27results about How to "Describe well" patented technology

A water leakage monitoring method for a digital twinning system of a coal mine shaft comprises the steps that an RFID antenna and a Twinin-Tag sensor are installed on the wall of the shaft, a monitoring terminal is arranged on the ground, and an RFID reader is arranged at an outlet of the shaft; a shaft monitoring signal is collected in real time through a Twindow-Tag sensor, the shaft monitoring signal is read through an RFID reader, and then shaft monitoring data are obtained by analyzing and processing the shaft monitoring signal; collecting RSSI reading and phase data by using a short time window, and performing state identification by using a decision tree; carrying out coarse segmentation and fine segmentation on the leakage signal, and determining the location of a water leakage point in combination with a change point detection algorithm; and the leakage volume and the leakage rate are estimated. According to the method, the water leakage point can be accurately positioned, the volume and flow velocity information of the leaked water in the shaft can be obtained, so that a reliable basis is provided for subsequent maintenance decision making, and the method is suitable for long-term monitoring operation of the coal mine shaft.

The invention relates to the technical field of medical images, in particular to a neural CT map segmentation method based on high-precision registration. The method comprises the following steps: acquiring a nerve CT image; performing coarse registration based on mutual information according to the CT image, and performing multi-scale fusion based on wavelet to obtain a fused image; performing standard map preprocessing on a preset standard nerve CT map database according to the fused image to obtain a preprocessed standard map set; adding a multi-scale feature fusion module to a pre-established basic U-Net architecture, and embedding a space attention module to obtain a to-be-trained U-Net network; and performing deep registration network training on the to-be-trained U-Net network by using the fused image and the preprocessed standard atlas set to obtain a trained U-Net network. According to the invention, through technologies of multi-modal image fusion, deep learning registration and conditional random field optimization, a segmentation effect with higher precision and higher robustness is realized.

This invention discloses a method and storage medium for reconstructing the energy surface of vacancy-helium-hydrogen complexes. The main steps include: S1, calculating the energy of small complex clusters; S2, analyzing the formation energies of vacancy-helium and vacancy-hydrogen complexes with respect to p2 and p3, respectively; S3, selecting a suitable univariate function to fit the relationship between cluster energy and p2 and p3 at a given p1; S4, fitting the relationship between the univariate function parameters and p1; and S5, calculating the energy of arbitrary clusters and defect energy levels. This method reconstructs the energy surface of vacancy-helium-hydrogen complexes based on a class of univariate functions, enabling high-precision reproduction of the energy and energy levels of defect clusters. This reconstruction method not only accurately describes the energy of defect clusters within a known computational set but also provides a good description of the energy and energy level trends of clusters outside the computational set, exhibiting excellent extrapolation properties.

This invention relates to the field of social network analysis technology and proposes a social network sentiment evolution model that integrates user influence and activity. To address the shortcomings of existing technologies, such as inaccurate simulations and inflexible predictions in current network sentiment analysis and sentiment evolution processes, this invention provides a social network sentiment evolution model that integrates user influence and activity. The model analysis method involves: collecting text sentiment data from target users; collecting user influence data from each user; collecting the activity level of the target social network at time t; collecting the forgetting probability of each user at time t as a measure of sentiment evolution capability; establishing a dynamic model for the sentiment evolution of the social network; optimizing the evolution probability of the information propagation model based on text sentiment; and analyzing the evolution process of the dynamic model for the sentiment evolution of the social network based on the optimized information propagation model. This model is suitable for application in social network analysis.

The application discloses a kind of wheat scab monitoring methods based on satellite remote sensing, belong to remote sensing monitoring technical field, first obtain the remote sensing data and meteorological precipitation data of wheat planting area in predicted year and N years before predicted year, the remote sensing data include multispectral data and thermal infrared remote sensing data;Then the relative vigor index is calculated using the multispectral data;Using the multispectral data and thermal infrared remote sensing data obtains normalized surface temperature index;Using the meteorological precipitation data obtains normalized precipitation index;Finally, the relative vigor index, normalized surface temperature index and normalized precipitation index are used to calculate the wheat scab incidence index of predicted year;The application can better reduce the interference caused by the difference of wheat vigor in different regions in large-scale monitoring on scab monitoring model, improve the objectivity and practicability of scab remote sensing monitoring.

