8results 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 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.

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.