67results about How to "Ensure objectivity" patented technology

The application discloses a kind of full-diameter core radial permeability test error calculation methods, belong to oil and gas exploration technical field, it is characterized in that, include the following steps: a, preparation core;B, the true value k of permeability when the texture of core and the end surface of core are parallel is calculated / / ; the true value of permeability when the texture of core and the end surface of core are vertical is calculated to simulate the permeability value c that passes through the left and right sides of cuboid;D, the radial permeability test error value ε of core is calculated by formula 5.The application can carry out error analysis to core radial permeability test, effectively estimate the accuracy of core radial permeability test, carry out reliability evaluation to core radial permeability test.

This invention discloses an automatic verification and risk warning method for international trade information based on smart ports. It collects multi-source document data, including customs declarations, bills of lading, transportation routes, payment vouchers, and certificates of origin, and converts them into a standardized format through field mapping rules. A cross-document verification rule base is established, and rule matching is performed on key fields such as invoice amount and declared price, and bill of lading quantity and packing list, using a weighted scoring mechanism to calculate consistency scores. A spatiotemporal graph of trade behavior is constructed, and risk characteristics are statistically analyzed using an improved random walk algorithm, outputting a dynamic risk feature matrix. This matrix is ​​matched with a historical risk case database, and the probability of risks such as smuggling, false declarations, and tax evasion is calculated in conjunction with regional risk benchmarks. Risk thresholds are dynamically adjusted based on port clearance flow, triggering adaptive warnings and generating warning information including warning level, risk type, and inspection measures, thereby improving the intelligence level of port supervision.

This utility model relates to a training system and hand probe device for security personnel, comprising: a training uniform, a mannequin, and a hand probe device; the training uniform is worn on the mannequin, and a wireless communication tag is affixed to a predetermined position on the inside of the uniform; the hand probe device communicates wirelessly with a client, and one or more wireless communication tag readers are installed within the hand probe device. This utility model facilitates in-depth analysis and accurate feedback of training content, effectively avoids the subjectivity and arbitrariness of manual assessment, ensures the objectivity and consistency of assessment results, and helps improve the quality and effectiveness of security personnel training.

The present application relates to the technical field of data processing and business intelligence, and discloses a multi-dimensional data driven self-brand growth value prediction method, which extracts a main feature vector of a previous time step, calculates a dynamic weight for a same-product white label control group to generate a dynamic benchmark, and accordingly peels off a pure brand-driven incremental index, and combines a repeat purchase decay rate and a search index to construct a three-dimensional state vector; through eigenvalue decomposition on a state covariance matrix, a current main feature vector and a maximum eigenvalue are obtained, and the main feature vector is fed back to a weight calculation link to form a closed loop; finally, the decomposition result and a historical state sequence are respectively input into a pre-trained machine learning model to output a brand life cycle stage and a future brand asset valuation. The present application accurately anchors a reference system through a dynamic feedback mechanism, and realizes comprehensive and accurate diagnosis and prediction of brand value.

This invention relates to an equivalent accelerated testing method for plexiglass based on creep constitutive equations, belonging to the technical field of accelerated testing of polymer structures. Addressing the testing requirements for the creep performance of plexiglass structures, this invention shortens the testing cycle and saves testing costs through the design of testing temperature and pressure. Simultaneously, the reduced testing time indirectly saves manpower and material resources, and also reduces the frequency of random risks such as power outages and equipment failures. Therefore, the testing method of this invention has significant timeliness and economic efficiency, and can effectively improve the accuracy of quantitative analysis, possessing important value for engineering practice.

The invention relates to the technical field of artificial intelligence and human-computer interaction, and discloses a rehabilitation training adjustment method and system based on multi-modal feature fusion and a storage medium, and the method comprises the steps: obtaining voice, face and physiological signals, constructing a multi-modal data stream, extracting features, and outputting a speech error classification identifier and a physiological signal quality index; splitting the facial action net displacement into healthy and affected sides, correcting affected side features based on healthy side features, and constructing visual representation; fusing each feature to output a comprehensive state vector; updating a dynamic baseline in a task gap, mapping a state vector, and screening to obtain an effective action set; calculating a composite reward and storing the composite reward in an experience playback pool to update the strategy network; and based on the action set, re-weighting the large model output probability, and generating a target interaction corpus. According to the method, the state sensing precision is improved by correcting the deviation of the affected side through the uninjured side, and a closed loop of self-adaptive adjustment of the rehabilitation difficulty and safe interaction text generation is realized by combining the dynamic baseline and penalty mechanism optimization reinforcement learning.

