34 results about "Joint evaluation" patented technology

The invention discloses an equipment identification and quality grade joint evaluation method for a transformer substation inspection image, and the method comprises the steps: inputting a collected original transformer substation image into an image identification and quality grade joint evaluation model; the model comprises a detection perception image enhancement module, a target detection module, an ROI extraction module and an image quality evaluation module which are connected in sequence. Performing enhancement processing on the original transformer substation image by using a detection perception image enhancement module to obtain an enhanced image; performing target detection on the enhanced image by using a target detection module to obtain a power equipment category label and ROI frame coordinate information; an ROI extraction module is utilized to cut the original substation image according to the ROI frame coordinate information to obtain a corresponding equipment ROI image; performing no-reference image quality evaluation on the ROI image of the equipment by using an image quality evaluation module to obtain a quality grade label; according to the method, the equipment identification accuracy is improved, and the image quality grade is credibly output.

This invention discloses a method for joint evaluation and optimization of buckling and bending of arbitrary quadrilateral laminates based on physical information neural networks, relating to the field of composite material structure design technology. The method, for arbitrary quadrilateral laminates, first constructs a method based on classical laminate theory... USA The stiffness matrix explicitly reflects the influence of ply parameters, and a physical domain is transformed to a reference domain through a bitriangular affine mapping to establish a physical information neural network mechanical model. The model is trained with the goal of minimizing the total potential energy or Rayleigh quotient, solving for the buckling factor and layer-by-layer strain limits, and adapting to four typical boundary conditions through a boundary embedding function. Subsequently, using ply angle and thickness as variables, optimization is performed using a genetic algorithm, with the goal of minimizing mass, and the buckling factor and strain limits as constraints. The final output is the optimal ply scheme that satisfies specific boundary conditions. This invention can optimize ply angle and thickness while satisfying buckling stability and strain strength constraints.

This application provides a method and apparatus for jointly evaluating security boundaries and communication performance based on 5G-A industrial internet. The method includes: acquiring current network load data and current security policy parameter combinations, and inputting the current network load data and current security policy parameter combinations into a nonlinear latency prediction model to obtain the current overall latency; utilizing the current security policy parameter combinations and the current overall latency to generate a current security-communication global score; when the current security-communication global score is lower than a preset threshold, determining the fine-tuning amount of each security parameter from a multidimensional coupling relationship matrix library based on the current network load data and the current security policy parameter combinations to obtain the optimal security policy parameter combination. Through the nonlinear latency prediction model and the multidimensional coupling relationship matrix library, coupled modeling of security and communication is achieved; it also enables comparison and integration of security and communication in the same dimension, achieving synergistic optimization of security and communication resources.

The invention discloses a double-domain joint evaluation method for imaging quality in wide-spectrum coherent diffraction imaging, which belongs to the related technical field of wide-spectrum coherent diffraction imaging, and comprises the following steps: 1, measuring light source spectrum distribution for wide-spectrum coherent diffraction imaging, and imaging a wide-spectrum diffraction field through an imaging algorithm; 2, obtaining a current reconstructed image and actually measured diffraction light intensity after each iteration of the imaging algorithm, constructing wide spectrum diffraction light intensity by using spectral distribution and reconstructed image values, and using and calculating diffraction field errors; 3, performing no-reference quality evaluation on the reconstructed image after each iteration, and calculating an image error; and 4, using weighting to form a double-domain joint evaluation result. The method can effectively solve the problem that the existing wide-spectrum laminated diffraction imaging lacks a unified and accurate evaluation method, thereby improving the reliability and consistency of reconstruction quality evaluation.

This invention relates to the fields of civil engineering structural safety inspection and machine learning technology, and discloses a machine learning-based collaborative evaluation method and system for the mechanical properties of concrete components. The method constructs a coupled graph of mechanical indices with confidence levels, trains a missing-node-aware joint evaluation model, and suppresses the propagation of noise from missing nodes through joint attenuation of observability masks and edge confidence weights. Then, it performs weighted SHAP interaction effect analysis and hierarchical verification, and generates a supplementary detection scheme with comprehensive information gain ranking based on the D-optimal criterion. Through iterative closed-loop optimization, it outputs the collaborative evaluation results and evaluation confidence levels of the concrete component's compressive strength, splitting tensile strength, and elastic modulus.