The invention relates to a construction and control method of an input-output control system for industry. The construction and control method comprises the steps that an input-output model between the equipment manufacturing industry and the petrochemical industry in a single region is established based on an input-output model; expanding the established input-output model to a multi-region input-output model; establishing a multi-region input-output diffusion model and an input-output control system; designing a pulse controller of the actuator fault; and analyzing the index tolerance of the input-output control system to obtain the gain of the pulse observer and the gain of the pulse controller for the designed pulse observer and the pulse controller to complete the control of the input-output control system. Compared with a continuous time observation and control method, the method provided by the invention can realize the balance between supply and demand of industrial production by regulating and controlling the product demands of the equipment manufacturing industry and the petrochemical industry with lower cost and time consumption.

The present invention claims a method for spatial downscaling of land surface temperature based on the Geographically Weighted Durbin Model (GWDM). Land surface temperature with high temporal and spatial resolution is crucial in the study of environmental ecology and climate systems. However, due to technical limitations, satellite thermal sensors cannot provide thermal infrared images with high temporal resolution and high spatial resolution at the same time. The spatial downscaling method combines low spatial resolution LST and auxiliary data with high spatial resolution from other satellite sensors to improve the temporal and spatial resolution of temperature images under the premise of assuming scale invariance. However, spatial non-stationarity and spatial autocorrelation coexist in most spatial variables, and the spatial characteristics of land surface temperature should be fully considered as spatial variables in the downscaling process. However, previous studies on downscaling of land surface temperature only considered spatial non-stationarity and ignored the spatial autocorrelation between independent variables and dependent variables.

The invention relates to the technical field of block chains, in particular to an export trade account receivable financing digital asset management method capable of increasing credit, and the method comprises the steps: digital asset generation: a financing party stores a hash value of a file generated in export trade on a block chain system, and the corresponding relation is file 1.. n to hash1.. n; and performing digital asset transaction: querying related information of the digital assets by other parties, obtaining the original text of the evidence storage file from other ways, comparing the original text with the hash value of the evidence storage so as to ensure that the information of the file is consistent with the evidence storage and no tampering behavior exists, and purchasing a certain share of digital assets according to prices agreed by the two parties. According to the method, the digital assets with different qualities are flexibly distinguished, the expressive force and the transaction capability of the digital assets are enhanced, and the tampering resistance of the digital assets is improved by combining the certificate of the digital assets with the generation process of the digital assets.

The invention belongs to the field of petroleum and natural gas development, and particularly relates to a fatigue life prediction method based on drill string dynamic stress, and the method comprises the following steps: inputting basic parameters: the basic parameters comprise a well track, a bottom drilling tool combination, a drill string structure and drilling parameters; according to a Lagrange equation, a drill string system dynamic model is established; node velocity, displacement and acceleration are obtained through a drill string system dynamics model, and drill string dynamic equivalent stress is calculated according to the node velocity, displacement and acceleration; counting a stress amplitude and a stress mean value by adopting a rain flow counting method; correcting the stress amplitude and the stress mean value by adopting a goodman formula; substituting into an S-N curve and calculating to obtain the fatigue life. According to the method, the fatigue life of the whole-well drill string can be analyzed, the fatigue service life of the whole-well drill string under the working condition is predicted through data analysis and processing, the presented result is the specific service time of the drill string, and the method has a very strong guiding effect on field engineering practice.

The invention discloses a social network emotion evolution model fusing user influence and activeness, and relates to the technical field of social network analysis. In order to solve the technical defects of inaccurate simulation and inflexible prediction in the existing network sentiment analysis and sentiment evolution analysis process in the prior art, the invention provides a social network sentiment evolution model fusing user influence and activeness. The model analysis method comprises the steps of collecting a text emotion of a target user; collecting the user influence of each user; collecting the activeness of the target social network at the t moment; the forgetting probability of each user at the t moment is collected as the emotional evolution ability; an emotional evolution dynamics model of the social network; optimizing the evolution probability of the information spreading model according to the text emotion; and analyzing the evolution process of the emotional evolution dynamics model of the social network according to the optimized information propagation model. The method is suitable for social network analysis work.

