90results about How to "Improve evaluation efficiency" patented technology

The invention belongs to the cross technical field of remote sensing data processing and soil environment monitoring, and discloses a multi-source remote sensing collaborative soil quality index inversion and comprehensive evaluation system and method, and the method comprises the following steps: obtaining different types of remote sensing data in a target area, and constructing a multi-source data set; the acquired multi-source remote sensing data are preprocessed, data noise and system errors are eliminated, and data consistency is ensured; performing multi-source remote sensing data fusion by adopting a spectrum-polarization-texture collaborative fusion strategy in combination with a multi-scale decomposition and weighted fusion model; based on the fusion data, constructing a machine learning inversion model, and inverting soil quality key indexes; and carrying out comprehensive evaluation on the soil quality by adopting an analytic hierarchy process-matter element extension model to realize grading of the soil quality. By adopting the multi-source remote sensing collaborative soil quality index inversion and comprehensive evaluation system and method disclosed by the invention, rapid, accurate, large-area and dynamic monitoring and comprehensive evaluation of soil quality are realized.

The present application relates to the technical field of children nutrition assessment, and provides a kind of intelligent food material identification weighing and children nutrition assessment system, comprising: weighing module, for accurately weighing food material weight;Image recognition module, integrated multispectral camera and edge computing unit, through convolutional neural network model, multi-level feature extraction is carried out to food material image, and food material category and subdivision category are identified;Database module, built-in latest version Chinese food composition table, stores the nutrient component data of each kind of food material per 100 grams;Calculation module, according to the weight data output by weighing module and the food material category identified by image recognition module. Through the linkage of image recognition and weighing module, the synchronous acquisition of food material category and weight is realized, non-professional personnel can operate independently, the evaluation efficiency is improved by more than 70%, long-term data accumulation and trend analysis are supported, help parents to master children's nutrition status comprehensively, avoid phase nutrition imbalance.

The invention provides a high-reliability power supply mode selection method for a power distribution network. The method comprises the following steps: establishing a quantitative evaluation index system comprising a grid structure, an equipment level, technical application and management capability dimensions; for each power supply wiring mode, an improved success flow method is adopted to calculate a reliability quantitative index of the power supply wiring mode according to a topological structure, a grid structure and equipment level parameters of the power supply wiring mode; meanwhile, based on the index system, the economic quantitative index of the power supply wiring mode is calculated by adopting a full life cycle cost method; extracting a forward index and a reverse index based on the reliability quantitative index and the economical efficiency quantitative index; constructing an improved CCR model of a data envelope analysis method, and taking the reverse index as input and the forward index as output to obtain a quantitative efficiency index; and calculating a comprehensive recommendation coefficient according to the quantitative efficiency index, and taking the power supply wiring mode with the highest comprehensive recommendation coefficient as an optimal power supply wiring mode. According to the method provided by the invention, the reliability and economy are integrated, and the optimal power supply mode is quantitatively recommended.

The invention discloses a laser radar detection capability evaluation method and evaluation system, and a laser radar, and the evaluation method comprises the steps: A, adjusting the relative pose of the laser radar and a preset target plate, and enabling the detection light of a to-be-detected channel of the laser radar to be incident to the target plate; and B, under a preset test condition, adjusting the relative distance between the laser radar and the target board, obtaining the detection probability corresponding to the channel, and obtaining the limit distance of the channel based on the detection probability of the channel. According to the scheme, the accuracy of laser radar detection capability evaluation can be improved.

This invention relates to the field of medical device technology and provides a method, system, and medical device for measuring peak cough flow rate. The method includes real-time acquisition of inspiratory and expiratory flow rate signals and airway pressure signals; monitoring changes in the expiratory flow rate signal to identify burst cough events and lock a cough analysis window; calculating the difference in inspiratory and expiratory flow rates within the cough analysis window to obtain a baseline cough flow rate sequence; calculating the airway pressure signal within the cough analysis window using a system leakage factor to obtain a leakage flow rate compensation sequence; determining coefficients based on the ratio of tubing and patient airway resistance parameters and multiplying the expiratory flow rate signals to obtain a tubing resistance compensation sequence; superimposing the above sequences to obtain a corrected flow rate sequence; and extracting extreme value features and evaluating the effectiveness of the corrected flow rate sequence generated after a preset number of iterations to determine the peak cough flow rate value. This invention solves the problems of inaccurate and inefficient measurement results in existing peak cough flow rate measurements.