The invention belongs to the technical field of space target monitoring and data processing, and particularly relates to a space debris short arc data quality evaluation method and system based on a multi-dimensional standard, and the method comprises the steps: obtaining space target ephemeris data, a short arc observation data set and a target identification mapping relation, binding the ephemeris data of the space target and the short arc observation data set to the same space target; judging whether the space target ephemeris data is available or not; analyzing the successfully matched short arc observation data to obtain observation data features; executing a full-dimension quality evaluation process for available space target ephemeris data, and executing a degradation quality evaluation process for unavailable space target ephemeris data; and performing normalization processing and weighted fusion on each index to obtain a comprehensive quality score, and outputting an evaluation report. According to the invention, through joint evaluation and fusion scoring of multi-dimensional indexes, stable and interpretable quality determination of short arc observation data can be realized.

The invention provides an image determination method and device, electronic equipment and a computer program product, and relates to the technical field of machine vision. The method comprises the steps of obtaining a to-be-labeled image set, wherein the to-be-labeled image set comprises a plurality of target labeled images; receiving an image annotation result of the annotation personnel for the target annotation image, wherein the image annotation result is obtained by carrying out image annotation by the annotation personnel based on an image annotation standard generated after the annotation training operation; obtaining a reference annotation image, and performing cross verification on the image annotation result based on the reference annotation image to obtain an annotation verification result; and based on the annotation verification result, determining a target quality image from the plurality of target annotation images. According to the method and the device, through a multi-round joint evaluation and cross validation mechanism, the annotation consistency is remarkably improved, the problem that the quality of the annotated high-quality image is unstable can be effectively solved, and meanwhile, the construction efficiency of the high-quality image set can be improved.

The invention provides an aircraft bearing end face parallelism joint evaluation method with a common mode rejection function, and belongs to the technical field of aircraft engine bearing end face parallelism measurement. The method comprises the following steps: step 1, acquiring end face data of an inner ring and an outer ring of a bearing through a parallelism measurement system to obtain an original observation vector; 2, by introducing a weighing parameterization method, the absolute plane parameters of the inner ring and the outer ring are decoupled and recombined into common-mode tilt parameters and differential-mode shape parameters; step 3, error correlation modeling: capturing statistical characteristics of the system by constructing an equivalent covariance matrix containing cross correlation coefficients; step 4, performing robust judgment based on mahalanobis distance; and step 5, performing adjustment calculation in combination with a Gauss-Helmert model to obtain a final parallelism evaluation result. According to the method, the high-order residual problem of a traditional linearization model is solved, while common-mode vibration signals are reserved, real outliers are accurately recognized, and the numerical stability and the result reliability of parallelism evaluation are remarkably improved.

The invention relates to the technical field of medical monitoring, and discloses an orthopedic postoperative limb swelling monitoring method and system, and the method comprises the steps: carrying out the interaction relation mining of multi-source heterogeneous data in a target limb region, and obtaining a coupling relation group of the target limb region; performing multi-scale physiological signal separation on the multi-source heterogeneous data to obtain an integrated physiological state parameter of the target limb region; analyzing local microcirculation impedance characteristics of the target limb region, and performing spatial topological mapping on the local microcirculation impedance characteristics to obtain an impedance distribution diagram of the target limb region; performing path deduction on the individualized swelling trend of the target limb region to obtain a reference track of the individualized swelling trend; performing feedback type dynamic correction on the reference track to obtain a dynamic synchronous track of the individualized swelling trend; performing multi-modal joint evaluation on the individualized swelling trend to obtain a swelling report of the target limb region; the orthopedic postoperative limb swelling monitoring efficiency can be improved.

