87results about How to "Improve assessment accuracy" patented technology

The embodiment of the present specification provides a logistics service object scheduling method, which obtains service data of a target object; then performs data statistics on the service data through a service evaluation index to obtain a service evaluation parameter; and performs data statistics on the service data through a parameter influence index to obtain an influence factor; then adjusts the service evaluation parameter based on the influence factor to obtain a regional familiarity of the target object to a target region; and further schedules a service process corresponding to the target object according to the regional familiarity. Thus, the logistics service capacity resource dynamic scheduling process is realized. Since the multi-dimensional comprehensive service evaluation index is used to quantify the logistics service execution effect, and the multi-dimensional influence factor is used for quantitative correction, the evaluation accuracy of the service effect of the target object in a specific region is improved, and the service process is scheduled based on the obtained regional familiarity, so that the execution efficiency of the logistics service is improved.

The invention discloses a cascading failure-based wind power credible capacity evaluation method and device, and the method comprises the steps: obtaining the topological structure information of a power transmission network frame of a target power system, the conventional attribute information of a conventional unit, and the wind power attribute information of a wind turbine unit, and obtaining the actual power grid operation information of a target region within a preset time period; on the basis of the information, representative scenes of the target power system before, during and after the cascading failure occur are constructed; fault evolution operation simulation is carried out on the target power system in the representative scene before the fault, the representative scene in the fault and the representative scene after the fault, and a power grid state characteristic matrix of the target power system in each representative scene is determined based on simulation results; and based on the power grid state characteristic matrix, determining the wind power credible capacity through alternate iteration by using the upper layer model and the lower layer model.

The application belongs to the technical field of electric variable measurement, and particularly relates to a coaxial double-electrode friction nanometer power generation yarn electrical property test method and system. The method comprises the following steps: controlling the power generation yarn to perform calibration pre-excitation, collecting a reference charge amount, and constructing a response surface mapping function; performing calibration pre-excitation again, collecting current temperature and humidity and actually measuring the reference charge, and calculating a multiplicative environmental correction factor based on the mapping function; using a recursive least square algorithm with a forgetting factor to update a local gradient online, and calculating an additive dynamic reference drift amount; performing formal test excitation to obtain a formal test transfer charge amount; calculating a compensated surface charge density, and completing electrical property test. The application introduces a decoupling and compensation means for environmental factors and material historical state in the test method, so as to obtain a test result which can truly reflect the intrinsic charge transfer capacity of the material and has strong comparability under different times and environments.

The embodiment of the application provides a network quality evaluation method, device and equipment and computer storage medium, and relates to the technical field of low-altitude communication. The method comprises the following steps: obtaining static evaluation indexes and dynamic evaluation indexes of a space to be evaluated stored in different storage spaces. Based on the static evaluation indexes and the dynamic evaluation indexes, a static model and a dynamic model are constructed, and then a fusion model is obtained. Based on the fusion model and a preset evaluation method, the network quality evaluation result of the space to be evaluated is determined. The static evaluation indexes and the dynamic evaluation indexes stored in different storage spaces are obtained, and the static and dynamic indexes are differentiated, processed and stored, so as to adapt to the stability of the static evaluation indexes and the periodic change law of the dynamic evaluation indexes, improve the modeling efficiency and the prediction accuracy, and then improve the evaluation accuracy. Through fusing indexes of multiple dimensions, a multidimensional model is obtained, and multiple dimensions are comprehensively covered, so that the evaluation is close to the actual business, and the evaluation accuracy is improved.

The invention provides a portable digital intelligent human body thermal comfort portable detection device and method. The detection device comprises an intelligent bracelet, an intelligent tool, an intelligent safety helmet, a wireless communication module and a management terminal. The intelligent bracelet is provided with a thermal comfort evaluation model, physiological parameters, psychological parameters and underground environment parameters of an operator are monitored through the intelligent bracelet, the intelligent tool and the intelligent safety helmet respectively, all the parameters are gathered to the intelligent bracelet, and the thermal comfort evaluation model is called through the intelligent bracelet. The current thermal comfort level is obtained based on the collected physiological parameters, psychological parameters and underground environment parameters; and triggering grading early warning according to the thermal comfort grade. By adopting the device and the method provided by the invention, the accuracy of predicting the thermal comfort of the human body in the underground environment is improved, meanwhile, the individuation of thermal comfort prediction is reflected, and thermal comfort trending pre-judgment is realized by utilizing historical information.

