95results about How to "Simplify data volume" patented technology

This invention provides a position monitor method and a system , in which, said method includes: A, designing a mobile admitted boundry of a monitor target and a mobile admitted region corresponding to said boundary, B, plotting out caution regions contained in the mobile admitted region including caution regions in the admitted region sphere and those passed by the boundary or pressing the edge, said caution region is a square and the transverse edge of said square is parallel to the woof, every caution is corresponding to a parameter including the longitudinal and latitude value of an any opposite angle of the square on an electronic map, C, following the position change of the monitor target to report the current position information including longitudinal and latitude value of the current position of the target, D, determining the caution region the target places based on the information of the target to issue beyong the mark alarm information when the target overstepping the mobile admitted region.

The invention relates to the technical field of geographical information systems and provides a vector data compaction and compression method based on virtual screen mapping theory as well as a corresponding decompression method. The vector data compaction and compression method includes the following steps of: determining the size of a virtual screen; conducting Douglas compaction on segmental arc coordinate; conducting virtual screen mapping on the coordinate; conducting offset storage and compression on the segmental arc coordinate; and packing data after compaction and compression and conducting general lossless compression. The methods can be widely applied to the vector data compaction and compression in the fields of GIS, Web, GIS, MovingGIS and car navigation, and can compact and compress the volume of vector data dramatically on condition of meeting visual fidelity.

The invention provides a body axis system based oil level measuring method which is stable and reliable and can improve the measuring accuracy. According to the technical scheme, the body axis system based oil level measuring method comprises the following steps of establishing a fuel oil quality character database of attitude information and a straight line which is perpendicular to an XY panel, wherein the straight line is called a virtual sensor; enabling oil measurement sensors in a measuring process to be equivalent to straight lines and meanwhile establishing a body axis system based virtual sensor straight line equation according to installation positions of the sensors; measuring immersion oil surface height through more than three linear capacitive type oil measurement sensors which are arranged at different positions, obtaining coordinates of three points in an oil surface in combination with oil surface angle measurement and obtaining an oil surface attitude angle and an oil surface equation; obtaining coordinates of an intersection point of the line and the surface through the oil surface equation and the virtual sensor straight line equation; representing corresponding relationships of the oil surface height, the oil surface angle and the fuel amount through the fuel quality characteristic database and finally obtaining an oil amount measuring result through the three-dimensional linear interpolation calculation.

The invention relates to a hydraulic model building demands based digital processing method for a drainage pipeline network and belongs to the crossing field of the municipal engineering information technology and the geographic information system technology. Started with hydraulic model building demands, GIS (geographic information system) operation of standard CAD (computer-aided design) vector data is greatly simplified, main operation steps are automatically implemented through computers, errors of original data can be authenticated in time by the aid of a debugging mechanism, and digital processing of the drainage pipeline network system can be quickly and accurately realized. The hydraulic model building demands based digital processing method has the advantages that data size inputted manually by conventional processing methods is greatly simplified, flow direction information of pipeline sections is the only thing to determine, and complicated operations of inputting upstream and downstream node numbers of the pipeline sections are eliminated. Meanwhile, operability of various steps is taken into consideration, the steps can be implemented only by the aid of simple operations on the GIS platform instead of complicated procedural programming, and implementation of the digital processing method is guaranteed.

The invention provides a mining method for C-Mn steel industry big data and belongs to the field of cross technologies of steel industry production and data statistics modeling.The method includes the steps of data sample selection, steel coil merging, similar process clustering and training data uniformization.Through selecting data of multiple steel brand numbers, a data sample includes comprehensive parameter information, a more objective physical metallurgy rule is reflected, and a model has higher adaptability; through judging components of a steel blank to be detected and adopting the clustering method, multiple sets of data of a similar process are corrected to be one set of data, in this way, the data volume is simplified, and redundant data is deleted; in the process, abnormal data is rejected, errors are reduced, and data regularity is more obvious; through performing statistics on distribution of three kinds of mechanical properties of training data, the distribution balance of the training data is adjusted; by the adoption of a balanced data training neural network, a network model can learn about balanced information, and the regularity and accuracy of the model are improved.

