25results about How to "Improve interpretation efficiency" patented technology

The invention relates to the technical field of financial science and technology, and provides a document interpretation method and device, electronic equipment and a computer readable storage medium. Analyzing and processing the system document to obtain system attribute information; matching the system attribute information with a preset service category knowledge base, and determining a system type; extracting historical system information from the business category knowledge base according to the system type; generating an initial interpretation query according to the system document, and performing enhancement processing on the initial interpretation query according to the historical system information to obtain an enhanced query prompt; and inputting the enhanced query prompt into a preset large language model for analysis and processing to obtain system interpretation information. By means of the technical scheme, intelligent document interpretation can be achieved, the document interpretation efficiency is improved, and therefore development of banking business is better facilitated.

The invention provides a remote sensing monitoring multi-scale space grid index construction method and device, and belongs to the technical field of remote sensing monitoring, and the method comprises the steps: dividing uniform basic grids based on the geographic boundary of a monitoring region; calculating a service importance score fusing the supervision priority, the geographic complexity and the historical change frequency for each basic grid; according to the score, a preset threshold value and a dynamic decision, refinement, maintenance or aggregation operation is executed on the basic grid, and a service-adaptive multi-scale grid structure is formed; unified codes based on a Z-order curve are generated for all the grids; establishing association mapping between the water conservancy business object and the grid and determining a main grid; and finally outputting a spatial grid index fusing geometry, coding, hierarchy, attribute and association relationship. According to the method, the AI interpretation efficiency of the mass remote sensing data can be remarkably improved, the allocation of computing resources is optimized, and the accuracy of monitoring and early warning is improved through deep fusion with business rules such as river and lake supervision.

The invention discloses a priori knowledge embedded seismic wave data automatic interpretation method, and relates to the technical field of geological survey. According to the method, value range calibration of classification labels to which feature data belongs is completed in a normal distribution mathematical statistics mode, and fusion of a data decision-making layer is realized by using a D-S theory, so that secondary classification interpretation of seismic wave data on the basis of clustering is automatically realized by taking a KNN algorithm and the D-S evidence theory as cores; by taking a data analysis result of excavated scale data as a reference and combining with calculation of a clustering center distance, embedding of important priori knowledge of real rock mass quality is realized, so that mapping from a clustering label to a rock mass quality label is completed, and rationality and reliability of label classification are fully ensured; according to the method, the interpretation efficiency of the seismic wave data is remarkably improved, the time and the labor cost are greatly saved, the accuracy and the reliability of an interpretation result are ensured, and the method is suitable for large-scale application to interpretation of the seismic wave data in geological exploration.

The invention relates to the technical field of fluvial sediment digitization, in particular to an ISfM-PMVS fluvial sediment digitization modeling method based on images collected by a smartphone, high-resolution multi-view images can be obtained in a short time through an ISfM method in combination with the smartphone, and the method is suitable for quickly constructing a three-dimensional digital model. By combining SfM and PMVS technologies, a high-density three-dimensional point cloud and a digital orthoimage (DOM) can be generated, so that data not only contain geometric information, but also contain rich color and texture information; three-dimensional model parameters are optimized through RANSAC and bundle adjustment (BA), and the accuracy of sparse point clouds is ensured. The portable characteristic of the smart phone allows efficient data acquisition in complex terrains and harsh environments, and the generated data model can accurately reflect the actual conditions of geological points.

The invention provides a deep learning identification method and device for a dry layer and an effective reservoir based on four parameters, and the method comprises the steps: finding out one or more representative wells from a research region, and carrying out the interpretation of a layer section of a research target layer; digitalizing the lithology interpretation result of the target stratum; analyzing the logging data of the well in the research area, and normalizing the logging data of the representative well; constructing a deep learning network structure with an input layer with input neurons and bias neurons, a hidden layer and a neuron output layer by using a TensorFlow framework; setting a learning rate of a deep learning network gradient descent algorithm; setting a cost function of the deep learning network as a square error cost function; setting training times, and training the deep learning network on the basis of the training sample to obtain deep learning network parameters; and testing the training sample and the test sample by using the obtained deep learning network parameters. According to the method, the dry reservoir and the effective reservoir can be effectively distinguished from the complex and diversified reservoirs.

