35 results about "Data averaging" patented technology

Embodiments of the present application disclose a resource selection method, device, equipment and storage medium. The method is applied to a V2X terminal, and comprises: receiving data to be processed issued by an upper layer application; if a current time meets a search condition, determining whether the data to be processed in a search period before the current time meets a Poisson distribution; if the data meets the Poisson distribution, taking a data average receiving time corresponding to the Poisson distribution as a resource selection period, and performing periodic resource selection. The technical scheme of the embodiments of the present application can effectively select periodic resources, reduce the selection frequency of one-time resources, and improve the utilization efficiency of resources in the case that the time interval of data packets of the upper layer application is constantly changed.

The application relates to the technical field of data processing, and discloses an excel data batch processing method and related equipment.The method comprises the following steps: obtaining excel batch data to be processed, analyzing the excel batch data to obtain excel analysis data, and performing data volume statistics on the excel analysis data to obtain an excel data volume; a plurality of threads are created, and a queue corresponding to each thread is created according to the thread; the excel analysis data is equally divided according to the excel data volume to obtain a plurality of excel sub-analysis data, and the excel sub-analysis data is evenly distributed to the normal queue for processing; and the method can improve the document processing efficiency.

The invention relates to a city development talent demand prediction method and device, and a storage medium. The method comprises the following steps: selecting city research time nodes, input elements and output elements; collecting corresponding input element data and output element data of the city at the research time node; based on the input element data and the output element data, adopting a Cobb-Douglas production function to determine the output elasticity of each input element of the city; determining marginal output data and average output data of each input element according to the output elasticity; drawing a total output curve, an element marginal output curve and an average output curve of the city according to the total output data, the marginal output data and the average output data of each research time node of the city; according to the curve position relation, the urban talent development stage is determined, and a prediction result of the talent demand is generated. According to the method, the effects of capital, labor force and technical progress factors in the production process are described from the macroscopic perspective, and the influence of the talent number and quality on urban development is quantified.

The invention relates to the technical field of flood prevention and drainage, and discloses a printing and dyeing drainage state analysis method and system based on sensing data, and the method comprises the steps: obtaining drainage data and generating a curve through deploying sensors which are distributed at equal intervals in groups in a printing and dyeing drainage pipeline; matching the upstream curve by taking the middle / downstream data as a template, and calculating a time difference discrete value to identify sensing abnormality; and according to the upstream data average value, matching an execution instruction, performing hierarchical control on single drainage treatment equipment, multiple drainage treatment equipment in turn or all drainage treatment equipment is started, and performing corresponding pop-up window prompting, early warning or alarming. Meanwhile, environmental interference is corrected through multi-sensor data fusion, database parameters are dynamically optimized to adapt to the production cycle, pipeline undercurrent is recognized in combination with detection particles, and equipment parameters are monitored to early warn faults. According to the method, the printing and dyeing drainage monitoring accuracy and the equipment scheduling intelligence are improved, and the abnormity early warning capability is enhanced.

The application belongs to the technical field of transportation, and particularly relates to a traffic prediction method based on multi-graph gated convolution and Conv-LSTM. The DTWN similarity value filling module is used to calculate the similarity between time series, and the average value of K data with high similarity is taken to fill in the missing data, so as to ensure the integrity of the traffic data. The traffic data is decomposed into approximate coefficients and detail coefficients through DWT. The approximate coefficients reflect the long-term trend of traffic flow, and the detail coefficients contain short-term fluctuation information. Different models are combined to process the data obtained through DWT. The detail coefficients are processed through the multi-graph gated dilated convolution MGDCN to capture the short-term fluctuation, and the approximate coefficients are processed through the Conv-LSTM to capture the long-term trend. Compared with the existing traffic prediction model, the application can fully fill in the missing data, capture the short-term fluctuation and long-term trend of traffic, effectively reduce the error in traffic prediction, and improve the accuracy of traffic prediction.

