279results about How to "Accurate assessment" patented technology

The invention relates to the technical field of first-aid repair tower safety assessment, and discloses a first-aid repair tower safety risk assessment method and device, and the method comprises the steps: building a first-aid repair tower assessment model based on a Bayesian neural network, and enabling the first-aid repair tower assessment model to comprise an input layer node, a middle layer node and an output layer node, the input layer node represents a risk cause of the first-aid repair tower, the middle layer node represents a middle assessment node of the risk of the first-aid repair tower, and the output layer node represents a risk assessment target of the first-aid repair tower; acquiring first-aid repair tower data and environment data; inputting the first-aid repair tower data and the environment data into the first-aid repair tower evaluation model for probabilistic reasoning to obtain state probability distribution of the output layer nodes; and performing risk assessment on the first-aid repair tower according to the state probability distribution of the output layer nodes.

The invention discloses a server test environment guarantee method and system based on dynamic simulation, a storage medium and computer equipment. The method comprises the steps that the air inlet temperature, real-time power consumption and heat dissipation strategy signals of a tested server and the actual environment temperature of an incubator are collected in real time; dynamically setting the temperature of the air inlet of the tested server as the target environment temperature of the incubator, and calculating the real-time temperature deviation between the actual environment temperature and the target environment temperature; if the real-time temperature deviation exceeds a preset threshold value, a dynamic PID control algorithm is triggered, a basic control quantity is obtained through calculation according to the real-time temperature deviation through the dynamic PID control algorithm, a dynamic compensation quantity is obtained through calculation according to the target environment temperature, the real-time power consumption and the heat dissipation strategy signal, and the heat dissipation strategy signal is obtained based on the basic control quantity and the dynamic compensation quantity. Generating a temperature control instruction of the incubator; according to the temperature control instruction, a refrigerating or heating device of the incubator is dynamically adjusted so as to guarantee the test environment of the tested server.

The application discloses a kind of multi-modal hierarchical fusion network-based motor function multidimensional intelligent evaluation method and system. First, multi-modal data input is carried out, and the original data from the sensor is received;Then data preprocessing and feature extraction are performed, signal filtering, segmentation, alignment and feature extraction are completed;Efficient fusion of multi-modal data is realized by using MMHF-Net core model;Finally, multi-scale evaluation result output is realized, which is used to generate macro, meso and micro three-level evaluation results. The present application deeply fuses kinematics, electromyography, electroencephalogram and visual information, accurately restores the motor control process, and the evaluation accuracy is significantly better than that of single modal method. The proposed multi-modal hierarchical fusion network MMHF-Net can model multi-modal spatio-temporal interaction and dynamically focus on key information, while outputting scale scores, sub-project indicators and recognition results, providing fine-grained clinical insights, and achieving excellent generalization performance relying on multi-task learning and data augmentation.

The utility model discloses a kind of ceramic finger thermal shock deterioration experimental device, comprising: first box, heating unit is arranged, for heating target product;Second box, linear guide is arranged, for moving target product;Wherein, the target product end is detachably connected with the linear guide by connecting block. In the utility model, box is divided into cold and hot two groups of closed cavities, heating is carried out by heating unit arranged in the heating cavity of first box, and linear guide in the cooling cavity of second box is used to transfer target finger during testing, various operating conditions in actual working process can be simulated, whether fracture occurs is monitored by connected sensor, and then whether product is truly in line with actual service life requirement is accurately evaluated.

The application relates to the technical field of batteries, and provides a battery negative electrode potential evaluation system, a battery negative electrode potential evaluation method and an electric vehicle. The system comprises a data acquisition device configured to acquire battery surface stress data; and a controller configured to: determine a current high stress concentration area and an area of the current high stress concentration area based on current battery surface stress data; determine a current change rate of the area of the high stress concentration area with respect to a battery SOC based on the area of the current high stress concentration area, a current battery SOC, a historical area of the high stress concentration area and a historical battery SOC; and in the case that the current change rate is greater than a preset change rate threshold, substitute the current battery SOC into a mapping relationship model of the SOC and the negative electrode potential to obtain a current battery negative electrode potential. The application does not need to depend on a complex electrochemical model or additional hardware, has low calculation cost, good real-time performance, can be deployed on a large scale at a vehicle end, and is beneficial to early warning of lithium precipitation risk before lithium precipitation occurs.