The present invention relates to the field of artificial intelligence, and discloses a data interpretation method, device, equipment and storage medium based on image recognition, which is used to solve the problem of low efficiency in interpreting physical examination reports with different layout contents in the prior art. The method includes: receiving and extracting a physical examination report image in a data interpretation request; identifying the text position of the physical examination result therein, and cropping it to obtain a cropped image set; performing text recognition on the cropped image block in the cropped image set to obtain the text content; and determining the inspection category and inspection result contained in the cropped image block, and obtaining the corresponding standard indicator range; judging whether the inspection result is within the standard indicator range; if not, marking the inspection result and inspection category as abnormal inspection result and abnormal inspection category; retrieving medical information in a medical knowledge graph, and outputting the data interpretation result. In addition, the present invention also relates to blockchain technology, and relevant information of the physical examination report can be stored in the blockchain.

A ship navigation system, in particular a ship navigation system for a ship, comprising: a positioning unit configured to detect a position of the ship; a nautical chart database; a display configured to present nautical chart information and a view of a position of the vessel on the nautical chart; a short range sensor module disposed on the vessel, the short range sensor module configured to provide scan data of the surroundings of the vessel; a control unit operably connected with the short range sensor module, the positioning unit, the nautical chart database and the display, the control unit configured to process the scan data to provide a scan view of the ambient environment, the control unit is configured to present the nautical chart and an enhanced view of the scan data on the display, and is configured to indicate a portion of the scan data that does not match the nautical chart information in the enhanced view.

The invention relates to a complex working condition engine state infrared image interpretation method, and relates to the field of engine test.The method comprises the steps that projection positions and envelope shapes of engine tail flames are obtained through calculation, and target frames are set to select the tail flames of all engines based on projection position information and envelope shape information; a background frame is selected according to the relation between centroid positions of all engine tail flame envelope shapes; calculating an average value, a median and a standard deviation of all pixel gray values in the target frame, calculating average values of all pixel gray values in the background frame and the whole image, and selecting a minimum value in the average values of all pixel gray values in all the target frames; selecting the average value of the gray values of all the pixels in all the background frames and the maximum value of the average values of the gray values of all the pixels in the whole image, and calculating the difference value between the minimum value and the maximum value; by comparing the difference value with the set threshold value, the on-off state of the engine can be judged. The method has the advantage of automatically judging the on-off state of the engine.

The invention discloses blood cell analysis equipment and a blood cell analysis method. The equipment comprises a sample injection module, a sample adding module, a detection module, a processor and a display, the sample introduction module is used for acquiring a blood sample; the sample adding module is connected with the sample introduction module and is used for mixing a reagent with a blood sample to obtain a to-be-detected sample solution; the detection module is connected with the sample adding module and is used for detecting the to-be-detected sample liquid to obtain detection data; the processor is connected with the detection module and is used for receiving the detection data and predicting a prediction score of the detection data; the display is connected with the processor and used for displaying an analysis interface which is at least used for displaying the predicted score. Therefore, the predicted score can be directly displayed on the analysis interface of the display, so that medical staff can intuitively obtain the predicted score of the disease risk predicted according to the detection data, the information interpretation efficiency of a user is improved, and the use experience of the user is improved.

The invention discloses a method and device for automatically identifying a stratum unconformity surface from seismic data, and the method comprises the steps: carrying out the seismic stratigraphic body analysis of the seismic data of a research region, and determining a first-year stratigraphic body; performing spatial interpolation processing on the first-year stratigraphic body to obtain a second-year stratigraphic body; respectively determining a relative stratum thickness body, a relative stratum amplitude difference body and a relative stratum dip angle body according to the second-year stratum body; determining a stratum unconformity characteristic body according to the relative stratum thickness body, the relative stratum amplitude difference body and the relative stratum dip angle body; and determining a stratum unconformity surface according to the stratum unconformity characteristic body.

The present invention discloses a monitoring device, a medical central station system and a monitoring data review method. The monitoring device includes a sensor, a display and a processor. The sensor is used to collect monitoring data of the patient. The display is used to display a monitoring interface. The processor is used to obtain monitoring data; according to the monitoring data, a real-time monitoring image and a monitoring evaluation image are displayed on the monitoring interface, and the monitoring evaluation image is used to present parameter trend curves and virtual human models of multiple parameters, and optionally also used to present preset evaluation parameter values ​​of multiple parameters; the virtual human model is used to graphically display the monitoring part; in response to the review operation for any target monitoring point on the parameter trend curve, the target parameter value corresponding to the target monitoring point is determined; according to the target parameter value, the virtual human model and the optional preset evaluation parameter value are updated and displayed, the browsing operation is simple, the monitoring part can be observed at a fixed point, and the efficiency of medical staff in interpreting relevant monitoring data is improved.