The invention belongs to the technical field of semiconductor manufacturing and testing, and discloses a matching evaluation method, system and device of a WAT testing machine and a storage medium. The method comprises the following steps: acquiring test data of a target and a reference machine, generating comparability conditions based on information such as products and stations to perform data alignment and preprocessing, and outputting an alignment data set and a quality index; calculating a multi-dimensional feature vector including distribution, risk, trend and wafer spatial features for each test item based on the alignment data; the feature vector and the alignment quality index are fused, a difference score is calculated, and evaluation is carried out in combination with a self-adaptive threshold value dynamically generated based on historical data and parameter importance; and finally, outputting a difference parameter list and an evaluation result, simultaneously introducing an AI model to carry out comprehensive judgment, and continuously optimizing through a feedback closed loop. Through the method, automation, quantification and intelligentization of machine matching evaluation are realized, and evaluation efficiency, consistency and accuracy are remarkably improved.

The invention relates to the technical field of risk assessment of diabetic patients, in particular to a risk assessment method and system for diabetic patients. The eye fundus image containing local defects is directly processed through the trained lesion risk assessment model, lesion risk assessment is carried out on the decoupled lesion feature vector, and the preprocessing step of carrying out manual or algorithm restoration on the defect image is omitted, so that distortion errors possibly introduced in the restoration process are avoided, the assessment efficiency is improved, and the method is suitable for popularization and application. By constructing a feature decoupling network and constructing a total loss function including comparison loss, independence constraint loss and classification loss, the model is forced to learn pure lesion feature vectors, lesion information is ensured to be effectively separated from imaging quality information, and the defect that a traditional model excessively depends on image integrity is overcome; the technical problem that the risk assessment effect of most existing DR risk assessment models based on deep learning is poor when a repaired complete eye fundus image is input is solved.

The invention discloses a vehicle safety assessment method and device based on an AI-assisted attack tree, equipment and a medium, and belongs to the technical field of computers. The method comprises the following steps: automatically generating an attack tree containing a dynamic risk level by adopting a hierarchical agent workflow based on a vehicle type architecture; extracting a threat scene from the attack tree and generating a structured description; matching a historical knowledge base by utilizing a retrieval enhancement generation technology, and generating an asset list and a threat score through a large language model; and synthesizing the attack tree and the scoring result to generate an evaluation conclusion containing security disposal suggestions. According to the technical scheme, the attack tree can be automatically generated based on the vehicle model architecture, intelligent scoring is linked, finally, the safety evaluation conclusion containing specific disposal suggestions is output, and the evaluation efficiency, accuracy and engineering practicability are remarkably improved.

The invention relates to the technical field of medical literature data processing and artificial intelligence, and discloses a random contrast test (RCT) bias risk automatic evaluation method and system, and the method comprises the steps: obtaining RCT literature data containing a text, a table and a flow chart, and a RoB2 evaluation problem set; a problem reconstruction module injected through medical knowledge; performing position decision and multi-modal coordination analysis on the RCT literature through a multi-modal document analysis module; the reconstructed evaluation problem and the analyzed context information are input into a multi-expert cooperation module, cooperative reasoning is performed through a multi-reasoning unit, results are fused through a decision unit, and item-level, field-level and overall bias risk evaluation results are generated. The invention also constructs bias risk entry level and domain level data sets for supporting the training and verification of the method. The system comprises a data acquisition module, a problem reconstruction module, a document analysis module and a collaborative evaluation module, all the modules work cooperatively, automatic evaluation of RoB2 whole-process bias risks is achieved, and the system can be applied to scenes such as evidence-based medical research, system evaluation and clinical research quality control.