The application discloses a compressed air energy storage power generation system containing dehydration, and relates to the field of compressed air energy storage power generation. The compressed air energy storage power generation system containing dehydration comprises an energy releasing subsystem and a controller. The energy releasing subsystem comprises a dehydration device, a temperature recovery device and an expansion power generation device. The working medium taken from a gas storage device is dehydrated through the dehydration device, then is heated through the temperature recovery device, and finally enters the expansion power generation device to generate power. The dehydration device comprises a first expander and a first separator. The working medium after passing through the first expander comprises liquid working medium and gaseous working medium. The liquid working medium is separated out through the first separator, and the gaseous working medium flows out of the outlet of the first separator and then flows into the temperature recovery device to be heated. The application solves the technical problem that the water content of the working medium in the compressed air energy storage system in the prior art is difficult to control, has the advantage that the working medium gas is always in a gaseous state in the expansion power generation process, and improves the efficiency and safety of the system.

This invention provides a similarity-based method for anomaly detection and diagnosis of multivariate time series, comprising: S1, acquiring the multivariate time series to be tested; S2, obtaining a similarity matrix by combining a basic probability allocation method and the Tanimoto coefficient; S3, reconstructing the similarity matrix using an attention-based reconstruction model; S4, comparing the similarity matrix and the reconstruction matrix to obtain a similarity error matrix, and using the number of abnormal elements in the similarity error matrix as the anomaly score for the corresponding time moment; S5, if the anomaly score reaches a first threshold, the time moment is considered abnormal, and the anomaly attribute is determined based on the distribution of abnormal elements. The similarity matrix calculation method based on basic probability allocation and the Tanimoto coefficient realizes interpretable relationships between attributes of multivariate time series. The attention-based reconstruction model enhances the ability to process long-term, high-dimensional data, better describing long-term temporal dependencies, improving anomaly diagnosis capabilities, and detecting abnormal times and attributes.

This invention discloses a method and system for estimating fuel cell parameters based on adaptive subset simulation. It transforms the updating of the posterior distribution of parameters into a structural reliability problem, constructs a limit state function using measurement data to form an intermediate failure domain, and generates conditional samples using the MCMC method to progressively approximate the target posterior probability distribution, thereby achieving parameter estimation of the fuel cell system. This method does not require a Gaussian prior assumption, can adaptively adjust algorithm parameters to ensure the reliability of the estimation results, and can comprehensively characterize the probability distribution of unknown parameters, achieving accurate estimation of fuel cell system parameters.

The invention discloses a photovoltaic system dynamic state estimation method and a photovoltaic system dynamic state estimation system based on solar irradiance change, which are characterized in that the randomness of solar irradiance is regarded as unknown input of DSE, and the unknown input is merged into an unscented Kalman filtering algorithm in an unbiased minimum variance form to realize state estimation of a photovoltaic system. According to the method, the dynamic state of the photovoltaic system can be timely and accurately estimated, the problem that the estimation precision is influenced by illumination volatility is solved, and the operation state of the power system is better described.

This application discloses a method for determining conversion rate prediction, comprising: acquiring a set of parameters to be optimized, a target CPA, and a sample data set; based on the set of parameters to be optimized and the target CPA, determining the sum of the PCVR of effective clicks for each advertisement according to the total conversions in the first period, the total PCVR in the first period, the total conversions in the second period, the duration in the first period, the campaign cost, and the PCVR before each click calibration; determining the average difference between the sum of the PCVR of effective clicks for each advertisement and the actual total conversions; training the set of parameters to be optimized with the objective of minimizing the average difference to obtain a target parameter set; and determining the calibrated PCVR of the target advertisement based on the target parameter set and the associated data of the target advertisement. This application also discloses an apparatus, device, and medium. This application introduces more data for parameter optimization, thereby improving the accuracy of PCVR.

The application discloses a brain region target point division method for autism neural regulation, which comprises the following steps: acquiring resting-state functional magnetic resonance imaging data of an autism patient, and pre-processing the functional magnetic resonance imaging data; extracting back-lateral prefrontal cortex ba9 and ba46 in the pre-processed data as target brain regions by using a Brodmann template; unfolding the pre-processed image data into a two-dimensional time sequence, and performing sliding window processing on the time sequence to obtain a plurality of sliding window time sequences; calculating a functional connection matrix of voxel points in the target brain region and all voxel points in the whole brain gray matter in each sliding window time sequence; performing dimension reduction processing on all the functional connection matrices based on local similarity to obtain a reduced dimension functional connection matrix; acquiring a reference clustering template of a normal person which has been constructed, performing Kmeans clustering on the functional connection matrix of the autism patient according to the clustering cluster number, and obtaining sub-region division of the target brain region.

