12results about How to "Improve interpretation efficiency" patented technology

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 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.

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 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 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 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.