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 discloses a performance evaluation method for an internal insulating medium of an oil-immersed capacitor based on a RBF neural network, and the method comprises the following steps: measuring characteristic variables of the internal insulating medium of the oil-immersed capacitor to construct training samples; constructing a RBF neural network model; optimizing initial weights and thresholds of the RBF neural network model; iteratively training the RBF neural network model by using the training samples to obtain a trained RBF neural network model; and evaluating the performance of the RBF neural network model by using the trained RBF neural network model.

The invention relates to the technical field of motion terrorism risk assessment, in particular to a spine endoscopic postoperative motion terrorism assessment method and system based on a 5E rehabilitation mode. According to the degree of adaptation of a patient to all rehabilitation trainings of the same type in each treatment stage and the change synchronization degree of rehabilitation state values, and the difference of entry scores of the same entry of an analysis questionnaire corresponding to the rehabilitation trainings and an adjacent next questionnaire, the rehabilitation training is analyzed; the association degree between each rehabilitation training of each treatment stage and each item of the questionnaire is obtained; adjusting the entry score of each entry of each questionnaire by using the correlation degree, and obtaining an optimized TSK total score of the corresponding questionnaire; and based on the optimized TSK total score of the questionnaire in all treatment stages, evaluating the motion terrorism symptom of the patient. According to the method, the entry score of the questionnaire is adjusted through the association degree between each rehabilitation training and the entry of the questionnaire, so that the influence degree of drug interference factors, physiological stress response and the like is reduced, and the accuracy of acterrorism symptom rating is effectively improved.

The invention discloses a judgment document element extraction method based on a large model, a storage medium and equipment, and the method comprises the steps: collecting a large number of judgment documents, carrying out the cleaning and word segmentation of each judgment document, and marking key element information; taking the judgment document as the input of the large language model, outputting a key element extraction result of the judgment document, setting a reward function based on the marked key element information, and performing feedback optimization on the large language model in combination with a dominant actor-commentator algorithm; and inputting a newly obtained judgment document into the optimized large language model, and extracting key element information. The judgment document element information can be accurately extracted, the analysis efficiency and accuracy of the judgment document are effectively improved, and manual intervention is reduced.

The present application relates to the field of health care information technology, in particular to an interventional operation risk assessment method and system, first, the abnormal period curve is divided in the waveform curve to be analyzed; in the abnormal period curve, according to the change situation of the periodic abnormality metric of periodic fluctuation curve with time sequence, the recovery ability index of abnormal period curve is acquired;According to the overall distribution of the periodic abnormality metric of all periodic fluctuation curves included in the abnormal period curve, the electrocardiogram abnormality index of the abnormal period curve is acquired;In the waveform curve to be analyzed, according to the recovery ability index and electrocardiogram abnormality index of all abnormal period curves, the local risk index of the waveform curve to be analyzed is acquired;According to the local risk index of the electrocardiogram waveform curve corresponding to all leads of the patient, the interventional operation risk of the patient is evaluated. The present application excavates the recovery ability situation and overall risk situation of the heart abnormality in depth to improve the risk assessment accuracy.

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 fire protection planning technology, specifically a method for fire station layout and fire equipment configuration based on GeoAI. The method includes: acquiring spatial data related to building identification and constructing a multi-source dataset; determining fire rescue demand points and types based on socio-semantic segmentation using a visual language model, and constructing a dynamic database of fire stations and fire equipment; establishing a comprehensive demand paradigm for fire rescue equipment and decomposing its equipment subsets; determining the optimal pairing of fire rescue demand points with multiple fire stations and evaluating the comprehensive weighted response time; identifying areas with weak fire rescue coverage and determining the initial locations of each candidate fire station; iteratively optimizing the locations of candidate stations to determine the proposed fire station layout scheme; optimizing the spatial layout and equipment configuration of fire stations in conjunction with fire rescue response capabilities; and outputting the fire station layout and fire equipment configuration scheme. This invention achieves differentiated and refined configuration of fire station site selection and equipment, providing a scientific basis for fire protection planning.