The invention discloses a social network user emotion propagation model based on a game theory, and aims to overcome the technical defect that an emotion propagation model cannot accurately describe a real emotion propagation process in the existing emotion analysis and propagation simulation work in the prior art. According to the technical scheme provided by the invention, a model construction method of the social network user emotion propagation model based on the game theory comprises the following steps: performing emotion analysis on a target user node according to a preset emotion analysis method, and extracting an emotion label of the node; constructing an emotional game income matrix according to the emotional label of each node; adjusting the basic propagation probability in the SIR infectious disease model according to the emotional game income matrix; according to the social enhancement effect, the basic immune probability in the SIR infectious disease model is adjusted; and adjusting the structure of the SIR infectious disease model according to a forgetting mechanism to obtain a social network user emotion propagation model. The method is suitable for sentiment analysis and propagation simulation work.

The invention relates to the technical field of computer vision, and discloses an image data enhancement preprocessing system for gesture recognition, which comprises an image acquisition unit, a data enhancement unit, a feature extraction unit and a preprocessing output unit. The image acquisition unit receives multi-source input of visible light, infrared and depth sensors and the like, and performs de-weighting and resolution calibration; the data enhancement unit implements geometric transformation and color adjustment based on gesture features; the feature extraction unit identifies contour edges, textures and joint points; and the preprocessing output unit verifies the data quality and packages and outputs the data in a standardized manner. According to the system, through multi-source data fusion, semantic perception enhancement and multi-dimensional feature extraction, the training data quality of a gesture recognition model is remarkably improved, the problems of data isomerism, feature distortion and the like in a traditional method are solved, and the system has the advantages of being high in processing efficiency and adaptability.

The application discloses a construction method of a rock triaxial rheological damage constitutive model, which is based on the basic principle of thermodynamics and starts from the energy dissipation in the rheological process of rock, and an elastoplastic rheological constitutive model is established by defining the plastic yield surface and plastic potential energy equation in the rheological process of rock, so that the mechanical and deformation behaviors in the rheological process of rock are described, and the rheological mechanical behavior of rock can be better characterized. The coupling between plastic flow and damage is realized by introducing the form of damage variable, which is the basis for in-depth research on the real structure change behavior of rock, and has reference value for accurately evaluating the safety and long-term stability of rock in major projects.

The utility model discloses a negative pressure suction filtration device and a chemical synthesis workstation, and relates to the technical field of chemical synthesis, the chemical synthesis workstation comprises a base, the base is provided with a negative pressure suction filtration device, a moving assembly, a pipetting head, a liquid storage assembly and a reaction zone, the moving assembly is provided with a pipetting assembly, and the movement of the pipetting assembly is controlled by the moving assembly. The pipetting assembly is used for pipetting, negative pressure suction filtration is carried out through the negative pressure suction filtration device after pipetting is finished, the suction filtration device comprises a suction filtration module, the suction filtration module comprises a negative pressure assembly, a receiving plate and a filtration module are arranged in the negative pressure assembly, and the filtration module is located above the receiving plate. According to the technical scheme, the moving assembly can drive the pipetting assembly to move, the working steps of pipetting, mixing, suction filtration and the like are completed in a full-automatic mode, efficiency is greatly improved, and meanwhile manpower is saved.

The embodiment of the application provides a fraud identification method and device based on sensor data, electronic equipment and medium, which are related to the field of information processing. By state anchoring, dynamic sensing processing and filtering processing on key data of the sensor, sub-module time sequence data and parent module time sequence data are obtained, and an LSTM base model of the sub-module and an LSTM base model of the parent module are respectively established. The output data of the LSTM base model of the sub-module and the LSTM base model of the parent module are used to train an integrated learning tree model to obtain a fraud identification integrated learning tree model. The sensor data to be measured is input into the LSTM base model and the fraud identification integrated learning tree model respectively to obtain fraud prediction values, corresponding decisions are executed according to the fraud prediction values, the sensor data is converted, which is more conducive to describing the data of the objective scene, the effect and interpretability of the model are improved, and the model is used to identify the sensor data to determine whether the user has fraudulent behavior.