The invention discloses a seismic structure tensor feature vector determination method and device and a stratigraphic dip angle estimation method and device. The seismic structure tensor feature vector determination method comprises the steps of preprocessing target seismic data; inputting the preprocessed target seismic data into a pre-trained feature vector calculation model; outputting a feature vector of the target seismic data through a feature vector calculation model; the feature vector calculation model is obtained by training in the following mode: pre-training a deep neural network model; seismic data obtained from actual data are used as training sample data, the training sample data are input into a deep neural network model obtained through pre-training, parameters of the deep neural network model obtained through pre-training are adjusted in an unsupervised training mode, and a feature vector calculation model is obtained. According to the method, the feature vectors can be quickly and efficiently calculated, the stratigraphic dip angle attributes can be calculated, and the interpretation efficiency of seismic data is integrally improved.

The invention discloses a single crystal blade orientation detection method and system based on LIBS characteristic spectral response, and the method comprises the steps: building a standard characteristic spectral data set matched with orientation difference through EBSD gold standard, aligning a to-be-detected blade with coordinates of a three-dimensional digital twin model, and planning a gridding scanning path; the method comprises the following steps: collecting original spectrums and space coordinates of all detection units through LIBS in-situ scanning, preprocessing the spectrums, calculating the actual area of each spectrum interval based on the linear positive correlation between the spectrum intensity and the grain boundary area, mapping the result to a digital twinborn model to complete three-color visual calibration, and finally calculating the overall anomaly rate to judge the qualification of the blade. According to the invention, in-situ nondestructive and full-surface accurate quantitative detection of the single crystal blade is realized, the detection result is visualized in real time, the judgment logic is scientific, a modular automatic detection system is constructed, the system is adaptive to industrial batch online detection of aviation single crystal blades, and the problems of low detection efficiency, non-visualized result and difficulty in industrial application in the prior art are solved.

The application belongs to the technical field of seismic signal processing and interpretation, and specifically discloses a special geological body identification method based on RPCA background modeling, which comprises the following steps: S1, a special geological body identification model is constructed based on an RPCA algorithm, and seismic data matrix is decomposed into a sparse sharp noise matrix and a low-rank structure information matrix; S2, the low-rank structure information matrix is calculated through an SVD decomposition algorithm, the sparse sharp noise matrix is calculated through a soft threshold algorithm, and the low-rank structure information matrix and the sparse sharp noise matrix are updated through iterative residuals until the residuals of the seismic data two-dimensional matrix, the sparse sharp noise matrix and the low-rank structure information matrix meet the set conditions; S3, the sparse sharp noise matrix is output, which is special geological body data, and the low-rank structure information matrix is output, which is a remaining stratum background. The application can identify special geological bodies, and improves the interpretation efficiency, accuracy and applicability of special geological bodies. The application is suitable for the identification of special geological bodies.

The invention belongs to the technical field of intelligent processing and application of remote sensing images, and discloses a large-size image target linkage strict judgment system and method based on identity responsibilities, and an identity responsibility matrix engine module realizes efficient allocation of resources and tasks in the system, and further combines with data analysis, so as to realize the target linkage strict judgment. Accurate user capability evaluation and dynamic identity responsibility adjustment are provided; the intelligent linkage task scheduling center module realizes intelligent matching based on identity responsibility and multi-mode intelligent linkage task distribution; the multi-user linkage real-time interpretation module realizes large-size image display, multi-user linkage target interpretation and real-time synchronization of target interpretation results; the intelligent interpretation auxiliary module utilizes a target historical library, a target knowledge library, a target situation library, an image searching engine and similar target extraction to assist in completing target interpretation. According to the method, the performance of a large-size image target interpretation system is remarkably improved, the accuracy and practicability of remote sensing image analysis are improved, and application of the remote sensing technology in more actual scenes is promoted.