The application relates to the technical field of interface measurement, and discloses an electrolytic aluminum electrolyte aluminum liquid interface measurement system based on conductive characteristics, which comprises a data acquisition module that obtains impedance distribution data at different depth positions by controlling a probe to move in a vertical direction and collecting impedance signals; the data acquisition module adopts a multi-frequency excitation mode to obtain impedance responses at different frequencies during the movement of the probe, and adaptively adjusts the movement speed of the sampling probe according to the stability of the collected signals; an impedance change rate is extracted according to the impedance distribution data, the interface is judged based on the impedance change rate, and a candidate interface of the electrolytic aluminum electrolyte aluminum liquid is determined; one candidate interface of the electrolytic aluminum electrolyte aluminum liquid is selected, random multi-point measurement is carried out in the horizontal direction of the candidate interface, measurement information in the horizontal direction of the candidate interface is collected, and an evaluation model is constructed; and the application helps to improve the recognition accuracy of the interface.

This invention discloses a method, device, and medium for assessing street light leakage risk based on residual current, relating to the field of street light risk assessment technology. The method includes dividing historical residual current data from the low-voltage side of a dedicated street light transformer into a risk-to-be-investigated dataset and a normal baseline dataset; calculating the baseline mean and baseline standard deviation based on the normal baseline dataset; calculating the investigation mean based on the risk-to-be-investigated dataset; if the difference between the investigation mean and the baseline mean is greater than or equal to n times the baseline standard deviation, the dedicated street light transformer is determined to have a high risk of water immersion leakage; for street lights within the power supply range of a dedicated street light transformer with a high risk of water immersion leakage, the street lights with high water immersion leakage risk are determined based on a comparison of the vertical height of the bottom edge of their maintenance door from the ground and a water depth threshold. This invention, by establishing a dynamic statistical benchmark and significance testing, achieves the distinction between normal aging current of the line and sudden water immersion current during rainstorms.

This invention belongs to the field of carbon asset assessment technology, specifically relating to a method and system for carbon asset potential analysis and assessment based on multi-indicator comprehensive evaluation. The method includes the following steps: generating correction factors based on historical emission data of carbon assets; correcting historical emission data using the correction factors to obtain corrected emission values; and determining the assessment level of the carbon asset based on the corrected emission values. This invention identifies peak and trough points in time series data to define peak and trough periods, compares the average emission value within a period with the global average emission value to determine whether it belongs to positive or negative fluctuations, and sets corresponding adjustment parameters. This qualitatively classifies and quantitatively characterizes historical fluctuations, identifying their existence and revealing their specific nature, providing dynamic characteristic basis for subsequent carbon asset potential analysis and assessment, thereby improving the accuracy of the assessment results.

The invention relates to the technical field of communication, and discloses an audio test method and system of a wireless audio transmitter and a storage medium. The audio testing method comprises the following steps: connecting a wireless audio transmitter with an audio input source through an audio receiving link of the wireless audio transmitter, and connecting the wireless audio transmitter with audio playing equipment through an audio sending link of the wireless audio transmitter; the audio input source is controlled to play a pre-stored standard test audio, and the wireless audio transmitter receives and obtains a first to-be-tested audio and analyzes the first to-be-tested audio to obtain a test result of the audio receiving link; and the wireless audio transmitter is controlled to play the pre-stored standard test audio, and the audio playing device receives and obtains the second to-be-tested audio and analyzes the second to-be-tested audio to obtain a test result of the audio sending link. According to the embodiment of the invention, automatic testing is adopted, objectivity and consistency of testing results can be ensured, core quality indexes can be accurately quantified, accurate detection results can be output, testing efficiency is greatly improved, and labor cost is reduced.