The invention discloses an outdoor exercise risk intelligent assessment method and system, and relates to the technical field of exercise risk assessment. An intelligent assessment system for outdoor exercise risks comprises a data acquisition and processing module, a physiological risk assessment module, a state risk assessment module, an environment risk assessment module and a comprehensive assessment and processing module. According to the invention, the preprocessed motion state data is segmented based on the preprocessed surrounding environment data, and the motion state of the user is evaluated according to the historical outdoor motion data and the segmented motion state data. According to the intelligent assessment method and system for the outdoor exercise risk, the mental or fatigue state of the user during outdoor exercise can be quantified under the condition that the influence of surrounding environmental factors is eliminated, so that the change of the outdoor exercise risk caused by the poor mental state and muscle fatigue of the user is accurately assessed, and the assessment comprehensiveness of the intelligent assessment method and system for the outdoor exercise risk is improved.

The embodiment of the invention relates to a processing method and device for road side sensing track evaluation. The method comprises the following steps: receiving a first task request; acquiring a drive test trajectory set, a sensing trajectory set and a local high-precision map from the cloud; unifying a coordinate system for all track points of the two track sets; carrying out track cutting on the two track sets; segmenting the road test tracks based on the track point curvature, selecting a matching track set for each segmented track based on a DTW algorithm, merging all the matching track sets corresponding to each road test track, and performing sensing track splicing based on each merged track set according to a time-space continuity rule; calculating the effective sensing track length of each drive test-sensing track pair according to a high-low speed self-adaptive invalid track length identification method, and calculating a corresponding sensing coverage rate; and taking the average value of all the sensing coverage rates as the roadside sensing coverage rate. According to the invention, the evaluation accuracy of the roadside perception capability can be effectively improved.

The invention relates to the technical field of investment casting, in particular to a casting liquid fluidity experiment device and method. The casting liquid fluidity experiment device comprises a pouring cup, a main pouring gate, a bent pouring gate, a bottom pouring transverse pouring gate and a bottom pouring test plate. The first end part of the main pouring gate is communicated with the pouring cup; one end of the bent pouring gate is communicated with the bypass position of the main pouring gate; one end of the bottom pouring cross gate is communicated with the second end part of the main pouring gate; the interior of the bottom pouring test plate is hollow; one end, far away from the main pouring gate, of the bottom pouring cross gate is communicated with the bottom pouring test plate; the extension direction of the bottom pouring test plate is intersected with the extension direction of the bottom pouring cross gate; the bottom pouring test plate and the bent pouring gate are positioned on the same side of the bottom pouring cross gate; the cross section of the bottom pouring test plate is rectangular; the extension length of the bent pouring gate is greater than that of the bottom pouring test plate; in this way, the problems that in the prior art, casting liquid fluidity testing is single, and evaluation is not comprehensive enough are solved.

The application relates to the technical field of hydrogeological monitoring, in particular to a hydrogeological dynamic monitoring and analysis system and method based on big data; specifically, hydrogeological data is collected in real time, data denoising, space-time calibration and error correction are carried out in combination with edge computing, noise and drift error are eliminated by adopting variational mode decomposition, geological model constraint and wavelet transform, and the storage and transmission efficiency is optimized by increment encoding and Huffman encoding, and a quadratic form check code is generated to ensure data reliability; a space-time deep learning model and a self-attention mechanism are fused to predict a hydrological evolution trend, adaptive anomaly detection is realized by combining DBSCAN clustering and prediction error analysis; water resource allocation strategies are optimized through reinforcement learning, risk levels are evaluated in layers, and management schemes are generated, and finally, monitoring data, abnormal scores and decision results can be visually displayed. The application integrates multi-source data fusion, space-time modeling and intelligent decision-making, and improves hydrological monitoring precision and response efficiency.

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 ship navigation trajectory prediction method and system, and the method comprises the steps: obtaining the inertial navigation data of a ship, carrying out the inertial navigation calculation based on the inertial navigation data, and obtaining a first trajectory prediction result; obtaining historical navigation data of the ship, and obtaining a second trajectory prediction result through a trajectory prediction model based on the historical navigation data; carrying out credibility evaluation on the historical navigation data in spatial density and mode similarity dimensions to obtain a credibility index of the historical data; dynamically determining data fusion weights of the first trajectory prediction result and the second trajectory prediction result based on a credibility index evaluation result; and fusing the first trajectory prediction result and the second trajectory prediction result according to the data fusion weight to generate a final ship navigation trajectory prediction result.