This application discloses a method and apparatus for thyroid cancer analysis based on real-time quantitative PCR. The method includes: acquiring data to be analyzed; determining sample-specific threshold line data based on the data to be analyzed; calculating a corrected Ct value based on dual-inflection-point kinetics based on the sample-specific threshold line data to obtain the final corrected Ct value; and generating a detection result based on the final corrected Ct value. This application significantly improves the linearity of the fluorescence amplification curve, reduces the interference of background noise on the results, and improves the stability of Ct value calculation through optimized curve fitting algorithm processing.

The invention provides a heart rate data drawing method and device and intelligent wearable equipment applying the same, and the method can respond to a first query task, call first heart rate data specified by the first query task, divide the first heart rate data into a plurality of sub-data corresponding to different time periods, and display the sub-data in the first query task. And determining each sub-data as valid data or invalid data based on a preset rule, so as to generate a first heart rate data graph based on each valid data, each invalid data and a time period corresponding to each sub-data. According to the scheme provided by the invention, the heart rate data is divided into a plurality of sub-data and validity judgment is carried out, so that invalid data in the heart rate data can be effectively searched, and graphical display is carried out based on the valid data and the invalid data, so that the trend and characteristics of the heart rate changing along with time can be intuitively reflected; and the user can conveniently and quickly understand the heart rate condition of himself.

The invention belongs to the technical field of power equipment state monitoring and artificial intelligence, and particularly relates to a transformer fault diagnosis method and device based on an interpretable technology, equipment and a medium. According to the dynamic integral gradient algorithm provided by the invention, the baseline for removing the key features is dynamically generated for each sample, and the gradient weight is dynamically adjusted, so that an explanation result with relatively high fidelity can be obtained under the condition of relatively low gradient calculation times. Therefore, a visual fault diagnosis basis is provided for operation and maintenance personnel, the opaque problem caused by the black box model can be relieved, the interpretation efficiency is improved, and the real-time requirement of an online monitoring system is better met. And a cascade architecture combining lightweight shunting with expert diagnosis is designed. The first-level expert model quickly processes a large number of normal samples and performs preliminary classification at a low calculation cost, and the second-level expert model focuses on fine diagnosis of a specific frequency band, thereby being beneficial to realizing high-precision and low-delay balance and adapting to edge deployment.

The application discloses a kind of on-load tap-changer internal fault diagnosis method, system, equipment and medium, it is related to power system operation monitoring and state diagnosis technical field, comprising: obtaining the insulating oil sample of on-load tap-changer;Detect the volume concentration of acetylene, ethylene and methane in insulating oil sample and obtain the volume percentage value of each characteristic gas;Establish rectangular coordinate system;Determine fault diagnosis space;In fault diagnosis space, multiple mutually non-overlapping fault sub-regions are divided out, to determine the volume percentage value of characteristic gas horizontal, longitudinal coordinate, determine target coordinate point in fault diagnosis space;According to the fault sub-region where target coordinate point is located, output the internal fault type of on-load tap-changer.The application retains the fault criterion of international standard, and the diagnosis result is consistent with traditional method, solves the problems of low interpretation accuracy, variable redundancy, machine implementation complexity and other problems existing in prior art, improves the intuitiveness, accuracy and real-time performance of on-load tap-changer fault diagnosis.

The invention belongs to the technical field of ancient building hidden danger detection, and discloses a deep learning-based interpretation method for an ancient building internal hidden danger multi-source detection result, and the method comprises the following steps: collecting multi-source detection data and a detection interpretation result, and carrying out the data preprocessing; constructing a deep learning model based on the preprocessed multi-source detection data and the detection interpretation result; based on a deep learning model, carrying out hidden danger automatic identification and interpretation to obtain a multi-dimensional interpretation result; and carrying out multi-dimensional visual analysis and decision support according to a multi-dimensional interpretation result. According to the interpretation method for the multi-source detection result of the hidden dangers in the ancient building based on deep learning, automatic and accurate recognition and interpretation of the hidden dangers in the ancient building are realized, the limitation of traditional manual analysis is overcome, the positions, sizes, types and distribution characteristics of the hidden dangers are rapidly and comprehensively interpreted, and the interpretation accuracy of the multi-source detection result of the hidden dangers in the ancient building is improved. And a basis is provided for protection and maintenance of the ancient wall building.