The application provides a kind of based on visual detection's sports glasses dimming film evaluation method and system, it is related to sports glasses manufacturing technical field, its technical solution main point is: by obtaining positioning map, determine clamping offset and correct, convert image to uniform lens coordinate, compare the candidate abnormal area in different images and determine its stability, finally mark effective feature and determine evaluation result, effectively solve the problem that visual information is unstable in prior art due to clamping deviation and observation condition change, ensure the objectivity and accuracy of evaluation result, have by clamping offset correction and image coordinate uniform, effectively eliminate the visual information fluctuation caused by clamping deviation and observation angle change, ensure that visual information accurately reflects the real state of film, thereby improve the objectivity and accuracy of evaluation result.

The invention belongs to the technical field of lightning positioning, and particularly relates to a lightning positioning method based on low-frequency whistle wave dispersion characteristics of an electromagnetic satellite, and the method comprises the steps: obtaining ELF / VLF electromagnetic field secondary data of an SCM load and an EFD load of a Zhang Heng No.1 satellite, and carrying out the time sequence reconstruction of original data; calculating satellite space physical coordinates, respectively generating dynamic power spectral density maps of the magnetic field data and the electric field data through short-time Fourier transform, and performing time alignment and cutting processing on the PSD maps; identifying whistle wave traces with continuous drop frequency characteristics on the PSD graph, and classifying regularly spaced whistle waves into multi-hop whistle events according to time continuity and morphological similarity; selecting high-frequency region feature points and low-frequency region feature points on each whistle wave trace, and recording coordinate data of the feature points if the high-frequency region feature points and the low-frequency region feature points are satisfied;

The invention provides a contact lens defect detection model training method and device, and relates to the technical field of image processing, the method comprises the steps of obtaining real sample data and real sample labeling data, customizing defect types and directionally generating sample labeling data, samples in the directional sample data comprise one or more defects, and samples in the directional sample data comprise one or more defects; and training the contact lens defect detection model by using the real sample data and the directional sample data. Due to customizing the defect data, contact lens samples containing specific or multiple defects are permitted to be generated in a targeted manner. The directionally generated samples can cover various defect types possibly encountered in actual production, and ensure that the model can fully learn the characteristics of the defects in the training process, so that the defect detection precision and sensitivity are improved.

The invention discloses a supply chain ESG risk dynamic assessment method and system based on multi-source data fusion, and the method comprises the following steps: 1, collecting multi-source heterogeneous data at each node of a supply chain, processing the data, and generating a node data set containing ESG risk features; 2, based on the node data set generated in the step 1, in combination with attribute parameters of supply chain nodes and external dynamic information, adaptively generating a dynamic evaluation benchmark; and step 3, on the basis of the node data set generated in the step 1 and the dynamic assessment benchmark generated in the step 2, constructing a risk conduction model to carry out real-time risk assessment, and outputting an assessment result containing a risk conduction path. And multi-source implicit information is fused by combining a space and semantic association technology, so that the objectivity and comprehensiveness of an evaluation basis are ensured.

The application discloses an automatic image checking tool for a civil aircraft display system, wherein an image synchronization module is used for continuously sending a synchronization signal outward; an image acquisition module synchronously acquires a to-be-tested image and a standard image according to the synchronization signal and saves the to-be-tested image and the standard image onto a hard disk; an image cache module reads two-way image data in a fixed data format from the hard disk into a memory according to a checking rate; an image difference detection module obtains image pixel differences by performing pixel subtraction on the to-be-tested image and the standard image, eliminates noise point interference and highlights difference information through a plurality of graphic operations, and finally explicitly identifies each difference information through a mark box. An image checking result output module is used for recording the difference information. The application realizes the image checking function at the pixel level, can timely find and correct errors in the image, ensures that pilots obtain accurate information, and can meet the checking requirements of high reliability and high precision.