This application belongs to the field of radar data processing technology, specifically relating to a radar data association and detection capability analysis method. The method includes: classifying and parsing received radar detection result data of a batch to be analyzed according to data source; acquiring the spatiotemporal position data of the platform to be analyzed, the target track data output by the platform's radar detection, and the spatiotemporal position data of the test target; identifying the time period where the above three types of data coexist; using the detection time of the radar detection track as a reference, converting the spatiotemporal position data of the platform to be analyzed and the spatiotemporal position data of the test target to the reference time through interpolation; for the selected platform to be analyzed, associating the track corresponding to the test target from the radar detection track; calculating the error of each radar detection index relative to the given actual value of the test target, and graphically displaying the radar detection value, actual value, and error value of the index. This application significantly improves data processing efficiency and evaluation accuracy.

This invention discloses a method and system for acquiring corrosion damage points in metallic materials based on machine vision technology. The method includes: acquiring image sequences of corrosion regions under different spectral bands to generate an original image set containing spectral features and spatial information; performing semantic segmentation of the corrosion regions on the original image set based on deep learning to generate a binary mask image of corrosion damage points; using a 3D reconstruction algorithm to recover depth information of the corrosion regions based on the binary mask image to generate a set of corrosion damage points with quantified attributes; and using a density clustering algorithm to identify the spatial distribution pattern of discrete corrosion points based on the corrosion damage point set to generate an analysis report including corrosion level assessment and distribution heatmap. Using this invention, high-precision acquisition and 3D quantitative analysis of metal corrosion damage points can be achieved, improving the automation level and assessment accuracy of corrosion detection.

The application provides an evaluation device and method for phase measurement error of a spherical near-field antenna when the antenna is installed eccentrically, which can evaluate the phase measurement error of a to-be-measured antenna in a certain direction, a certain section and a certain angle range of a space under different eccentric distances of the antenna in a field. The device comprises a spherical near-field scanning ring 7, a low-frequency probe array 8, a high-frequency probe array 9, a spherical near-field test azimuth turntable 11 and an adapter tool 12. The two half rings of the spherical near-field scanning ring 7 are respectively arranged with the low-frequency probe array 8 and the high-frequency probe array 9. The spherical near-field test azimuth turntable 11 is located on the central axis of the spherical near-field scanning ring. The azimuth turntable 11 is connected with the adapter tool 12. The tool main body structure 1 and the counterweight 6 are connected with the turntable flange 3 and are installed on the adapter tool 12. The to-be-measured antenna 10 is installed on the antenna installation hole 2 of the test tool.

The application discloses a kind of customized training plan generation methods for operation and maintenance personnel based on performance prism, which comprises the following steps: collecting multi-source heterogeneous demand data of operation and maintenance personnel on multiple platforms, and combining Carnot model and importance performance analysis model for fusion processing, extracting key technology theme through cluster analysis, drawing core training intention and decomposing into key measurement indicators, collecting employee daily operation and maintenance behavior data and calculating ability membership degree vector, combining post demand information, calculating target ability information to be enhanced, generating training content using intelligent workflow engine according to target ability information and key measurement indicators, generating hybrid training plan combining online and offline according to employee historical schedule, issuing the plan to terminal and setting task reminders, which can ensure that training is executed on time, improve training coverage and completion rate, and realize the intelligentization, customization and high efficiency of operation and maintenance personnel training from demand analysis, capability assessment, content generation to plan execution.

The invention relates to the technical field of emergency drill evaluation, in particular to a chemical storage tank area fire emergency drill intelligent evaluation system and evaluation method.The multi-source monitoring terminal is arranged in a preset key area of a chemical storage tank area and used for collecting multi-dimensional sensing data of a drill site; the data transmission network is connected with the multi-source monitoring terminal and is used for transmitting the multi-dimensional sensing data in real time; and the background processing center is connected with the data transmission network and is used for receiving and processing the multi-dimensional sensing data. The effectiveness of fire extinguishing operation is quantitatively evaluated through an intelligent algorithm, accurate data support is provided, and the evaluation accuracy is improved; a detailed evaluation report is automatically generated, the evaluation period is greatly shortened, and the timeliness is improved; advantages and deficiencies of drilling are clearly pointed out, targeted improvement suggestions are provided, and emergency plan optimization is assisted; the thermal imaging technology penetrates through the smoke to monitor the temperature, and the dangerous area identification and fire behavior judgment capability is improved.