The invention relates to a drought monitoring method and system, and relates to the technical field of hydraulic engineering, and the method comprises the steps: monitoring the growth state of planted crops in a first irrigation region, the drought state and a ground water source through a plurality of monitoring satellites to obtain satellite monitoring data, and determining a first drought index; acquiring unmanned aerial vehicle monitoring data of the second irrigation area by using the plurality of unmanned aerial vehicles and the intelligent machine nest, determining a second drought index of the second irrigation area based on the unmanned aerial vehicle monitoring data, and determining a preliminary irrigation state of the second irrigation area; acquiring actual measurement data of the second irrigation area through ground drought monitoring equipment, and determining a third drought index according to the actual measurement data; and determining the land parcel drought grade of each land parcel in the second irrigation area by combining the first drought index, the second drought index and the third drought index, and determining the irrigation scheme of each land parcel based on the land parcel drought grade, the initial irrigation state and the actually measured data. According to the invention, the irrigation scheme can be timely and accurately determined.

The invention discloses a fission yield experiment data screening method, and relates to the technical field of nuclear data evaluation.The method comprises the steps that S1, fission yield experiment data are obtained from an EXOR database, and the experiment data are grouped; s2, fitting each group of fission yield experimental data by adopting a Zp model, and determining model parameters; the fission yield is calculated according to the determined model parameters, so that a yield calculation value is obtained; s3, calculating the deviation between the fission yield experiment data and the fission yield calculation value obtained in the step S2; and S4, screening the experimental data according to the deviation obtained in the step S3. According to the method provided by the invention, the evaluation efficiency can be effectively improved, the research period is shortened, and technical support is provided for further establishing an experimental database.

The invention discloses a method for evaluating the volume change rate of foundry coke, and belongs to the technical field of foundry coke production. The method comprises the following steps: substituting volatile components and caking indexes of coal as fired into a formula Vc = 0.4435 * Vdaf + 0.1995 * G-20.1214 to obtain a predicted value of the volume change rate of foundry coke; according to the method, the complex relation between the as-fired coal index and the foundry coke volume change rate can be accurately captured, the average absolute error can be controlled within 3% through actual verification, and compared with the prior art, the accuracy is improved by 40%-60%; the problem that the volume change rate of foundry coke cannot be accurately predicted is solved.

This application provides a domain name risk assessment method, apparatus, electronic device, and storage medium, relating to, but not limited to, the field of data processing technology. The method includes: determining a DNS resolution dependency path tree corresponding to a target domain name; performing a depth-first search on the DNS resolution dependency path tree to determine each DNS resolution dependency path of the target domain name; obtaining attribute risk indicators of node risk attributes for each node in the DNS resolution dependency path tree; calculating path risk indicators for each DNS resolution dependency path based on the DNS resolution dependency paths and each attribute risk indicator; and determining the target risk indicator for the target domain name based on the path risk indicators corresponding to the target domain name. This application's embodiments diagnose domain name risks from a management perspective, supplementing and improving existing DNS resolution-side risks. Furthermore, based on the dependency path tree, it enables further analysis of various dependency risks in the DNS resolution process, thereby improving the accuracy and efficiency of domain name risk assessment.

The application discloses a geothermal caprock multi-factor coupling evaluation system, which aims to solve the problems of low standardization degree of existing evaluation manual operation process, lack of unified engineering architecture of multi-factor coupling and insufficient result visualization. The application automatically executes caprock comprehensive evaluation on a unified platform through a data acquisition module, a single-factor evaluation module, a coupling model construction module, a coupling score calculation module, a comprehensive evaluation module and a result output module. The system completes single-factor scoring based on basic data, constructs and calculates the scores of four coupling subsystems of lithology-diagenesis-physical property, structure-mechanics-integrity, thickness-continuity and fluid-pressure-temperature, quantifies the coupling relationship between the subsystems by using a cross influence matrix to obtain the final score, and outputs the comprehensive score and the visualized result after weighting. The application realizes the integration and automation of the evaluation process, supports the engineering landing of complex coupling models, and improves the result visualization and decision support capability.

The invention discloses a workshop-oriented traffic vibration load influence rapid evaluation method, which comprises the following steps of: arranging an instantaneous synchronous measurement array comprising a plurality of measurement points on one side, adjacent to a traffic road, of a workshop area along the direction vertical to the road; performing 1 / 3 octave analysis on the vibration data of each measuring point to obtain a vibration speed effective value of each measuring point under each 1 / 3 octave center frequency; for each 1 / 3 octave center frequency, performing power function fitting on the vibration velocity effective value of each measuring point under the frequency and the distance from the measuring point to the road, and establishing a frequency-space attenuation model; and determining a vibration velocity frequency spectrum of the target position caused by traffic vibration by using a frequency-space attenuation model, and calculating a traffic vibration dominance index TVDI of the target process equipment in combination with vibration sensitive characteristics of the target process equipment so as to quantitatively evaluate the influence degree of the traffic vibration on the target process equipment. According to the invention, traffic vibration influence evaluation is realized through one-time short-time synchronous measurement.