The application relates to the technical field of computer vision and image processing, and particularly discloses a paper surface mold spot growth dynamic detection method and device; the detection method comprises the following steps: S1, acquiring a surface visible light image of a paper sample to be detected; S2, pre-processing the surface visible light image; S3, inputting the pre-processed image into a mold spot segmentation model pre-trained to obtain a pixel-level segmentation result image, wherein the segmentation result image at least contains a mold spot area category and a paper healthy area category; and S4, based on the segmentation result image, calculating one or more quantitative indexes for representing mold spot growth states; the detection device comprises an image acquisition module, a preprocessing module, a segmentation module and an analysis module; and the application is beneficial to realizing high-precision segmentation of a paper surface mold spot area and dynamic quantitative analysis of a mold growth process.

The application relates to the technical field of production quality control, in particular to a cable production quality control method based on multi-source data; the method comprises the following steps: collecting multi-source production data on a cable production line; based on environment state data and process parameter data, calculating an environment comprehensive cooling coefficient at each collection time; based on the environment comprehensive cooling coefficient and the process parameter data, calculating a dynamic cooling rate factor at each collection time; calculating the proportion of the difference between the dynamic cooling rate factor and a preset optimal dynamic cooling rate factor in the optimal dynamic cooling rate factor, and obtaining a non-uniform crystallization risk index at each collection time; inputting the non-uniform crystallization risk index and the multi-source production data into a pre-trained dynamic Bayesian network model to obtain a predicted value of a cable quality parameter at the next collection time, and controlling the cable production quality; the problem that the cable production quality control effect is poor is solved.

The invention discloses a clone selection-based mourhua surface modeling method and related equipment, and the method constructs an'antibody-parameter 'iterative optimization framework by simulating the clone selection principle of an immune system, achieves the automatic and intelligent global search of key parameters, and improves the modeling efficiency. The defect that parameters are set by depending on artificial experience in a traditional method can be effectively overcome, and then the objectivity and repeatability of the model are ensured; through loop iteration of a series of collaborative operations such as initialization, evaluation, cloning, variation, supplementation and reselection, convergence from a preset parameter space to an optimal solution can be efficiently achieved, when a precision threshold value is met, stopping and outputting an optimal antibody are achieved, and it can be ensured that a high-precision mourhua face model is obtained in limited computing resources. According to the method, full-process automation from parameter initialization to optimal model output is realized, manual participation can be remarkably reduced, the modeling efficiency is improved, the calculation process is more stable and robust, and the method can be widely applied to the technical field of data processing.

Embodiments of the present disclosure provide a wireless charging test method, device and equipment for a vehicle. The method comprises: determining a test function; generating a test instruction corresponding to the test function; sending the test instruction to the wireless charging panel; monitoring state information fed back by the wireless charging panel after receiving the test instruction; and determining whether the test function of the wireless charging panel passes according to the state information. In this way, a unified operation paradigm and data collection standard are provided for all wireless charging tests, differences in test results caused by inconsistent test steps, conditions or evaluation criteria are eliminated, the accuracy of test results is improved, and since the test instruction is automatically generated and sent by the test host and the state information is automatically monitored and determined, the test efficiency and automation level can be significantly improved.

This utility model relates to the field of electrode paste column technology, specifically to a device for measuring the height of electrode paste columns in a calcium carbide plant. It includes a mounting plate, with three connecting plates arranged in a circular array fixedly connected to the bottom end of the mounting plate. Each connecting plate has a laser level gauge slidably contacted at its bottom end. A first rotating ring is rotatably connected to the bottom end of the mounting plate, and a bearing is fixedly connected to the bottom end of the first rotating ring. Compared with existing technologies, this utility model achieves automated, multi-point random sampling through a friction-driven random positioning system. This significantly improves the safety and efficiency of measurement and effectively avoids measurement errors caused by irregularities on the electrode paste column surface (such as gaps or inclination). Its core lies in using friction blocks with varying roughness to cause the rotating ring to rotate asynchronously and randomly, thereby controlling the final measurement position of the laser level gauge through a sliding rheostat, ensuring the objectivity and unbiasedness of the sampling.