Disclosed herein is a method and system for knee joint evaluation and balancing. The method can include the steps of tracking a knee joint during a patellar tendon reflex with a sensor to generate sensor data, generating image data related to the knee joint during the patellar tendon reflex, and determining a patellar tendon score from the sensor data and the imaging data. The patellar tendon score can represent a knee joint condition. The system can include a sensor configured to track a knee joint during a patellar tendon reflex, an imaging device configured to generate image data related to the knee joint, a processor in communication with the at least one sensor and the imaging device, and a user interface configured to display a patellar tendon score.

This application provides a method and system for assessing the lifespan and tiered utilization of wind turbine blades. The method involves acquiring operational monitoring data and damage detection information of the wind turbine blades; based on the operational monitoring data, constructing a joint evaluation framework of a data-driven time-series prediction model and a cumulative damage calculation model based on material fatigue characteristics; determining the remaining lifespan of the wind turbine blades by cross-validating and weighted summation of the outputs of both models; generating targeted repair decisions based on the remaining lifespan and the damage type, location, and severity contained in the damage detection information; and performing repair treatment on the wind turbine blades according to these decisions; evaluating the performance of the repaired wind turbine blades; and classifying the blades into different tiered utilization levels based on the evaluation results and preset performance thresholds for corresponding reuse treatment. This approach improves the accuracy of lifespan assessment and the efficiency of tiered utilization.

The present application is suitable for the field of 3D scanning technology, and provides a character model 3D scanning and dynamic posture capturing method and system. The method dynamically triggers three-dimensional scanning by real-time monitoring of joint movement intensity, continuously collects continuous motion trajectories using inertial sensors during non-scanning periods, and inversely calculates the space-time parameters of the occluded part through multi-light source shadow boundary evolution. A space-time joint evaluation function is constructed to adaptively adjust the scanning frequency and sampling rate. Finally, the discrete point cloud, continuous trajectory and inverse calculation data are space-time aligned and confidence weighted fused to generate a dynamic biomechanical model. This scheme breaks through the resource waste and occlusion blind zone bottleneck of traditional fixed frequency scanning, realizes the space-time complementation and precision optimization of motion monitoring, and is suitable for dynamic scenes such as film and television animation, medical rehabilitation, sports training, etc. Through multi-modal data fusion and adaptive resource scheduling, the system significantly improves the data integrity, real-time performance and biomechanical analysis capability, providing an efficient solution for human motion digitization.

This application relates to the field of medical neuroimaging processing and computer-aided diagnosis technology, and discloses a method based on normal white matter. 18 An Alzheimer's Disease (AD) Auxiliary Assessment System Based on F-florbetapir Retention Features. This system includes a data acquisition module for acquiring multimodal brain imaging data of subjects; an image preprocessing and segmentation module for impurity removal and target localization of the image data; a feature extraction module for extracting image features from the processed images; and a joint assessment and prediction module for AD auxiliary assessment based on the extracted features, incorporating a subject performance characteristic model and a logistic regression system. This Alzheimer's Disease (AD) auxiliary assessment system can significantly improve the accuracy of early AD diagnosis, accurately predict the rate of cognitive decline, and dynamically monitor the effect of immunotherapy.

The invention relates to the field of geotechnical engineering monitoring, in particular to a half-excavated and half-filled roadbed and slope stability combined monitoring and evaluation method and system, and the method comprises the following steps: building a data combined monitoring array, and carrying out the data synchronous collection through the data combined monitoring array, so as to obtain multi-source distributed monitoring data; performing quality control and preprocessing on the multi-source distributed monitoring data to obtain a multi-source standardized monitoring data set; constructing a roadbed-slope stability joint evaluation model based on the multi-source standardized monitoring data set, and obtaining a stability collaborative evaluation index according to the roadbed-slope stability joint evaluation model; and constructing a multi-stage stability evaluation mechanism, and combining the stability collaborative evaluation index and the multi-stage stability evaluation mechanism to obtain a stability joint monitoring evaluation result. According to the method, the comprehensiveness and the accuracy of combined monitoring and evaluation of the stability of the half-excavated and half-filled roadbed and the slope are improved, and effective data support is provided for engineering decision and engineering safety.

