7results about How to "Reliable basis" patented technology

The application belongs to the technical field of fault identification, and discloses an equipment processing device fault identification method and system based on artificial intelligence. The method comprises the following steps: in a cloud data center, using an artificial intelligence algorithm, an equipment processing device fault identification engine is constructed, and a multi-modal data acquisition device is connected through an edge computing gateway; using the multi-modal data acquisition device, real-time monitoring multi-modal data of the equipment processing device is acquired, and is uploaded to the cloud data center through the edge computing gateway; in the cloud data center, according to the real-time monitoring multi-modal data, using the equipment processing device fault identification engine, fault identification is carried out, and real-time fault identification results and real-time fault maintenance strategies are obtained. The application solves the problems of single data dimension, limited model depth and precision, and lack of response mechanism in the prior art.

The application relates to a tumor intraoperative evaluation method and system based on multi-wavelength photoacoustic mathematical statistics analysis, wherein the method comprises the following steps: irradiating a tumor tissue with a pulsed laser during operation, collecting photoacoustic signals at different wavelengths in time sequence according to a preset wavelength sequence, performing mathematical statistics spectrum analysis after pretreatment to obtain multi-wavelength statistical parameters reflecting the characteristics of the photoacoustic signals; performing parameter mapping on the multi-wavelength statistical parameters to obtain a parameter imaging graph reflecting the scattering characteristics and microstructure differences of the tissue, obtaining a parameter spectrum curve based on the parameter imaging graphs at different wavelengths, and extracting auxiliary features based on the parameter imaging graphs; performing visual analysis based on the parameter imaging graphs and the parameter spectrum curve, spatially positioning a lesion area, selecting a ROI and visually displaying the lesion area; and taking the multi-wavelength statistical parameters and the auxiliary features as inputs of a tumor benignity and malignancy evaluation model to output a tumor classification result. Compared with the prior art, the application has the advantages of being capable of realizing rapid and accurate intraoperative evaluation.

This invention relates to the field of organoids, and discloses a method for detecting the drug sensitivity of primary tumor organoids. The method includes: obtaining the major diameter L0 of each organ type in well D0. n Area S0 n Observation of transmittance T0 n Surface smoothness R0 n Morphological integrity C0 n Obtain the major diameter L4 of each organ in well D4. n Area S4 n Observation of transmittance T4 n Surface smoothness R4 n Morphological integrity C4 n And the average fluorescence intensity Fg within the area of ​​organoids determined by live and dead fluorescence staining. n and Fr n The normalized score change values ​​of the organoids corresponding to each well in D0 and D4 are calculated according to the formula. This invention overcomes the problems of limited dimensions and low confidence in previous organoid drug sensitivity interpretation methods. By combining light microscopy information with fluorescence information, it comprehensively provides important information such as the growth status and viability of each organoid in the field of view, which is a reliable new method for detecting organoid drug sensitivity.

The invention relates to the technical field of intelligent decision making, and discloses an aggregation question answering method, system and device based on embedded semantic indexing and hierarchical aggregation reasoning and a medium, comprising: performing automatic desensitization processing on an original dialogue log, the original dialogue log at least comprising a detachable semantic block; performing multi-layer semantic vectorization conversion on the desensitized semantic blocks; integrating the semantic vector and a question and answer engine, and performing semantic aggregation reasoning based on the semantic vector of the set level according to the question and answer engine to generate a semantic aggregation reasoning result; on the basis of the aggregation reasoning result of the question and answer engine, performing group difference analysis on the semantic vector to obtain an initial group difference analysis result; the method can be applied to development of business systems such as financial science and technology, medical health, old-age care and the like, general viewpoints are extracted from massive dialogues through semantic aggregation reasoning of a set level, and the problem that single analysis is scattered and has no global cognition is solved.

The invention discloses a GIS-based photovoltaic power station intelligent arrangement design method and system, and relates to the technical field of photovoltaic power station design. The method comprises the following steps of mountain terrain initial modeling, mountain terrain shadow photovoltaic arrangement optimization and photovoltaic arrangement design scheme recommendation output. Geographic information data of a to-be-arranged mountain area is acquired based on a GIS to perform terrain modeling, and the to-be-arranged mountain area is divided to obtain photovoltaic design areas so as to preliminarily generate a photovoltaic arrangement design scheme. Then, surface shielding shadow continuity analysis is carried out on each photovoltaic design area in a shadow analysis period to determine adopted photovoltaic power station arrangement design optimization, and finally, the photovoltaic power station arrangement design schemes and the scheme recommendation priorities are synchronously output to a manual terminal, so that the generation efficiency of the photovoltaic power station arrangement design schemes is improved. The problems that in the prior art, due to mountain terrain shadow overlapping, photovoltaic power station arrangement is inaccurate, and the power generation efficiency is reduced are solved.

The invention discloses an annular blowout preventer rubber core failure prediction method and system based on a neural network, and relates to the field of oil and gas exploitation equipment monitoring, and the method comprises the following steps: obtaining multi-dimensional working data of an annular blowout preventer rubber core, comprising a use time sequence, a displacement sequence, a hydraulic pressure sequence and a corresponding failure degree label sequence; performing dynamic space-time normalization processing to generate a normalized sample set fused with time relevance; performing supervised heterogeneous neural network model training; and inputting the working data of the rubber core of the annular blowout preventer to be detected into the optimized supervised heterogeneous neural network model, outputting a corresponding failure probability sequence and triggering an early warning mechanism. According to the method, by integrating multi-dimensional data and carrying out dynamic space-time normalization processing and multi-modal heterogeneous neural network modeling, the failure prediction precision and real-time performance are remarkably improved, and full-period management of the rubber core of the annular blowout preventer is achieved in combination with a grading early warning mechanism and threshold value self-adaptive updating.

This invention relates to the field of unmanned aerial vehicle (UAV) simulation technology and discloses a method for simulating UAV flight status based on digital twins. The method involves constructing a digital twin system containing a physical UAV entity and a virtual simulation model, and collecting multi-source flight data streams, including the physical UAV's position information, motion parameters, and environmental perception data. Multi-dimensional feature fusion processing is performed on the multi-source data to generate a fused feature representation. Based on this fused feature, a probabilistic state modeling algorithm is used to determine the estimated flight status and related confidence information. The virtual simulation model is updated based on the estimated values ​​and confidence levels to simulate real-time flight status. Flight status clustering analysis is performed in the virtual model to detect abnormal patterns, and an adaptive simulation threshold set is generated based on historical flight data. By comparing the abnormal patterns with the adaptive threshold set, simulation control commands are output for UAV operation. This method can effectively support accurate simulation and anomaly control of UAV flight status.