The application discloses a kind of hardness correlation liver cancer lung premetastatic niche mouse model construction method, it includes the following steps: (1) in vitro enrichment respectively on the low hardness substrate of hardness 6kPa and the high hardness substrate of hardness 16kPa, the condition culture supernatant of mouse liver cancer cell Hepa1-6 that is cultured and grows, respectively named mL-CM and mH-CM;(2) mL-CM and mH-CM are respectively injected into two groups of mice using tail vein injection mode, every 1 day injection 1 time, until the 26th day, during continuous monitoring the recruitment of BMDCs in fresh lung tissue, while with the induction endpoint, i.e. 26th day premetastatic niche mark feature detection includes lung tissue matrix remodeling, immunosuppression, angiogenesis, vascular permeability and inflammation etc..The method has the advantages of short modeling cycle, easy operation, controllable induction condition, can comprehensively and accurately evaluate the common characteristics of liver cancer lung premetastatic niche formation etc..

This invention discloses a UAV inspection method and system for bridge bearings. The method includes: planning a strip-shaped flight path and constructing a coarse 3D point cloud model of the bridge; then planning a scanning flight path around the bridge's outer envelope to collect fine point clouds of bridge components; firstly, using a small amount of labeled data combined with pseudo-label generation and knowledge distillation to complete lightweight training of the PointNet model; then, strengthening structural association features through a contextual attention mechanism and generating virtual points using an occlusion region feature completion method to complete the occluded region and obtain a complete bearing point set; finally, extracting bearing geometric parameters by weighted noise point removal, iteratively fitting bounding boxes, and smoothing; planning a flight path based on the bearing's location to collect the bearing's surface image; then performing image cleaning and enhancement processing, and finally identifying surface defects using image recognition methods to generate an inspection report. Comprehensive technical support is provided.

The application discloses a kind of ship intelligent navigation algorithm simulation verification system and test method, the system uses four-layer modular structure, including: virtual navigation environment module, standardization data interaction module, algorithm execution module, quantitative evaluation module;Between each module, standardization data interaction module is realized two-way data transmission, forms the complete simulation verification system capable of independent test and closed-loop operation.The method, using the system, the steps are: step 1: build inland virtual navigation scene, step 2: select test mode and configure algorithm, step 3: start simulation and data acquisition, step 4: evaluation index calculation, step 5: generate verification report.The algorithm unit of the application can be independently accessed to test, without overall reconstruction, perception, decision-making, control algorithm can be quickly adapted, greatly reduce the difficulty of integration debugging, improve algorithm development and verification efficiency, effectively shorten the intelligent ship development cycle.

The application provides a drought propagation analysis method and system considering multi-dimensional characteristics of drought events. The method comprises the following steps: calculating a drought duration propagation index based on a meteorological drought total duration and an agricultural drought total duration; calculating a drought intensity propagation index based on meteorological drought intensities of previous meteorological drought events and agricultural drought intensities of previous agricultural drought events; calculating a drought intensity trend propagation index based on meteorological drought intensity trends of previous meteorological drought events and agricultural drought intensity trends of previous agricultural drought events; calculating a drought fluctuation propagation index based on meteorological drought index fluctuation rates of previous meteorological drought events and agricultural drought index fluctuation rates of previous agricultural drought events; calculating a drought probability propagation index based on a meteorological drought occurrence probability and an agricultural drought occurrence probability of a target region within a given time period; and constructing a comprehensive drought propagation index by using a CRITIC objective weighting method. The application can accurately describe the propagation process between meteorological drought and agricultural drought.