The invention relates to the technical field of artificial intelligence security and natural language processing, and particularly provides a model security availability joint evaluation method based on dynamic multi-objective optimization. The method comprises the following steps: iteratively updating a test suffix by using an optimization signal provided by a local reference model to generate an evaluation sample; a local evaluation sample optimized based on a reference model is applied to a to-be-tested target model environment for verification and evaluation, and the method solves the problems that evaluation target coverage is insufficient, and sample naturalness and scene consistency are weak.

The invention discloses a multi-modal joint evaluation method for the repairing effect of an eye-brain assembly, and belongs to the technical field of biomedical engineering and neuroscience. The method aims at solving the problems that an existing evaluation means cannot reflect function integration in real time in a living body state, a specific index is lacked to distinguish effective remodeling and disordered growth, and a single behavioral test is prone to interference, so that false positive is caused. Specific visual stimulation is presented to a transplantation receptor, local field potential of a primary visual cortex is synchronously collected, and Low Gamma frequency band signals are extracted to calculate direction selectivity indexes and brain network topological attributes; meanwhile, a hierarchical visual behavioral test for sensing spatial cognition from basic light is carried out; and finally, constructing a binary decision matrix based on thresholding scores of electrophysiology and behavioral indexes, and outputting a four-classification quantitative evaluation conclusion including effective functional repair, thereby realizing accurate and standardized judgment of the visual cortex repair effect.

The application provides an examination site and probe posture recognition method and system based on an ultrasonic body mark label diagram, and a storage medium. The method is divided into a training stage and an inference and automatic labeling stage. The training stage includes constructing a multi-vendor ultrasonic body mark dataset, designing and training a "body mark positioning and anatomy classification integrated model" and a "probe posture key point regression model", and model joint evaluation and deployment. The inference and automatic labeling stage includes image acquisition and preprocessing, serial execution of two pre-trained models, completion of body mark positioning, anatomy site classification and probe posture key point extraction, body mark pose analysis and standard view label generation, and structured data generation and storage. The application realizes full-link automation of body mark positioning, anatomy classification and probe posture analysis of ultrasonic images through the construction of a double model joint inference, breaks through the limitation of body mark information being used only for manual interpretation, and realizes the automatic value conversion of ultrasonic body mark information.

This invention proposes a joint assessment method for fleet mission load and crack state based on Bayesian updates, belonging to the fields of aircraft structural safety, aircraft structural fatigue crack propagation tracking, and aircraft load assessment. The method includes: converting the random load spectrum under different mission histories of the fleet into equivalent constant-amplitude loads using an equivalent load method based on the Paris formula, forming a load level that can be quantified for subsequent analysis; establishing a mission-labeled load library and a fatigue crack damage propagation model; constructing a Bayesian network based on network nodes and interdependencies to build a probabilistic joint assessment architecture for mission load and crack state; using a particle filter algorithm as the inference algorithm for the dynamic Bayesian network to jointly assess the fleet mission load and structural crack state; and testing and verifying the aforementioned network architecture and method in a pre-defined fleet. This invention provides real-time assessment of the load levels of different missions of the fleet, thereby ensuring the safety of the aircraft structure.

The application discloses a communication anti-interference autonomous decision-making method, system and device based on joint evaluation of interference parameters and channel conditions, and belongs to the technical field of wireless communication. The method comprises the following steps: processing a received composite signal, extracting parameters such as a signal-to-noise ratio, an interference signal-to-interference ratio, an interference lock time difference and an interference bandwidth proportion; constructing a state vector and selecting a target mode from candidate anti-interference modes based on a decision function; and performing waveform or parameter reconfiguration to maintain service communication. The application realizes quantitative differentiation of interference types and autonomous optimal selection of anti-interference modes, and solves the problem that existing systems cannot accurately cope with complex interference due to reliance on artificial experience.