The application discloses a kind of space three curved steel box girder model construction methods based on BIM technology, comprising: step 1, obtain the two-dimensional drawing data of bridge, generate route space curve;Step 2, according to the ellipse equation in two-dimensional drawing data, generate the corresponding semicircular arc part profile of roof, bottom plate, web plate and rib plate in bridge, and form parameterized profile family with corresponding straight line part profile;Step 3, with the obtained route space curve as reference, generate the corresponding steel box girder frame entity of bridge;Step 4, according to the diaphragm parameter of bridge section in two-dimensional drawing data, generate diaphragm entity;Step 5, with route space curve reference, the generated diaphragm entity is imported into steel box girder frame entity, and the corresponding three curved steel box girder model is output.The application further provides a kind of space three curved steel box girder model construction system.The method of the application can solve the technical problems of three curved steel box girder fine lofting and deepening design.

The invention relates to the technical field of batteries, and provides a battery cell structure, a battery and electric equipment. The battery cell structure comprises a battery cell and at least one thickness compensation piece, the battery cell comprises a first pole piece, a diaphragm and a second pole piece which are sequentially arranged in a stacked mode, the first pole piece, the diaphragm and the second pole piece are wound to form the battery cell, the battery cell is provided with a straight area and corner areas located at the two opposite ends of the straight area, and the winding starting end of the first pole piece is located in the straight area; a preset distance is formed between the thickness compensation part and the corner area, a cavity is formed, the cavity is located in the straight area, the thickness compensation part is arranged at the winding starting end of the battery cell, and the projection of the thickness compensation part and the projection of the cavity at least partially coincide in the thickness direction of the battery cell. The thickness compensation part can be used for compensating the space of the cavity, so that the thickness of the overlapping region of the battery cell in the formation stage is increased, and the thickness difference between the overlapping region and other regions in the formation stage is reduced. The problem of black spot lithium precipitation can be effectively improved, and the battery performance is further improved.

The invention discloses an image generation method and device, electronic equipment and a computer readable medium, and the method comprises the steps: firstly obtaining at least two to-be-used images, so as to enable different to-be-used images to be used for describing the states of a target object at different visual angles, therefore, the at least two to-be-used images can represent the states of the target object under the at least two view angles; constructing a position mapping relation so that the position mapping relation is used for describing a corresponding relation between pixel positions in the at least two to-be-used images and pixel positions in the fisheye image; and finally, according to the position mapping relationship and the pixel values in the at least two to-be-used images, generating the fisheye image, so that the fisheye image can describe the states of the target object under the at least two view angles, thereby enabling the fisheye image to better describe the target object, and being beneficial to improving the obtaining effect of the fisheye image.

This invention discloses a method for multi-target search and pursuit in an unmanned swarm under high sea state conditions. Unmanned aerial vehicles (UAVs) act as the swarm's eyes, responsible for target search; unmanned surface vessels (USVs) act as the swarm's brain, responsible for swarm control, data processing, and target allocation; and pursuit USVs perform target pursuit tasks. Through the collaboration of different UAVs, the swarm's search and pursuit tasks are completed. Furthermore, based on the swarm's collaborative task execution, this invention considers the issue of maneuver decision-making in high sea state environments. On the one hand, it enables precise target location by UAVs when traditional communication technologies are limited and positioning technologies are interfered with in high sea state environments; on the other hand, it enhances information interaction among UAVs within the swarm, maximizing overall efficiency while ensuring each UAV completes its pursuit task.

The application belongs to the technical field of medicine, and discloses a stable pharmaceutical composition. The pharmaceutical composition with active ingredients of edaravone and dextrocamphor can unexpectedly control the content of specific impurities SCR-756 and impurities SCR-757, and solves the problems of difficult control of impurities and product quality, short storage period and the like from the source.

Provided are a method and system for determining a population pharmacokinetic model of propofol and a derivative thereof. The method comprises determining a population pharmacokinetic model of a compound of formula (I) or propofol, wherein an equation of pharmacokinetic parameters in the population pharmacokinetic model of the compound of formula (1) comprises: CLi=exp4.20+0.349⋅logWT / 63.9−0.749⋅logTP / 72.4+0.238⋅SITE+ηCL,i; an equation of pharmacokinetic parameters in the population pharmacokinetic model of propofol comprises: CLi=exp4.56+ηCL,i.