The invention relates to a Bayesian theory-based virtual-real fusion life and reliability evaluation method, which introduces a Bayesian theory to carry out life and reliability evaluation research aiming at the problems of limited sample size, incomplete test data, more uncertainty factors and the like in life evaluation of electronic products. According to the technical scheme, the method comprises the following steps: firstly, dividing prior distribution and sample data according to obtained simulation data and test data; secondly, combining prior distribution with sample information according to a Bayesian theory, and deriving posterior probability distribution of parameters; and finally, comparing and verifying the precision of the fusion evaluation method according to actual test data. The patent mainly realizes effective fusion of electronic product simulation priori knowledge and newly acquired test data, and improves the evaluation accuracy and robustness under the conditions of small samples and high uncertainty.

The motion quality evaluation method based on motion perception and double-flow space-time graph convolution relates to the motion quality evaluation field, solves the problems that the existing rehabilitation motion quality evaluation method is difficult to accurately model the cooperation between joints, the fixed joint grouping strategy is not flexible enough, the model has insufficient recognition of the detail differences of complex rehabilitation motions, and the reliability of the evaluation result is affected, a dynamic joint grouping strategy based on motion amplitude driving is provided, a double-flow STGCN architecture is designed, the position and orientation information of the joints are processed respectively and then fused, a two-stage self-attention module SADG is developed, the inter-group time sequence mode and the intra-group spatial relationship are modeled in stages, and multi-granularity feature interaction fusion is realized. The attention mechanism introduces a constraint guided by the motion amplitude, so that the attention weight is more interpretable and has physical meaning.

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.

This application relates to a method for cross-border digital certificate mutual recognition based on dynamic trust anchors, comprising: collecting and preprocessing multi-dimensional trust assessment data of cross-border certificate authorities; collaboratively training a global model using federated XGBoost combined with a scenario-based attention mechanism to output a real-time trust score; constructing a hierarchical dynamic trust chain based on the score and writing the evidence data into the blockchain; generating proofs based on the Groth16 algorithm to complete certificate verification under privacy protection; deploying smart contracts to execute trust warnings, dispute arbitration, and rule updates; monitoring score changes, adaptively adjusting, and triggering an abnormal circuit breaker mechanism. This invention achieves real-time updating of trust weights and dynamic reconstruction of the trust chain, improving the efficiency and security of cross-border mutual recognition while ensuring data privacy compliance.

The application provides a shipborne integrated array antenna and stealth radome integrated design method, reasonably allocates performance indexes of the integrated antenna and the stealth radome according to the use requirements of the shipborne equipment, selects a local array surface and a radome with a proper size to perform electromagnetic performance iterative optimization, and determines the final technical requirements of the integrated array antenna and the stealth radome through a reasonable index evaluation system, so that the function of ensuring that various functional performance indexes of the shipborne integrated array antenna after being installed in the radome meet the overall requirements of the ship is realized. The application helps the radome designer to determine the performance parameters of the radome, thereby reducing the design iteration times of the radome; and the overall performance of the antenna and the antenna array under the shipborne environment is accurately evaluated, and the accuracy of the antenna performance evaluation under the shipborne environment is improved.

This invention relates to the field of new energy technology, and provides a battery pack selection method, system, and computer. The battery pack selection method includes: acquiring several initial cell datasets and several initial auxiliary datasets from the battery pack to be repaired based on an online data platform; acquiring a correction coefficient table and updating the initial auxiliary datasets to updated auxiliary datasets; updating the initial cell datasets to updated cell datasets and calculating a benchmark dataset based on the updated cell datasets; acquiring several spare cell datasets and calculating a matching degree set based on the spare cell datasets, benchmark datasets, and updated auxiliary datasets; setting a comprehensive weight set and calculating a weighted comprehensive matching degree based on the matching degree set and the comprehensive weight set. By adopting the above method, the health status of the battery pack to be repaired and several spare battery packs is quantified and then matched for evaluation, realizing the use of spare battery packs to repair and group the battery pack to be repaired.

This application discloses a humidity control device for aerospace products used to simulate the low-humidity environment of space, addressing the problems of high equipment investment and high operating energy consumption associated with existing nitrogen replacement methods for humidity control in thermal cycling test chambers. This application includes a cold drying unit, an adsorption unit, a filtration unit, and a control unit. The cold drying unit initially removes moisture and some impurities from the air, followed by further drying and filtration by the adsorption unit, ultimately outputting dry, clean air. This application employs a modular design to achieve humidity control in the thermal cycling test chamber. Through a tiered drying process of pre-treatment by a cold dryer and fine treatment by an adsorption unit, system energy consumption is reduced. The system uses compressed air as its gas source, eliminating the need for continuous consumption of expensive media such as nitrogen. While ensuring the provision of ultra-low dew point dry air, it boasts significant advantages of low operating costs and high economic efficiency, effectively preventing material degradation caused by condensation during testing.