The application discloses a method and device for quickly evaluating a ranking model, and belongs to the technical field of computers, in particular to the field of machine learning and data mining. The method comprises the following steps: obtaining a first score list of all items, wherein the score is obtained by a ranking model to be evaluated; obtaining a second score list of related items, wherein the score can be obtained from the first score list; dividing the first score list by taking the second score list as a demarcation value, and obtaining the ranking of the related items in the first score list; and calculating a ranking evaluation index and evaluating the ranking model according to the ranking of the related items. The application solves the problems of large calculation complexity and high calculation cost in the existing method for evaluating the ranking model, and improves the evaluation efficiency. By using the method, the ranking model can be quickly and accurately evaluated on the order of 100 million items by using a small amount of calculation resources, and the cost, resources and time are saved.

This invention provides a system for evaluating the breakthrough pressure of temporarily plugged chemical bridge plugs, comprising: a high-temperature oven; a breakthrough pressure main device for holding the base fluid of the temporarily plugged chemical bridge plug, which can be arranged inside the high-temperature oven, the breakthrough pressure main device having an inlet pipeline and an outlet pipeline; a horizontal flow pump for injecting a displacement medium, the horizontal flow pump being connected to the inlet pipeline; a first pressure sensor and a second pressure sensor respectively installed on the inlet pipeline and the outlet pipeline; a pressure sensor workstation connected to the first pressure sensor and the second pressure sensor for recording the data measured by the first pressure sensor and the second pressure sensor; and a camera for capturing the breakthrough process of the temporarily plugged chemical bridge plug. This invention also provides a method for evaluating the breakthrough pressure of temporarily plugged chemical bridge plugs.

The invention provides a risk level assessment method and device, electronic equipment, a medium and a product, and relates to the technical field of computers. The method comprises the steps that after a data set in a database is obtained, a scene set corresponding to the data set is obtained according to the data set; and performing risk level division according to the number of various types of scenes in the scene set to obtain target risk levels corresponding to the various types of scenes. Through the method, the evaluation efficiency of the scene risk level can be improved.

The present disclosure provides a high crack sensitive alloy L-PBF forming hot crack sensitivity evaluation method, which can quantitatively predict the hot crack tendency of the alloy before forming by considering whether to add a heterogeneous nucleation agent, microstructure characteristics, intergranular liquid film stability and cracking driving force, combining a small amount of test, effectively solving the problems that the prior art relies on a large number of process tests, micro-characterization is complex, and cannot be predicted in advance, and greatly improving the evaluation efficiency and engineering applicability.

The application discloses an AI-based health risk assessment and intelligent grading method and system, and relates to the fields of artificial intelligence, health management and big data analysis.The system comprises a data acquisition and preprocessing module, an AI risk assessment model, a personalized suggestion generation module and a user interaction and interface module; the method collects multidimensional data such as physiological indexes, physical examination reports, lifestyles, genetic heredity, medical histories and wearable devices, inputs the data into an AI model after preprocessing, automatically calculates the weights of dynamic indexes and generates a quantitative score, maps the score into a three-level action orientation grade such as a suggestion for medical treatment, regular review and daily attention, outputs personalized guidance, department recommendations and disease early warning in combination with a user portrait, and supports third-party integration and model closed-loop optimization.The application realizes panoramic and accurate insight, dynamic tracking and personalized management of health risks, has high efficiency and can be scaled up, and provides scientific decision-making support for users, medical institutions and insurance companies.