This invention discloses an intelligent evaluation method and system for gasket assembly compatibility, relating to the field of gasket assembly quality evaluation technology. The method includes: acquiring contour data of the gasket to be assembled, structural data of the assembly groove, and process timing response data during gasket assembly; constructing an initial bonding distribution model; extracting dynamic response features and determining corresponding assembly interface regions; correcting bonding state parameters of corresponding regions to generate a virtual bonding map; determining the regional bonding risk distribution; and generating gasket assembly compatibility evaluation results. This invention achieves a joint evaluation of regional bonding risk distribution and overall compatibility level, enabling the identification and location of hidden defects in the assembly process, providing a basis for selective rework and process optimization.

The application provides a generative machine translation reward model based on an in-group joint evaluation paradigm and a training method thereof, and comprises the following steps: step 1, constructing training data; step 2, based on the training data, selecting a base model and performing supervised learning fine-tuning training to obtain a cold start group relative reward model; step 3, based on a verifiable reward reinforcement learning, optimizing the cold start group relative reward model to obtain a final group relative reward model; and step 4, using the final group relative reward model to optimize a target translation model to obtain an optimized translation model for a machine translation task.

The invention discloses an authority management system based on multi-modal biological characteristics. The authority management system comprises a biological characteristic acquisition module; an environment information acquisition module; an authority selection module; the biological characteristic acquisition module and the environment information acquisition module transmit information to the combined evaluation module for joint evaluation to obtain a first instruction, and then the authority selection module is controlled to output different function instructions; the system further comprises a memory, and function instructions corresponding to different combination criteria are stored in the memory. Compared with the prior art, the mobile equipment has the advantages that the structure is simple, and the mobile equipment can be actively started according to environmental dynamics, or combination is performed according to collected biological characteristics of a user, for example, data deletion and modification are performed under the conditions of stress and the like.

The invention relates to the technical field of medical detection and diagnosis, in particular to a diabetic foot wound infection severity and osteomyelitis risk combined assessment method and system based on image recognition. The method comprises the following steps: acquiring a wound image and a patient context, and performing white balance correction, color card reference calibration and quality screening to obtain a quality passing image; performing instance segmentation and semantic segmentation through the image based on the quality, generating a wound mask, a contour and a tissue category mask, and performing area and color texture statistics to construct a candidate index structure; feature aggregation, double-task reasoning and hierarchical calibration are executed, and a joint evaluation structure is generated; and finally, performing thermodynamic diagram rendering, evidence fragment extraction and report generation to obtain a configuration updating parameter structure. According to the invention, multi-modal data fusion and automatic decision-making of wound assessment are realized, and the accuracy, interpretability and clinical applicability of the assessment result are improved.

The application provides a kind of laser light source line width stability multi-parameter joint evaluation method and system, obtains the junction temperature parameter of laser, environmental sound spectrum data and optical interference original signal during power mutation;The energy accumulation operation is carried out to the environmental sound spectrum data, and acoustic characteristic energy value sequence is generated;The optical interference original signal is phase demodulation processing, and line width drift value sequence is generated;The junction temperature parameter, the acoustic characteristic energy value sequence and the line width drift value sequence are carried out frequency domain correlation operation, and joint transfer function matrix is generated;The amplitude response modulus of the matrix is calculated, and dynamic weight vector is obtained;The line width drift value sequence is Fourier transformed, and initial line width frequency domain distribution vector is obtained, combined with the dynamic weight vector, and multi-parameter joint evaluation value is calculated;The application realizes dynamic weighted comprehensive evaluation to laser light source line width stability, and improves the accuracy and robustness of evaluation.

The application discloses a fritillaria delavayi treatment UC efficacy system and optimization method based on multi-omics joint evaluation, belongs to the field of medicine, and comprises a sample collection module, a quality control processing module, an extraction labeling module, a graph construction module, an individual simulation module, a treatment management module, a disturbance identification module, a learning update module, a driving identification module, a therapeutic effect prediction module, an optimization simulation module, and a clinical return module; the application effectively solves the problem that the therapeutic effect of fritillaria delavayi has obvious individual differences but is difficult to explain, avoids the risk that a traditional model lacks biological rationality, improves the credibility and interpretability of a conclusion, provides clear target clues for mechanism research, pharmacological interpretation and subsequent experimental verification, reduces the application obstacles of uninterpretable model conclusions, and has high general value and platform potential.