This invention provides an airflow measurement and correction system for non-uniform wind field ducts, comprising an airflow measurement system based on big data analysis and an airflow measurement system based on the average wind speed value of the data points, with airflow meters set at these locations. By setting up the airflow measurement system based on big data analysis and the airflow measurement system based on the average wind speed value of the data points in different cross-sections of the non-uniform wind field duct, the airflow velocity values ​​Fdps and Fpps are measured simultaneously. If the difference between Fdps and Fpps is large, the airflow measurement value is taken as Fdps, or the location of the airflow meter at the average wind speed value point is manually or automatically readjusted. The two systems complement each other and verify each other, accurately and reliably solving the problem of inaccurate and unreliable measurement of duct airflow by the geometric mean wind speed value in existing airflow measurement devices.

The invention belongs to the field of GPU multi-card interconnection communication, and relates to a full-exchange GPU communication method and system. According to the method, the data stored in each GPU is averagely divided into N blocks, and each block of data corresponds to a specific data block needing to be sent to the target GPU; constructing a data symmetric matrix, and determining a total communication round according to the total number N of the GPUs; in each round of communication, two-way data transmission is carried out between the two GPUs based on a pairing rule of a symmetric matrix; and through multi-round iteration, complete exchange transmission of all data blocks is completed, so that each GPU obtains a complete data set from all GPUs. According to the method, a connection topology scheme of the GPUs does not need to be changed at all, the symmetric matrix of the GPUs only needs to be generated according to the number of the GPUs, and the condition that the GPUs communicate with other GPUs at the same time is reduced under the condition that the data transmission quantity is not increased, so that the congestion possibility of the GPUs is reduced, and the communication performance is improved.

The application discloses a kind of task data processing method and system, first result data and its type are obtained after upstream node processing task data ends, center node sets corresponding type label for downstream node after obtaining first result data and its type, and the type label of downstream node is synchronized to upstream node, so upstream node can send specific type first result data to corresponding downstream node. Meanwhile, upstream node is sequentially sent first result data to downstream node, so downstream node can only process specific type data related to task. Compared with the method that upstream node needs to divide data to downstream node in prior art, in the present application, data is not needed to be evenly divided to each downstream node for processing each time, thereby reducing the number of network interactions and network IO occupation of upstream and downstream, and also reducing the amount of data received by center node from downstream node. In this way, the probability of network failure during task processing is reduced.

The invention relates to the technical field of solder paste management, and provides a solder paste multi-dimensional data fusion management method and system, and the method comprises the steps: creating a quality label corresponding to each batch of solder paste; continuously receiving temperature and humidity data from the temperature and humidity sensors in all the areas in the refrigerated cabinet, and preprocessing the temperature and humidity data to correct the temperature and humidity data which are higher than the data average value of all the areas but do not reach a preset abnormal alarm threshold value; calculating and updating a quality label according to the preprocessed temperature and humidity data, solder paste material characteristics and storage environment parameters; evaluating the sensitivity of each production task to the solder paste quality in the production process to obtain a sensitivity level; according to the sensitivity level and the updated accumulative microstress damage value, the solder paste batch is dispatched; and according to the updated accumulative microstress damage value, issuing a process adjustment suggestion to production equipment. The method has the effect of improving the management precision and efficiency of the full life cycle of the solder paste.

The invention discloses a secret key using method and device and a storage medium. The method comprises the steps that n data processing processes are created and used for conducting concurrent processing on data; obtaining n unused key files with the length of L from the key files with the total length of M according to the data average length L within a past period of time T, and sequentially and correspondingly distributing the n key files to corresponding data processing processes; and distributing the to-be-processed data to the corresponding data processing process for encryption processing. According to the invention, a segment of key is preset in each data processing process, so that the data processing process can immediately execute encryption operation when receiving the to-be-processed data without waiting to request to distribute the key to a key file; particularly, under the condition that the length of the data to be processed is smaller than the length of the preset key, encryption can be completed by directly using the preset key, the encryption preparation time is remarkably shortened, and the real-time performance of data processing is improved.

