved.

To provide an evaluation system, an evaluation method and a control program capable of quantitatively evaluating the effect of learning.SOLUTION: The evaluation system evaluates the effect of learning. At each time point before and after the learning, questions related to the content of the learning are asked to the subject of the learning. The evaluation system includes an acquisition unit, an evaluation unit, and an output unit. The acquisition unit acquires natural language data indicating an answer to a question. The evaluation unit evaluates the answer to the question by performing natural language processing on the natural language data. The output unit outputs an evaluation result of an answer to a question asked at each time point.SELECTED DRAWING: Figure 1

The invention discloses a security check system evaluation method and device, electronic equipment and a storage medium, and belongs to the technical field of security check. The method comprises the following steps: acquiring operation data of a security check system from a plurality of data sources associated with the security check system; determining first evaluation basis data of each evaluation dimension in the operation data according to a plurality of evaluation dimensions of the security check system; processing the first evaluation basis data of each evaluation dimension to obtain a dimension index value of each evaluation dimension; obtaining a dynamic weight corresponding to each evaluation dimension according to the operation data; and determining a quality score representing the security check quality of the security check system according to the dimension index value of each evaluation dimension and the corresponding dynamic weight. According to the invention, the security check quality evaluation accuracy of the security check system is improved.

The application discloses a kind of based on the cultivated land ecological safety comprehensive evaluation method and system of multi-model coupling, which comprises: setting the future multi-source data set of the cultivated land to be evaluated in future time period;Using the grid calculator in ArcGIS software, the grid division is carried out on the cultivated land to be evaluated, a plurality of grid regions are obtained, and the future multi-source data set is divided into grid based on the plurality of grid regions, to obtain the future multi-source sub-data set of each grid region;Using the multi-ecological safety comprehensive evaluation function quantity model that has been constructed, spatial classification method and the ecological safety comprehensive evaluation index calculation formula that is constructed, the future multi-source sub-data set of each grid region is predicted, to obtain the ecological safety comprehensive evaluation index corresponding to each grid region.The application simulates the ecological function of the cultivated land to be evaluated under future scenario by coupling multi-ecological safety comprehensive evaluation function quantity model, to realize the system evaluation of cultivated land ecological function of the cultivated land to be evaluated under future scenario.

To facilitate the detection and response status of system security issues, thereby simplifying security measures. [Solution] The system evaluation device includes a generation unit that uses detection result information representing the detection results of vulnerabilities possessed by multiple information processing devices included in the system to evaluate the vulnerability status in the system for each different type of evaluation method and generates evaluation result information representing the evaluation results for each evaluation method, and an output unit that causes an output device to output vulnerability trend information representing the vulnerability trend corresponding to the worst evaluation result among the evaluation result information for each evaluation method.

A system is provided.SOLUTION: A system comprising: means for collecting driving data; means for acquiring physiological data and in-vehicle environment data of a driver; means for evaluating a driving skill and a fatigue state from the driving data and the physiological data; and means for proposing a transition to an automatic driving mode based on an evaluation result. To evaluate a driving skill and a fatigue state of a driver, to smoothly shift to an automatic driving mode, and to perform appropriate communication according to a surrounding situation.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of water environment monitoring, and provides a grading evaluation method and system based on river and lake type adaptation, and the method comprises the steps: collecting and sorting the river and lake information of all to-be-evaluated rivers and lakes, obtaining a natural evaluation vector and a social evaluation vector, constructing a natural and social dual-system evaluation model, and carrying out the multi-dimensional data fusion, calculating to obtain natural subsystem evaluation and social subsystem evaluation of the to-be-evaluated river and lake, constructing and training an evaluation prediction model, predicting the natural subsystem evaluation and social subsystem evaluation of the to-be-evaluated river and lake in a deduction time period, analyzing an evaluation change trend in the deduction time period, calculating a natural actual score and a social actual score, and calculating the evaluation result of the to-be-evaluated river and lake. And dividing river and lake types for the to-be-evaluated river and lake, fusing the natural actual score and the social actual score based on the river and lake types, calculating to obtain a comprehensive score value of the to-be-evaluated river and lake, and grading the to-be-evaluated river and lake according to the comprehensive score value.

The invention discloses a power grid enterprise emergency plan system assessment method and system, a medium and equipment, and belongs to the technical field of emergency plan system assessment, and the power grid enterprise emergency plan system assessment method comprises the steps: constructing an emergency plan assessment index system; key risk indexes are identified through a fuzzy Delphi method; carrying out dynamic weight distribution on the key risk indexes based on a Bayesian best worst method; a fuzzy comprehensive evaluation method is combined with the maximum membership degree principle, and comprehensive evaluation is carried out on the emergency plan system; constructing a comprehensive risk early warning model, and calculating an early warning value of each index and an overall early warning level; and outputting an evaluation result and an early warning level. According to the method, comprehensiveness, systematicness, feasibility and practicability of emergency plan system evaluation indexes can be ensured, and emergency capability construction of power grid enterprises can be objectively and effectively evaluated.

The invention discloses a dynamic evaluation method, system and equipment for integrity of a wetland ecosystem and a medium, and particularly relates to the technical field of ecosystem evaluation, and the technical key points are as follows: constructing an integrity evaluation hierarchical structure model of the wetland ecosystem; wherein the wetland ecosystem integrity evaluation hierarchical structure model comprises a target layer, an element layer and an index layer; the target layer is a wetland ecosystem integrity evaluation target; the element layer comprises ecological system integrity evaluation elements related to the dynamic change of the water level; the index layer comprises evaluation indexes used for quantifying the ecological system integrity evaluation elements; obtaining current situation data of each evaluation index of the index layer under different water level scenes, and calculating a standardized quantized value of each evaluation index based on the current situation data; and determining the weight of each evaluation index, and calculating the wetland ecosystem integrity comprehensive index of the target layer based on the standardized quantized value and the weight of each evaluation index.