The invention relates to the technical field of new energy ships, in particular to a new energy ship damage state assessment method and system, and the method comprises the steps: obtaining multi-dimensional sensing data of a new energy ship, monitoring the multi-dimensional sensing data, and recognizing a damage event and positioning and quantifying a damage feature when the data triggers a self-adaptive damage threshold value; based on the damage event and the multi-dimensional sensing data, multi-model joint evaluation is executed, and the multi-model joint evaluation at least comprises hull structure and survivability evaluation based on the structural integrity data; performing energy system safety assessment based on the new energy system state data; based on the electric propulsion network data, power grid topology and propulsion capability evaluation is carried out; and generating a comprehensive assessment report and / or a damage control suggestion according to a multi-model joint assessment result, the method solves the problem that hull assessment, energy assessment and electric power assessment are mutually isolated in the prior art, realizes cross-system cascade risk assessment, and makes a decision no longer lagged.

The application discloses a kind of advertisement recommendation effect evaluation systems based on multidimensional user portrait, it is related to artificial intelligence technical field, the functional module of the system includes: user portrait quantification module, space-time correction module, sample weight correction module, joint evaluation score calculation module and normalization quantification output module.The application is measured by setting the user portrait abnormal risk measurement mechanism based on space-time correction, and is normalized modeling by joint sample weight, forms unified abnormal risk joint evaluation score, and the scheme effectively overcomes the deficiency of abnormal risk isolated evaluation in the prior art, improves the stability and credibility of advertisement recommendation effect evaluation.The technical means provides a solid data basis for risk identification and effect quantification of recommendation model, and promotes the development of advertisement recommendation system to more accurate and intelligent direction.

The present application relates to the technical field of artificial intelligence security and natural language processing, and in particular provides a model security and usability joint evaluation method based on dynamic multi-objective optimization. The method comprises using an optimization signal provided by a local reference model to iteratively update a test suffix to generate an evaluation sample; and applying the evaluation sample optimized based on the reference model to the local environment of a target model to be tested for verification and evaluation. The method solves the problems of insufficient evaluation target coverage and weak sample naturalness and scene consistency.

The present application relates to the field of geotechnical engineering monitoring, especially to a method and system for monitoring and evaluating the stability of semi-excavated semi-filled roadbed and slope, the method comprising the following steps: establishing a data joint monitoring array, using the data joint monitoring array to obtain multi-source distributed monitoring data through synchronous data acquisition; performing quality control and preprocessing on the multi-source distributed monitoring data to obtain a multi-source standardized monitoring data set; constructing a roadbed-slope stability joint evaluation model based on the multi-source standardized monitoring data set, and obtaining a stability collaborative evaluation index according to the roadbed-slope stability joint evaluation model; constructing a multi-level stability evaluation mechanism, and obtaining a stability joint monitoring evaluation result in combination with the stability collaborative evaluation index and the multi-level stability evaluation mechanism. The present application improves the comprehensiveness and accuracy of the joint monitoring and evaluation of the stability of semi-excavated semi-filled roadbed and slope, and provides effective data support for engineering decision-making and engineering safety.

The application discloses a kind of movement and cognitive ability evaluation method, system and device, method includes: obtaining the real-time motion information of user, including real-time joint angle information, real-time gait information, real-time attention information and real-time decision speed information;Physiology-behavior coupling model based on hidden Markov model is constructed, and joint evaluation index is generated by input real-time motion information;Real-time motion information is extracted using hierarchical feature extraction model, and motion feature vector and cognitive feature vector are obtained;Characteristic vector is fused with joint evaluation index, and abnormal state information containing movement anomaly and cognitive anomaly is output;Through dynamic threshold model detection behavior anomaly and combine preset feedback rule generates real-time feedback instruction, finally according to instruction dynamic adjustment user training task parameter.The method realizes the collaborative monitoring and adaptive training control of movement and cognitive ability by multidimensional data fusion and dynamic evaluation mechanism.