The application belongs to the field of smart meter fault detection, and discloses a smart meter fault diagnosis method based on distributed data set compression. First, the fault data of the meters at multiple sites is uniformly collected to generate a labeled data set, and then the data is evenly distributed to each client. The local model is trained to extract features and encapsulate information, and the representative samples are selected by the gain maximization strategy to maintain the distribution coverage and intra-class diversity. Then, batch normalization trajectory matching, multi-cropping and adversarial distillation are used to mine difficult samples and reduce the model difference by using soft labels to generate high-value compressed data. Finally, the fault diagnosis model is retrained on the integrated data, which significantly reduces the storage and transmission costs and improves the detection accuracy, providing an efficient solution for large-scale meter operation and maintenance. The method takes into account the safety and scalability, has great popularization value, broad prospects and significant benefits.

The application provides a health diagnosis method suitable for a GNSS receiver, and the method comprises the following steps: determining to-be-diagnosed sites, and acquiring calculation data and original data of GNSS receivers of each to-be-diagnosed site within a preset time period; acquiring a standard deviation of the calculation data of the GNSS receivers of each to-be-diagnosed site within the preset time period; acquiring a data average value of each quality parameter in the original data of the GNSS receivers of each to-be-diagnosed site within the preset time period; acquiring a correlation coefficient of each quality parameter and the standard deviation; acquiring quality parameters corresponding to the correlation coefficients in the top 50%; obtaining a normalized data average value of each quality parameter; and judging an influencing factor of GNSS receiver accuracy based on the normalized data average value of each quality parameter, so as to complete the health diagnosis of the GNSS receiver. The application can solve the technical problem that it takes too long to judge the authenticity of ground surface deformation by using manual work in the prior art.

The utility model provides a real-time and accurate air volume measurement system based on big data analysis, which comprises at least one big data air volume dynamic sensing device arranged in the cross section of an air duct of a non-uniform wind field, an air volume transmitter connected with the big data air volume dynamic sensing device, and a control monitoring analysis unit A for controlling and monitoring the big data air volume dynamic sensing device and the air volume transmitter. A big data air volume measurement dynamic sensing device is arranged in the cross section of the air duct of the non-uniform wind field, preset point positions are evenly distributed in the cross section of the air duct in an omnibearing mode, big data air volume measurement is conducted on the preset point positions, and the average air speed value of the cross section data of the air duct represents the actual air speed of the cross section. The problem that the geometric average wind speed value of an air volume measuring device in the prior art cannot measure the air volume of an air duct accurately is solved.

The application relates to the technical field of flood prevention drainage, and discloses a printing and dyeing drainage state analysis method and system based on sensing data. The method deploys group sensors with equal intervals in a printing and dyeing drainage pipeline, obtains drainage data, and generates a curve; the upstream curve is matched with the middlestream / downstream data as a template, time difference discrete values are calculated to identify sensing abnormalities; according to the average value of the upstream data, an execution instruction is matched, and the drainage treatment equipment is controlled in stages to continuously work, to rotate and patrol in multiple sets or to start all together, corresponding pop-up prompts, early warnings or alarms are given. Meanwhile, through multi-sensor data fusion, environmental interference is corrected, database parameters are dynamically optimized to adapt to a production cycle, pipeline undercurrent is identified in combination with detection particles, and equipment parameters are monitored to give a fault warning. The method improves the monitoring accuracy of printing and dyeing drainage and the intelligentization of equipment scheduling, and enhances the abnormal early warning capability.

Aspects of the disclosure relate to using machine learning models to automatically deallocating overallocated database storage. A computing system may retrieve database state data that indicates current states of databases. Further, the computing system may retrieve average storage usage thresholds and peak storage usage threshold for the databases. The average storage threshold for the databases may indicate an average amount of storage used by each database. The peak storage usage threshold for the databases may indicate an amount of storage that is allocatable without causing an abnormal termination. Based on inputting the database state data, the average storage usage threshold, and the peak storage usage threshold into the machine learning models, an amount of overallocated storage of the databases may be determined. Further, the overallocated storage may be deallocated from the databases based on configurations of each of the databases.