The application provides a tunnel lining concrete evaluation method and system, and belongs to the technical field of tunnel lining quality detection. The method comprises the following steps: a data acquisition and matrix construction step: obtaining full polarization data and establishing a complex domain scattering matrix of each sampling point; a spatial phase locking step: constructing a spatial phase locking loop, tracking the spatial phase of the steel bar in real time, determining the locking state according to the phase difference and determining the steel bar high-weight prediction area; a polarization feature calculation step: in the steel bar high-weight prediction area, performing eigenvalue decomposition on the local covariance matrix, calculating the polarization entropy and the average scattering angle; an adaptive projection stripping step: generating an adaptive gain factor and adjusting the projection strength of the projection matrix, performing projection transformation on the original polarization vector to obtain a residual signal; and an evaluation step: reconstructing a defect signal based on the residual signal to evaluate the quality of the tunnel concrete lining. The scheme can improve the accuracy of tunnel concrete lining quality evaluation.

The application provides a method and system for fertility guidance based on deep learning image recognition. The method comprises: obtaining environmental data by a pre-set test paper collection module, determining whether the environment is qualified, starting the focusing auxiliary function, obtaining test paper image data and uploading to the cloud after obtaining the test paper image data, and obtaining effective test paper image data after the cloud server processes the test paper image data; obtaining a test paper result quantitative value by weighting calculation according to a test paper quantitative parameter; obtaining a test paper detection state by threshold comparison of the test paper result quantitative value; thereby improving the accuracy of test paper detection state evaluation through the judgment of the collection environment state, the calculation of the test paper result quantitative value and the threshold comparison.

This invention discloses a method and apparatus for operational risk assessment based on multidimensional data. The method includes: acquiring operational information of a target device, including basic attribute information, real-time status information, and wear and tear maintenance information; determining whether the target device meets preset basic operational assessment conditions based on the operational information; and if so, determining the operational risk assessment result corresponding to the target device based on the operational information and the preset operational assessment conditions. Therefore, this invention can intelligently realize the function of equipment operational risk assessment, which is beneficial to improving the comprehensiveness and scientific nature of the equipment operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment results, and also improving the efficiency and convenience of determining the operational risk assessment results.

The embodiment of the application discloses a kind of equipment health assessment method and device based on multidimensional data fusion and dynamic weight, it is related to the intelligent monitoring and health assessment technology of equipment complex system in the field of equipment health management, the present application includes: respectively from the regression trend of health parameter with time, the correlation between different health parameters and the angle of health parameter data probability distribution, describe the change with the increase of equipment storage life of health parameter, accurately reflect the difference between health parameter monitoring data and baseline data.Propose storage whole process weight dynamic updating method, scientifically calculate the weight of different health parameters when calculating health index.Thereby effectively solve the problem of health parameter monitoring data scarcity caused by inability to frequently power test during actual storage and use of equipment, improve the evaluation accuracy of equipment health state under the condition of limited monitoring data.

The application relates to the technical field of photovoltaic power station evaluation, and particularly discloses a photovoltaic power station total solar radiation data correction method and system. The method uses high-precision ground surface radiation observation sequence data of a solar radiation in a certain range of the power station, corrects a weather scale radiation component, namely a low-frequency component, of meteorological satellite radiation sequence data at a position of the power station according to spatial similarity and randomness of total solar radiation through a wavelet analysis method, reduces deviation caused by an optical thickness related parameter model inversion, and improves evaluation accuracy of satellite radiation data.

The application discloses a lithium battery operation state evaluation system and method based on data analysis, relates to the technical field of lithium battery operation state evaluation, collects electric excitation response data of a battery under different measurement parameters, generates an impedance spectrum tensor, carries out normalization processing on the impedance spectrum tensor along a temperature dimension, outputs a temperature decoupling impedance tensor, decomposes the temperature decoupling impedance tensor along a rate dimension, outputs a rate separation impedance matrix, extracts static contact impedance from the rate separation impedance matrix, carries out trend deduction along a state of charge dimension, outputs a charge decoupling impedance sequence, decomposes the charge decoupling impedance sequence, outputs a contact impedance fluctuation sequence, carries out filtering processing on the rate separation impedance matrix according to the contact impedance fluctuation sequence, outputs a corrected internal resistance spectrum, calculates a real health state of the battery based on the corrected internal resistance spectrum and carries out determination, and outputs a battery health state signal.