The present application relates to the technical field of oil and gas development, in particular to a kind of oilfield water drive extra-high water cut late double-determination double-exchange adjustment method.The present application determines first abnormal characteristic value by analyzing the abnormal change characteristics of layer pressure and layer flow in the process of layer injection test, and combining the difference degree between the abnormal change characteristics of layer pressure and layer flow;Second abnormal characteristic value is obtained based on the mutation peak characteristics of layer pressure and layer flow by analyzing the mutation peak characteristics;Abnormal jamming evaluation value is determined by combining first abnormal characteristic value and second abnormal characteristic value, and the process of layer injection test is regulated using abnormal jamming evaluation value;After regulation, the layer indication curve of layer injection well is measured;Double-determination double-exchange adjustment is carried out based on layer indication curve.The present application accurately evaluates the abnormal jamming characteristics in the process of layer injection test, and more accurately controls the process of layer injection test.

The application relates to the technical field of large language model privacy protection, and discloses a sensitive data processing method and system combining privacy scores and dynamic thresholds. The method comprises the following steps: obtaining user input text in a scene dimension, determining each word segmentation and each privacy word of the input text; based on the attention mechanism of a large language model, calculating a basic privacy score of the input text according to the privacy word weight of each word segmentation, calculating an associated risk enhancement score of the input text according to the privacy word co-occurrence frequency of each privacy word pair, and determining a comprehensive privacy score of the input text according to the basic privacy score and the associated risk enhancement score; obtaining historical comprehensive privacy score statistical data in the scene dimension, determining a dynamic threshold according to the privacy word occurrence frequency of the input text and the historical comprehensive privacy score statistical data; and performing corresponding operations on the input text according to the comparison result of the comprehensive privacy score and the dynamic threshold. The privacy safety of a user in the interaction process with a large language model can be effectively protected.

The application belongs to the technical field of material engineering and failure analysis, and particularly relates to a metal fatigue micro-damage detection method, device, medium and equipment, the method comprising the following steps: acquiring a longitudinal wave sound velocity of a metal material to be detected; calculating a normalized damage index of the metal material to be detected based on the longitudinal wave sound velocity; taking the normalized damage index as an input of a fatigue micro-damage evaluation model that has been constructed, and obtaining a plastic strain of the metal material to be detected, so as to realize fatigue micro-damage detection of the metal material to be detected. The application can improve the sensitivity of metal fatigue micro-damage detection.

This invention discloses a phase error tracking method and system based on dual weighting in OFDM systems, belonging to the field of wireless communication system technology. This application introduces a dual weighting mechanism to simultaneously evaluate and utilize static reference quality weights and dynamic measurement quality weights, thereby obtaining a more accurate estimate of channel phase error and significantly improving the performance of the communication system in harsh channel environments. Compared with the prior art, this application not only considers the quality of real-time measurement, but also incorporates the "historical" quality of the reference information used as the measurement benchmark, making the weight evaluation more comprehensive and accurate. It can effectively suppress the systematic bias introduced by the weights and prevent the propagation and contamination of errors throughout the entire data packet processing process. Moreover, in complex multipath channels, the dual weighting mechanism of this application can accurately identify and "ignore" continuously unreliable information sources, greatly enhancing the survivability of the system in harsh environments.

This application relates to the field of image recognition technology, specifically to a visually assisted method and system for quality inspection of laser engraving on mobile phone buttons, solving the technical problem that the accuracy of laser engraving quality inspection of mobile phone buttons in the prior art cannot meet the requirements. The method includes: acquiring image sequences of the laser engraved area of ​​the mobile phone button under multiple different lighting directions, and design trajectory information; determining the microscopic gradient vector field and texture contrast value of the laser engraved area based on the image sequences; constructing a light transmission resistance field based on the geometric deviation between the macroscopic light transmission direction and the microscopic gradient vector field, characterized by the design trajectory information, and the texture contrast value; calculating the light transmission attenuation index, which characterizes the overall light transmittance performance of the laser engraved area to be inspected, based on the light transmission attenuation field; and determining the light transmittance quality of the laser engraved area to be inspected based on the light transmission attenuation index.