The invention belongs to the technical field of oil-gas exploration and interpretation, and discloses a method for enhancing a geological object in a frequency domain based on target orientation. Comprising the following steps: selecting a seismic attribute data volume to be researched, denoising and carrying out energy equalization, carrying out channel-by-channel z transformation, selecting a geological target sample, carrying out data averaging processing, fusing Z-domain data of the attribute volume and average Z-domain data of the geological target sample, and carrying out reverse z transformation on the Z-domain data of the enhanced attribute volume. Different from a traditional time-space domain and frequency-space domain feature enhancement method, the invention provides a geological target enhancement method of a frequency domain, z transformation of a local geological target and z transformation of an overall geological environment are combined, and manual intervention is added, so that attribute enhancement processing is no longer blindly carried out, and an effect of instant effect is achieved.

The invention relates to an imaging method and system for a dynamic enhanced magnetic resonance image with motion correction, and the method comprises the steps: carrying out the repeated continuous collection of a center K line in a K space in a layer direction through a radial collection mode of a star-shaped stacked golden angle, and obtaining the data of the center K line; and based on the sampling time sequence, averagely distributing the K-line data into a plurality of time amplitudes. One-dimensional Fourier transform is carried out on K-line data to obtain a projection contour, and three-dimensional information is projected to a layer direction. A motion information graph for generating K-line data is evaluated by utilizing a principal component analysis algorithm, and respiratory motion information is directly extracted without depending on gating equipment conditions. And according to the spatial position of the projection contour of each center K line in the graph, performing coordinate point rearrangement on each time frame motion curve, and then controlling a reconstruction model to perform continuous iteration by using a soft weighting low-rank matrix and the rearranged motion curve so as to reconstruct a reconstruction image under each motion state under each time frame. Additional motion dimension information can be provided while suppressing a blurring effect.

The invention belongs to the technical field of drug detection, and provides a drug type identification method and system based on a sensor array. The method comprises the following steps: acquiring a response data time sequence of at least three sensors in a sensor array; extracting a steady-state feature and more than one dynamic feature corresponding to the sensor based on the response data time sequence of the sensor, the steady-state feature being a ratio of a response data average value in a tail data segment to a response data average value in an initial data segment in the response data time sequence; the more than one dynamic feature at least comprises a response data accumulated value of a predefined response region in the response data time sequence; and based on the steady-state features corresponding to the at least three sensors and the more than one dynamic feature, utilizing a classification model to obtain a drug type identification result of the to-be-detected article. The invention also provides a drug type identification system. The method is extremely low in cost, easy to operate, small in calculation amount and capable of rapidly and accurately achieving identification of various drugs.

The invention relates to the technical field of spaceflight meteorology, and particularly discloses a FY-4 cloud wind guide height redesignation and inspection method fusing cloud top air pressure, which comprises the following steps: S1, acquiring cloud top air pressure data and cloud wind guide data, and matching the cloud top air pressure data and the cloud wind guide data according to time difference and spatial distance to obtain a matching result; obtaining a plurality of cloud top air pressure data in the tracking frame corresponding to the cloud air guide; s2, retrieving the cloud top air pressure data in the tracking frame to obtain a target window with the strongest cloud top air pressure data consistency in the tracking frame; s3, averaging the cloud top air pressure data of the target window at the first time and the cloud top air pressure data of the target window at the second time; s4, determining a new cloud air guide height according to a difference value between the cloud top air pressure data average value at the first time and the cloud top air pressure data average value at the second time; and S5, carrying out effect inspection on the new cloud wind guide height. The invention provides a new thought for the multi-source data fusion method in the cloud wind deflection deviation correction process.

The invention discloses a railway ballast quantity analysis method and device. The method comprises the following steps: acquiring a two-dimensional image and a depth image of a railway; inputting the two-dimensional image into the trained segmentation model, and outputting a segmentation result; according to the depth image, mapping a segmentation result to a three-dimensional point cloud, and determining a railway ballast point cloud coordinate set, a sleeper point cloud coordinate set and a steel rail point cloud coordinate set; fitting the sleeper point cloud coordinate set to generate a sleeper reference plane; determining relative height index data, average height index data and standard deviation index data; according to the relative height index data, the average height index data and the standard deviation index data, the railway ballast quantity is analyzed, and an analysis result is generated, the efficiency and accuracy of railway ballast quantity analysis can be improved, high-precision segmentation, space parameter quantification and full-scene robust analysis of the railway ballast quantity are achieved, and the method is suitable for large-scale popularization and application. And a technical support with accuracy and high efficiency is provided for railway engineering maintenance.