The present application relates to a kind of shore-based container crane remote operation safety behavior evaluation method and electronic equipment, comprising: the operation action sequence of the driver to be evaluated is obtained and the state trajectory of work environment, construct multimodal time series dataset;Safety behavior benchmark model obtained by pre-training is called, and the behavior norm index under the expert strategy of operation trajectory is calculated;Operation action sequence is encoded, and the spatial risk sensitivity and time criticality of different work stages are quantified;Dynamic safety potential field model is constructed, and the repulsive potential energy between spreader and hoisting weight and environmental obstacles is calculated in real time, and trajectory safety margin index is generated;Fusion behavior norm index, spatial risk sensitivity and time criticality, and trajectory safety margin index, generate the safety behavior comprehensive evaluation result of the driver to be evaluated.The present application can automatically learn expert safety intent, have the differentiated evaluation ability to the space-time key characteristics of operation behavior, can effectively fuse physical world safety constraint.

The present application relates to the technical field of cable detection, in particular to a cable insulation state evaluation and early warning method based on transient traveling wave signal characteristics, comprising: distinguishing intra-zone faults and extra-zone faults according to the fault distance and the high-low frequency energy difference of the transient traveling wave signal, combining the topological structure of the current cable to be detected to determine the preliminary identified fault point; performing secondary regional mapping on the fault point, integrating the spatial position of each fault point through the direction information corresponding to the transient traveling wave signal to determine the fault region topological graph of each fault point combination; positioning the fault section corresponding to the current fault point according to the fault region topological graph data updated at any time; combining the identified fault section with the duration, intensity and frequency of fault occurrence to evaluate the insulation problem level of the corresponding fault section; comparing the insulation problem levels of the fault section under multiple analyses to perform early warning according to the coincidence of each fault section. The accuracy and efficiency of cable early warning are realized.

The invention discloses an automatic transmission project quality inspection system and method based on BIM model guidance and unmanned aerial vehicle multi-modal data fusion, and aims to solve the problems of low efficiency, high risk and insufficient precision of traditional quality inspection. The method comprises the following steps: firstly, controlling an unmanned aerial vehicle carrying a laser radar and a camera to collect high-precision point clouds and images of a completion line, and fusing the high-precision point clouds and images into a completion live-action digital model; secondly, millimeter-level accurate registration is carried out on the real scene model and a BIM model serving as a design benchmark; the method comprises the following core steps: performing BIM-guided targeted analysis, namely, automatically delimiting a local three-dimensional region of interest (ROI) in a live-action model based on the design position and size of a component in the BIM, and only calling an AI model in the ROI to identify a component instance and judge the installation state of the component instance; and finally, quantitatively calculating the deviation between the identified component instance and the BIM design parameters, and generating a visual quality inspection report containing multi-view evidence. According to the method, through a targeted analysis strategy of locating according to pictures, the efficiency, the stability and the precision of automatic quality inspection are greatly improved, objective, quantitative and full-coverage inspection of the quality of the power transmission project is realized, and a foundation is laid for digital delivery and operation and maintenance.

The embodiment of the present application provides an online control method and system of an electric dust removal system, and belongs to the technical field of electric dust removal. The method comprises the following steps: collecting real-time operation parameters of the electric dust removal system, and simulating operation conditions based on the real-time operation parameters; determining condition fitting parameters of each preset fitting path based on the simulated conditions; taking dust removal efficiency as an optimization target, taking each fitting path as an optimization variable to construct an optimization problem; adaptively adjusting the condition fitting parameters of each preset fitting path, determining an optimization path based on the linkage condition of the optimization problem, and determining target parameters of the optimization path based on the optimization problem; and generating and executing corresponding control instructions based on the target parameters of the optimization path. The present application scheme ensures accuracy while improving the intelligence of the system when performing electric dust removal efficiency control.

This invention relates to the field of natural language-driven clustering technology, specifically to an e-commerce customer classification method based on end-to-end goal-driven clustering, comprising: S1: acquiring business goals and raw consumption behavior data of all e-commerce customers; S2: standardizing the raw consumption behavior data of all e-commerce customers to generate an e-commerce customer feature matrix; S3: inputting the business goals and the e-commerce customer feature matrix into a large language model, and generating importance scores corresponding to each consumption behavior feature through the independent query mechanism of the large language model for each consumption behavior feature; S4: performing clustering based on proximity and volume clustering algorithms, combined with the importance scores of each consumption behavior feature, to generate cluster labels for each e-commerce customer; S5: distinguishing the importance of e-commerce customers based on their cluster labels and formulating corresponding service strategies. This invention improves the objectivity and goal orientation of e-commerce customer classification.