The invention relates to the technical field of metal structure corrosion resistance data processing, in particular to a simulation calculation evaluation method for corrosion resistance of a multi-welding-seam area, which comprises the following steps: establishing a three-dimensional finite element model according to welding seam geometry and material parameters of a base metal / heat affected zone / weld nugget area; directly importing the obtained continuous residual equivalent stress field into a three-dimensional finite element model in the form of an interpolation function or an external field, and constructing stress dependent electrochemical parameters in an electrode dynamic boundary condition; after parameter setting is completed, electrode surface corrosion potential distribution and local current density are solved; and evaluating the corrosion resistance of the welding seam area according to the current density distribution, the corrosion rate field and the time-varying corrosion depth data obtained by simulation. According to the scheme, the method can be used for judging the sensitive position of the multi-welding-seam area, the corrosion resistance of the multi-welding-seam area can be evaluated more systematically and visually, the possible corrosion sensitive position can be recognized in advance, and risks can be found more timely in engineering application.

The application discloses a kind of active implantable medical device in-vivo radio frequency response modeling method based on equivalent lumped element model, by constructing and matching the electromagnetic characteristics of the actual conductive path of AIMD and surrounding tissue, equivalent lumped element model (LEM), the key factors such as the multiscale electrical characteristics of the geometry size of implantable medical device and its in homogeneous, non-uniform even real anatomic tissue environment are parameterized characterization, so as to quickly and accurately reconstruct the radio frequency transfer function of implant.The method of the application effectively breaks through the bottleneck of the existing Tier 3 evaluation method, meets the technical requirements of the latest standard based on Tier 4 evaluation method for modeling the radio frequency transfer function of implant in the environment closely related to clinical tissue, and provides a new technical path and implementation means for efficient and accurate evaluation of the radio frequency heating risk of implantable medical device in the magnetic resonance environment.

The application discloses a capital construction subcontractor project input evaluation method based on large model retrieval enhanced generation, which constructs a personnel portrait library, a team portrait library and a capital construction subcontractor portrait library based on manager dimension data, construction personnel dimension data and capital construction subcontractor dimension data, evaluates the portrait data in each portrait library of the large model and the expert scoring rule to evaluate the manager input score and the construction personnel input score of the capital construction subcontractor, and obtains a project input comprehensive score based on the manager input score and the construction personnel input score. By fusing the expert scoring rule and the reasoning ability of the large model, the consistency of the evaluation standard is ensured, the evaluation result is more objective and accurate, and the evaluation efficiency is also significantly improved. Moreover, the evaluation large model is obtained by fusing the expert scoring rule into the initial large model based on the retrieval enhanced generation technology, the retrieval enhanced generation technology can provide detailed scoring reasons for each score, so that the evaluation result is more persuasive.

This invention relates to the fields of biomolecule synthesis technology and artificial intelligence technology, specifically disclosing a method and apparatus for assessing the synthesizability of biomolecules based on reinforcement learning. The method includes: acquiring a preset dataset; merging the preset dataset to generate a merged dataset; performing structural verification and repair operations on the merged dataset to generate a corrected dataset; extracting bioaccessibility features from the corrected dataset to generate a bioaccessibility database; scoring the synthesis paths of the molecules to be analyzed based on a multimodal fusion scoring model and the bioaccessibility database, and determining the optimal path; and performing similarity clustering and replacement on the unsynthesized molecules in the optimal path to optimize the synthesis path. Through systematic data processing, multimodal feature fusion, reinforcement learning path search, and similarity replacement, efficient and accurate synthesis path assessment is achieved.

The invention discloses a cockpit layout design and evaluation method, computing equipment and a computer readable storage medium, and the method comprises the steps: constructing a digital model of cockpit layout, and obtaining a human body model matched with the features of a target user group; importing the digital model and the human body model into a simulation platform for interactive simulation, and outputting corresponding simulation data; importing the digital model into a virtual reality environment, and collecting multi-dimensional interaction parameters of a target person and a cockpit in combination with an interaction device and a capture device; according to preset airworthiness regulations and terms and evaluation standards, the simulation data and the multi-dimensional interaction parameters are comprehensively analyzed, and a conformity evaluation report is generated; and performing a simulation test on the key area in the cockpit layout, verifying the rationality of the conformity evaluation report, outputting a final evaluation report, and performing iterative optimization on the cockpit layout according to the final evaluation report. Therefore, the assessment result of the cockpit layout is more accurate, and the overall design efficiency of the cockpit is improved.