The invention provides a weather forecast data generation method and device and terminal equipment, and is suitable for the technical field of data processing, and the method comprises the steps: calculating the dispersion information and average information of initial weather forecast data corresponding to weather forecast mode information, initial weather forecast data dispersion information and initial weather forecast data average value information are obtained; screening the initial weather forecast data according to the dispersion information of the initial weather forecast data and the average information of the initial weather forecast data to generate intermediate weather forecast data; and generating target weather forecast data according to the intermediate weather forecast data. According to the method, the difference of each weather forecast mode can be reflected, and the weather forecast data closer to the real situation can be screened out, so that the accuracy and effectiveness of weather forecast are improved.

The invention belongs to the field of intelligent electric meter fault detection, and discloses an intelligent electric meter fault diagnosis method based on distributed data set compression. The method comprises the following steps: firstly, uniformly collecting multi-site ammeter fault data and generating a data set with a label, then averagely distributing the data to each client, extracting features and packaging information through local model training, and meanwhile, selecting representative samples by using a gain maximization strategy to maintain distribution coverage and intra-class diversity. And then adopting batch normalized trajectory matching, multi-clipping and confrontation distillation, mining difficult samples and reducing model differences by using soft labels to generate high-value compressed data. And finally, a fault diagnosis model is retrained on the integrated data, so that the storage and transmission cost is remarkably reduced, the detection precision is improved, and an efficient scheme is provided for large-scale ammeter operation and maintenance. The method gives consideration to both safety and expandability, has popularization value, and is wide in prospect and remarkable in benefit.

The application provides an on-board abnormal data determination method and device and electronic equipment. The method comprises the following steps: selecting target on-board data corresponding to the number of independent variables of a data table; determining an on-board data average curvature sequence and an on-board data Gaussian curvature sequence corresponding to the target on-board data; determining an average curvature non-abnormal value interval and a Gaussian curvature non-abnormal value interval based on a relative deviation parameter, average curvature quartiles and average curvature quartile distance, Gaussian curvature quartiles and Gaussian curvature quartile distance; determining an average sequence abnormal data and a Gaussian sequence abnormal data based on an absolute deviation parameter, the average curvature non-abnormal value interval and the Gaussian curvature non-abnormal value interval; and combining the average sequence abnormal data and the Gaussian sequence abnormal data to obtain abnormal data of the target on-board data. The on-board abnormal data determination method, device and electronic equipment solve the problems of long time consumption, low reliability and low efficiency in checking on-board abnormal data by manual means.

The invention provides a covert communication-oriented communication and inductance integration performance optimization method. The method comprises the steps of configuring a covert communication-oriented low-altitude network model in an unmanned aerial vehicle relay scene; based on the low-altitude network model, determining performance indexes in the aspects of communication and perception; on the basis of the indexes, modeling is carried out on the covert communication-oriented communication and inductance integration performance optimization problem; and based on improved multi-operator differential evolution, solving the modeled optimization problem. According to the method, a multi-index weighted optimization problem of a joint security communication reachable rate, a transmission data average information age and a beam pattern error facing covert communication is established; the provided optimization problem solving algorithm based on improved multi-operator differential evolution has strong global search capability, can effectively avoid falling into a local optimal solution, also has an adaptive parameter adjustment mechanism, can dynamically adjust the parameters of the algorithm according to the evolution process, and improves the convergence rate and robustness of the algorithm.

The invention discloses an AI adaptive feature extraction method for real-time streaming data of an internet platform, and particularly relates to the technical field of data processing. According to the method, quality parameters such as feature effective rate and feature stability and cost parameters such as average extraction time consumption of single data, comprehensive resource occupancy rate and benefit ratio are integrated, and a policy effect estimation system is constructed through normalization processing and weighted summation, so that a policy effect estimation value capable of comprehensively reflecting policy technology quality and commercial value is obtained; scientific quantitative evaluation on the effect of the feature extraction strategy is realized, and the problem that whether the strategy needs to be optimized or not is difficult to accurately judge due to isolated attention to single dimension in the prior art is solved.