The invention discloses a deployment method and device of a multi-modal remote sensing image interpretation model, a medium and equipment, and relates to the technical field of deep learning. The method comprises the following steps: acquiring a reference multi-modal remote sensing image interpretation model; the reference multi-modal remote sensing image interpretation model comprises a feature extraction model and a feature interpretation model; matrix multiplication in the feature extraction model is replaced with block assembly line matrix multiplication, and an optimized feature extraction model is obtained; the block assembly line matrix multiplication comprises the steps of respectively partitioning two matrixes to be multiplied, and sequentially processing different block multiplications according to a block assembly line mode; and deploying the optimized feature extraction model on a field programmable gate array (FPGA) in a heterogeneous computing platform of the unmanned aerial vehicle, performing model quantization processing on the feature interpretation model, and deploying the quantized feature interpretation model on a graphics processing unit (GPU) in the heterogeneous computing platform of the unmanned aerial vehicle. The multi-modal remote sensing data interpretation model deployed through the deployment method is high in interpretation efficiency.

The invention provides an artificial intelligence interpretation method for multi-arm hole diameter logging data. The artificial intelligence interpretation method for the multi-arm hole diameter logging data comprises the steps that 1, imaging processing is conducted on logging interpretation data; 2, building a working condition interpretation model based on the convolutional neural network; step 3, training the built working condition interpretation model; 4, the well trained working condition interpretation model is utilized, and according to the collected actual multi-arm hole diameter logging data, the multi-arm hole diameter logging working condition is judged. According to the artificial intelligence interpretation method for the multi-arm hole diameter logging data, by combining the high-precision data acquisition capability of multi-arm hole diameter logging and the efficient intelligent analysis advantage of artificial intelligence, the interpretation efficiency and interpretation precision of multi-arm hole diameter logging interpretation work are effectively improved, and the labor intensity of workers is reduced.

The invention discloses a medical quality control index interpretation method and system, a medium and a program product, and the method comprises the steps: constructing a hierarchical index dictionary; establishing an index analysis rule base based on the hierarchical index dictionary; a preset index name standardization algorithm is used, the hierarchical index dictionary and the index analysis rule base are utilized to convert the index names into a preset standardization format, and a plurality of standardized index names are obtained; establishing an index semantic mapping matrix, and respectively matching core words, modifiers and qualifiers in the plurality of standardized index names with preset index connotation elements to obtain a hierarchical semantic mapping result; establishing a hierarchical index interpretation template library; and selecting and combining the initial template elements in the hierarchical index interpretation template library according to a hierarchical semantic mapping result to generate an interpretation text. According to the method and the device, possible differences of index definition interpretation between different medical institutions and regions are reduced, and the index interpretation consistency between the medical institutions and regions is improved.

The invention discloses a multispectral remote sensing image real-time processing method. The method comprises a data acquisition node (S1), an image splicing node (S2) and a parameter inversion node (S3). The method is characterized in that multispectral images can be read and processed in real time, and a corresponding parameter distribution diagram is generated. Wherein the data acquisition node (S1) can read multispectral data from a multispectral sensor in real time and perform preprocessing such as geometric correction, radiometric calibration, image registration and image synthesis on the multispectral data; the image splicing node (S2) can generate an orthoimage in real time; and the parameter inversion node (S3) can draw a parameter distribution diagram according to the embedded parameter inversion model. According to the multispectral remote sensing data real-time processing framework, the interpretation difficulty of the multispectral remote sensing data is reduced, and the processing efficiency of the multispectral remote sensing data is improved.

The present invention discloses a method for establishing a reference threshold for metagenomic pathogen detection. The method includes: determining the type of clinical sample; determining its composition and the distribution range of human cell content; setting a gradient negative control; performing multiple batches of repeated tests on the negative control sample according to the metagenomic detection process that the clinical sample to be tested is about to undergo; counting the number of detection sequences of different pathogens in the negative control samples with different human cell concentrations, and obtaining the fluctuation range of the number of detection sequences of the corresponding pathogens in the negative control samples with different human cell concentrations; taking 120% of the upper limit of the fluctuation range of the number of detection sequences of the corresponding pathogens in the negative control samples as the threshold. The present invention can achieve hierarchical discrimination of sample detection results, improve the accuracy of metagenomic pathogen detection results; improve the efficiency of report interpretation; effectively reduce the false positives of metagenomic detection results; and evaluate the contamination in the detection process in real time, guiding laboratory process improvement.