The invention discloses a model reasoning ability evaluation method, a data processing method and a storage medium, and relates to the field of large model technologies and data processing. The method comprises the steps that a target test set is obtained, the target test set comprises target questions and first verification information, the target questions are open questions obtained after question type conversion is conducted on original questions, and the first verification information is program codes for verifying answers corresponding to the target questions; the target test set is adopted to evaluate the reasoning ability of the to-be-tested language model, a first evaluation result is obtained, and the first evaluation result is used for determining the logical reasoning performance of the to-be-tested language model. According to the method and the device, the technical problems of low evaluation efficiency and poor evaluation reliability when the model reasoning capability is evaluated in related technologies are solved.

The application discloses a post-earthquake railway structure state evaluation method and system based on multi-source data fusion, which comprises the following steps: constructing a finite element model according to the structure of a regional railway network, generating a simulation data set, training a physical information neural network model, and forming a proxy model library; collecting multi-source observation data, inverting the complete posterior probability distribution of the damage parameters according to the Bayesian theory, the structure damage parameters of the physical information neural network proxy model and the multi-source observation data; extracting the statistical characteristics of the damage parameters from the posterior probability distribution, probabilistically grading the damage degree of the structure, generating driving constraint suggestions according to the damage probability grading and combining the specifications, and reducing the Bayesian inversion time from several days to several hours through the physical information neural network proxy model, thereby improving the evaluation efficiency; the output of the Bayesian method is a probability distribution, which clearly shows the uncertainty range of the evaluation result and quantifies the uncertainty.

The invention relates to the technical field of power distribution network bearing capacity evaluation, and discloses a distributed energy power distribution network bearing capacity evaluation method, system and equipment based on digital twinning and a medium, and the method comprises the steps: extracting the conventional working characteristics of a plurality of access points through collecting the working state data of a power distribution network; in combination with the operation overlapping duration of each access point, operation fluctuation characterization parameters for the power distribution network are calculated, and operation fluctuation degree categories of the power distribution network are divided; carrying out bearing evaluation or acquisition adjustment according to a division result; carrying out evaluation analysis on the operation bearing of the power distribution network; locking the fluctuating access point, identifying the number of branch lines of the fluctuating access point and the total operation duration within the preset time, judging whether the fluctuating access point is an interference access point, marking the interference access point, and sending out an early warning prompt signal. Or adjusting the acquisition frequency for the power distribution network based on the operation fluctuation characterization parameter. The accuracy of power distribution network bearing capacity evaluation is improved, bearing hidden dangers are recognized in advance, and operation safety is guaranteed.

The invention provides a bearing state evaluation method and system based on a vibration signal and a medium, and the method comprises the steps: collecting original vibration signals of a bearing under different operation conditions through a vibration sensor, and carrying out the preprocessing of the original vibration signals; respectively extracting a time domain feature, a frequency domain feature and a wavelet domain feature; carrying out feature screening by adopting a combined feature screening algorithm, and removing redundant features and invalid features to obtain an optimal feature set; performing feature fusion processing on the optimal feature set to generate a fused feature vector; constructing a bearing state evaluation model based on deep learning, inputting the fusion feature vector into the bearing state evaluation model, and outputting a bearing state evaluation result; by synchronously extracting time domain, frequency domain and wavelet domain multi-dimensional features, feature information of different types of bearing faults can be comprehensively captured, redundant and invalid features are eliminated by adopting a combined feature screening algorithm, the subsequent model calculation load is reduced, and the evaluation efficiency is improved.

The present application belongs to the field of image, in particular to a kind of pesticide preparation mixing uniformity online evaluation method, the method includes collecting pesticide preparation sample image, conversion color space extracts color and Gabor texture feature;Multi-dimensional joint measurement of fusing color, texture and spatial distance is constructed, initial superpixel is obtained by executing superpixel segmentation;Initial grouping is formed by clustering initial superpixel, fuzzy superpixel is identified by the distance proportion of superpixel to the first two cluster centers, affinity is calculated according to the color difference and spatial distance with adjacent clear grouping superpixel and is redistributed, and grouping is obtained;For each grouping, select the color channel with maximum variance as the main channel, calculate weighted zero-order moment and each order weighted central moment with the main channel normalized intensity value as weight, construct moment vector after dimensionless;The centroid of all moment vector point sets is calculated, the Euclidean distance mean of each moment vector to the centroid is calculated, and the global dispersion index is obtained as the evaluation result.