This invention discloses a bridge construction deflection sensitivity analysis method, comprising the following steps: Step S1, establishing a historical database; Step S2, standardizing each parameter in the historical database; Step S3, based on the standardized parameter data, taking the average of all data for that parameter, and generating random numbers with a sample size of N from the parameter distribution; Step S4, integrating a hybrid learner; Step S5, establishing a three-dimensional deflection model of the main beam using the hybrid learner; Step S6, obtaining multiple deflection values ​​as sample output values ​​using the arithmetic mean median method; Step S7, calculating the conditional expectation of each parameter with respect to the sample output values; Step S8, calculating the magnitude of the influence of the parameters on the main beam deflection using the Sobol sensitivity analysis system. This invention, by analyzing the influence of each parameter on the main beam deflection, guides the strict observation and control of parameters with a significant impact during construction, thereby avoiding resource waste and reduced construction efficiency.

The invention provides an intelligent electrocardiosignal classification method based on a mixed cross-correlation distance, which comprises the following steps of: 1, performing dimensionality reduction compression on an original electrocardiosignal time sequence with the length of L by adopting a segmented aggregation approximation PAA algorithm, and calculating a data average value in each segment to obtain a compressed sequence represented by PAA; 2, calculating a mixed cross-correlation distance between the to-be-measured data and the candidate data, wherein the distance is obtained by weighting and combining a global cross-correlation distance and a local cross-correlation distance through a harmonic parameter alpha; and 3, sorting the mixed cross-correlation distances in an ascending order, selecting the first K neighbors, and determining the final category of the electrocardiosignals to be detected according to a majority voting principle. According to the technical scheme, the calculation complexity is remarkably reduced while high classification precision is guaranteed, so that the requirements of a modern medical monitoring system for high precision, low delay and high robustness are met.

The invention provides an information processing method and device, a storage medium and a program product, relates to the technical field of communication, and is used for solving the technical problem of relatively low user experience quality caused by difficulty in effectively calculating a wireless side guarantee rate of service requirements based on service characteristics. The method comprises the following steps: acquiring first information of a target service in an indoor test network and second information of the target service when the target service runs in an outdoor application network; under the condition that the first satisfaction degree and the second satisfaction degree are both greater than or equal to a preset satisfaction degree threshold value and the difference between the first downlink data average downloading rate and the second downlink data average downloading rate is smaller than or equal to a preset difference threshold value, according to the first downlink data average downloading rate and the second downlink data average downloading rate, downloading the first downlink data according to the first downlink data average downloading rate and the second downlink data average downloading rate; determining a rate threshold value; the rate threshold value is used for evaluating whether the effective downloading rate of the target service in the target switching period meets the preset resolution or not when the data service quality evaluation is carried out based on the DPI.

This invention provides a method for measuring air volume based on big data analysis. It utilizes an airflow meter, part of a big data dynamic airflow sensing device, installed in at least one location within the cross-section of the duct, to perform omnidirectional dynamic point-to-point airflow measurements at preset intervals during each sampling period. The measured airflow electrical signal is then transmitted to a control, monitoring, and analysis unit A via an airflow transmitter. The airflow measurements at all preset points are then summed and divided by the number of preset points to obtain the average wind speed value of the duct data. This method uses the average wind speed value of the duct cross-section data to represent the actual cross-sectional wind speed, solving the problem of inaccurate measurement of duct airflow using the geometric mean wind speed value in existing airflow measurement devices.

The application provides a wind volume measuring system of a non-uniform wind field rectangular air duct, which is mainly composed of a large-data wind volume dynamic longitude-latitude sensing device arranged in a cross section of the rectangular air duct, a wind volume transmitter connected with the device, and a control monitoring and analyzing unit A for controlling and monitoring them. The application solves the problem that the geometric average wind speed value of the existing wind volume measuring device is not accurate for air duct wind volume measurement by arranging the large-data wind volume measuring dynamic sensing device in the cross section of the non-uniform wind field rectangular air duct, uniformly distributing preset points in all directions in the cross section of the air duct, and measuring the large-data wind volume of each preset point, and using the cross section data average wind speed value to represent the actual cross section wind speed.