The present application belongs to the technical field of geological disaster prevention and slope engineering, and particularly relates to a highway slope disaster proneness cross-region evaluation method and system, aiming to realize accurate cross-region evaluation of highway slope disaster proneness. The method obtains quantitative index data of source region landslide and stable slope, calculates a hazard degree coefficient based on an index importance coefficient; determines a screening threshold according to the 5% quantile of the hazard degree coefficient of the landslide sample, eliminates the pseudo-stable slope sample, and constructs a source region data set with balanced positive and negative samples; trains a transfer learning model using the source region data set, the model including source and target feature extractors and a domain discriminator sharing parameters, and reduces the distribution difference between domains through adversarial training; obtains target region to-be-evaluated slope data, calculates the hazard degree coefficient and inputs the trained feature extractor, and determines the proneness grade in combination with the hazard degree coefficient.

The invention discloses a vehicle mobile phone volume change track detection method, device and equipment and a storage medium. According to the method, a Python automation script is used for controlling terminal equipment to execute a sound detection process, a target sound source is automatically triggered, a volume gear is adjusted, a sound scene is switched, and an operation environment is provided for sound data collection; according to an operation environment, a browser sound collection interface is synchronously called to capture physical parameters of loudspeaker sound of terminal equipment in real time, original collection data are obtained, the original collection data are calibrated and filtered, standardized sound data are generated, and the standardized sound data are displayed in real time through a visual interface. And after the detection is completed, the full-amount detection data is automatically packaged and stored according to the preset format, so that the full-automatic operation of the volume change track detection of the vehicle-mounted terminal and the mobile phone can be realized, the detection efficiency is remarkably improved, the subjective error of manual operation is eliminated, the environmental noise interference is effectively overcome, and the objectivity and accuracy of the detection data are ensured.

The invention discloses a pear maturity nondestructive testing method and system based on mixed spectrum multiple tasks, and belongs to the crossing field of nondestructive testing and spectrum analysis technologies. The prediction method comprises the following steps: acquiring spectral reflectivity data of a target pear fruit, and performing three-view preprocessing to generate an original spectrum, a first-order derivative spectrum and a standard normal variable standardized spectrum; inputting the processed spectral data into a pre-trained mainstream pear variety global model, and synchronously outputting predicted values of hardness and soluble solids; and finally, obtaining a corresponding specific judgment threshold according to the variety of the target fruit, and comprehensively judging the maturity by comparing a predicted value with the threshold. According to the method, the advantages of traditional machine learning and deep learning are fused, the mainstream pear variety global model with the cross-variety generalization ability is constructed, the variety specificity threshold value is combined, rapid, lossless and accurate prediction of the maturity of the multi-variety pears is achieved, and the method is suitable for multi-scene application such as orchard harvesting, storage grading and market circulation.

The utility model relates to a kind of injection molded part pin performance detection device, belong to the technical field of injection molded part detection equipment.It is sequentially transported to each detection station by transfer gripper assembly with injection molded part, the end face and side of injection molded part containing pin are sequentially detected in comprehensive manner in conduction, height and location degree, and the two-dimensional code for tracing is marked to qualified product, avoid artificial misjudgment, realize efficient, accurate quality detection and data management.

The invention discloses a simulated annealing standardization correction method and system for density logging data, and belongs to the technical field of logging data processing. Comprising the steps of collecting density logging data of a standard well and original density logging data of a to-be-corrected well, preprocessing the original density logging data of the to-be-corrected well, establishing density data histogram distribution based on a linear mapping model, establishing a histogram overlapping comparison evaluation system, and calculating a comprehensive matching score. Optimizing calculation is conducted on the linear mapping model based on a simulated annealing algorithm, linear transformation parameters are automatically optimized, the optimal parameters are applied to full-well-section density data correction, and comparison between original density data and an anti-normalization processing result is achieved through anti-normalization processing. The method effectively overcomes the defects that a traditional method depends on artificial experience and is low in correction precision, data quality and processing efficiency are remarkably improved, and a reliable data basis is provided for reservoir fine evaluation.