The application provides a fetal electrocardio monitoring system based on data analysis, and belongs to the technical field of electrocardio monitoring, and specifically comprises the following steps: collecting a mixed signal, removing power frequency interference by using an IIR notch filter, removing baseline drift by using a median filter, and removing artificial pulse interference by using empirical mode decomposition; extracting a maternal signal by using an independent component analysis method, constructing a singular value transfer matrix, taking the maternal abdominal wall electrocardio signal as spatial filtering, offsetting the maternal signal by singular value decomposition; extracting a fetal signal by using the independent component analysis method again; determining a fetal electrocardio R wave peak by using a time domain nonlinear transformation threshold method, performing clustering detection on the R wave peak, calculating a fetal heart rate according to the time difference of RR intervals; analyzing low frequency components LF and high frequency components HF in a maternal heart rate signal, calculating an LF / HF value of the maternal heart rate, and judging whether the maternal body has an anxiety emotion; and the application realizes more convenient and accurate fetal heart monitoring.

The invention provides a power transmission line forest fire protection decision-making method based on bidirectional coupling digital twinning, and relates to the technical field of power transmission line forest fire protection, and the method comprises the steps: constructing a power transmission line digital twinning model; constructing a forest fire evolution digital twinborn model; coupling the forest fire evolution digital twinborn model with the power transmission line digital twinborn model; respectively inserting the mountain fire initial state constraint condition and the protection action combination into the line-mountain fire coupling model, executing multi-scene parallel fitting, and constructing a line risk evolution result; and executing multi-objective optimization analysis of a protection action by utilizing a line risk evolution result, a line operation influence index and a protection resource constraint condition, and establishing a protection decision scheme. According to the method and the device, the technical problem that the accuracy of a power transmission line protection decision is further influenced due to forest fire risk situation perception fragmentation caused by space-time blind areas and false alarms of single-source monitoring data in the prior art is solved, and the accuracy of the power transmission line protection decision is improved by combining digital twinning.

The application relates to a driving behavior evaluation method, a computer program product, equipment and a storage medium, comprising: obtaining time-labeled driving data of a target vehicle; dividing the driving data into multiple segments according to a preset time period, and respectively counting road condition characteristic data and driving style characteristic data of each segment according to the driving data; respectively determining a corresponding road condition, a frequency weight of the road condition and an evaluation weight of the road condition of each segment according to the road condition characteristic data; respectively determining a corresponding driving style of each segment according to the driving style characteristic data; and obtaining a driving behavior evaluation result of the target vehicle based on a preset basic score corresponding to each driving style, in combination with the corresponding road condition of each segment, the evaluation weight and the frequency weight of each road condition. The application realizes accurate evaluation of continuous, long-time and complex driving behavior, measures the risk of the driving behavior of a driver, and improves the objectivity and accuracy of driving behavior evaluation.

The invention provides a traffic scheduling method and device, equipment and a storage medium, and the method comprises the steps: determining the current health degree of each link according to the historical health degree of each link and each index value in a current time period; therefore, the health degree is determined more accurately, and the link health degree is evaluated more accurately. In addition, a data transmission mode between the first network device and the second network device is determined according to the current health degree of each link, and then a flow scheduling rule in the corresponding data transmission mode is determined. Therefore, the dynamic transfer of each link can be determined, and the situation that the links are idle is avoided, so that the link utilization maximization and experience optimization are realized. The method is suitable for various IP network environments and various network topology structures, can be used for traditional copper cable access and wireless access scenes, and can also be used for optical fiber access scenes including an FTTR (Fiber To The Room) all-optical access network.

The utility model relates to the technical field of workpiece production, and provides an automatic detection device for shaft workpieces, which comprises a feeding unit, a first detection unit, a conveying unit, a second detection unit, a third detection unit, a fourth detection unit and a sorting unit, and realizes full-automatic operation from feeding to final classification of the shaft workpieces. The detection efficiency is obviously improved; wherein the first detection unit is used for carrying out visual detection on a workpiece, the second detection unit is used for carrying out length dimension detection on the workpiece, and automatic transfer of the workpiece is realized through switching of the rotating seat between a first working position and a second working position; the third detection unit is used for performing eddy current flaw detection on the workpiece; the fourth detection unit is used for detecting the eccentricity of the workpiece; through a method of combining multiple detection modes, the quality condition of the shaft workpiece can be comprehensively and accurately evaluated, and it is ensured that each outgoing product meets the high-standard quality requirement.

This invention relates to a descaling and sterilization method for an intelligent bladeless fan and the fan itself, relating to the field of smart home appliances. The method includes: acquiring preset water hardness, water tank temperature, water storage time, and real-time scale buildup on an ultraviolet lamp; recording the number of pumping operations during the storage time; matching an appropriate pumping speed based on the real-time scale buildup when the real-time scale buildup is not less than a preset high scale buildup; pumping water at the specified speed; pumping water at a preset initial speed and closing the return valve when the real-time scale buildup is not greater than a preset low scale buildup, recording the pumping time at the specified speed; establishing a scale prediction model by recording water hardness, pumping speed, pumping time, and water tank temperature in a preset scale model database; simulating the scale formation rate and time based on the scale prediction model, and cleaning the scale when the scale formation time is reached. This application improves the fan's disinfection effect.

Embodiments of the present application provide a building network quality evaluation method and device, electronic equipment and medium, the method comprises: obtaining the historical connection number of each base station in the base station list of the target building; determining the permanent user of the target building according to the historical connection number; when detecting that the permanent user enters the target building, obtaining the real-time signaling data of the permanent user; and evaluating the network quality of the target building according to the real-time signaling data. Through the embodiments of the present application, the building network quality is accurately evaluated based on the real-time signaling data of the permanent user.

This invention relates to the fields of geographic information systems and underground pipeline detection technology, and discloses a buried optical cable detection system, including an optical cable detection module, an optical cable data acquisition module, an optical cable data analysis module, an optical cable data evaluation module, and a buried optimization module. The optical cable detection module is responsible for the preliminary detection of the location and depth of the underground optical cable. The optical cable data acquisition module is used to collect existing optical cable pipeline data and input business data. The optical cable data acquisition module includes a location data unit, a depth data unit, an environmental interference data unit, and an optical cable attribute data unit. The optical cable data analysis module calculates and analyzes the four units of data collected by the optical cable data acquisition module. The optical cable data analysis module includes an anti-interference correction unit, a depth calculation optimization unit, and a non-destructive access evaluation unit. The optical cable data evaluation module evaluates the data based on the analysis results of the optical cable data analysis module. The buried optimization module optimizes the data based on the evaluation information from the optical cable data evaluation module.

The invention discloses a transformer substation site selection data processing and feedback method, system and device based on unmanned aerial vehicle-AI cooperation and a medium, and belongs to the technical field of intelligent site selection of electric power engineering, and the method comprises the steps: controlling an unmanned aerial vehicle to shoot a transformer substation site selection region according to a preset flight route, and obtaining a site selection region image; performing preprocessing and feature extraction on the site selection area image to obtain key environment element information; inputting the key environment element information into a pre-trained site selection environment evaluation model to obtain an evaluation result, including a terrain suitability grade, infrastructure proximity and a comprehensive site selection feasibility score; according to the evaluation result and a preset engineering constraint rule base, matching an avoidance suggestion; and displaying the avoidance suggestions. According to the method, site selection suggestions can be provided for decision makers in a shorter time, the advancing speed of substation construction projects is increased, the advantages and disadvantages of site selection can be judged more objectively and accurately, and the risk of site selection errors caused by human factors or insufficient data is reduced.