The invention discloses a fluency assessment method and apparatus, and belongs to the technical field of computers. The method comprises the steps of obtaining minimum fluency in each time segment of a predetermined duration; performing interval division on the predetermined duration by utilizing the obtained minimum fluency, wherein each interval comprises at least one time segment; calculating a fluency score of each interval according to the value of the minimum fluency and the length of each interval; and calculating a total fluency score in the predetermined duration according to a predetermined mode based on the calculated fluency score of each interval. According to the method and the apparatus, the problem that an invalid frame rate obtained in a static time segment of an application cannot measure the fluency of drawing the application by the mobile terminal when the fluency of drawing the application by the mobile terminal is measured through the frame rate in related technologies is solved; and the effect of reflecting a jamming degree in the predetermined duration more really during measurement of jamming in the predetermined duration by utilizing the total fluency score in the predetermined duration is achieved.

The invention relates to a compressive-sensing-based on-satellite real-time image synthesis compression system, which comprises n compressive-sensing measurement modules and a measurement data synthesis module, wherein each compressive-sensing measurement module carries out random measurement on original row image data X output by a corresponding channel of a multichannel TDICCD (Time Delay and Integration Charge Coupled Device) by using a Bernoulli random measurement matrix to obtain compressed measurement data Y; and the measurement data synthesis module synthesizing measurement data Y of all channels into an entire row of compressed image measurement data. According to the invention, the data of each channel of the multichannel TDICCD is compressively sensed on satellite to obtain compressed data to be synthesized and transmitted to the ground, and a complex compressive sensing restructing algorithm is carried out on ground. A complex data recovery algorithm on ground is used to exchange a simple and reliable on-satellite image compression method, so that the work frequency of on-satellite circuits is reduced, and the stability of an on-satellite image integration circuit is improved, and meanwhile, on-satellite hardware resources are saved.

The embodiment of the invention discloses a data synchronization method, device and system. The method comprises the steps: receiving a data synchronization instruction sent by a terminal, wherein the data synchronization instruction comprises a cloud account and to-be-synchronized data; obtaining backup data according to the data synchronization instruction; carrying out the reprocessing of the to-be-synchronized data according to the backup data, so as to obtain target to-be-synchronized data; transmitting the target to-be-synchronized data to a log-in terminal which logs in the account, so as to enable the log-in terminal to complete the data synchronization. According to the scheme, the method achieves the data synchronization between terminals, can carry out the reprocessing of the to-be-synchronized data, simplifies the data size, speeds up the transmission of data, and effectively improves the efficiency of data synchronization.

The invention relates to the technical field of the communication security, especially a safety authentication and data communication system between internet of things equipment. The system comprisesa data injection system for producing IDs, certificates, and public and private key pairs of credible internet of things equipment, and commonly injecting the IDs, the certificates, the public keys and the private keys and the public key of the data injection system into the credible internet of things equipment; the credible internet of things equipment for storing various data sent by the data injection system, wherein the IDs, the certificates and the public and private key pairs between various credible internet of things equipment are different except that the public key of the data injection system is same in the data stored in different credible internet of things equipment. Through the technical scheme disclosed by the invention, the data storage security is improved, the maliciousattack is prevented, and the computation efficiency in the authentication process and the encryption process is improved; the technical scheme disclosed by the invention simplifies the interaction frequency and data size required by inter-equipment handshake and identity authentication, and improves the communication efficiency among various internet of things equipment; and the above scheme is easy to realize and convenient for transplant.

The invention discloses a sewage treatment soft measuring method based on an RVM. The method sequentially comprises the steps that a fuzzy monotone increasing dependence algorithm is used for conducting attribute reduction on collected sewage input data, and an input attribute which has a great influence on COD and BOD is quantificationally analyzed; a predication model is established through the RVM and the collected sewage input data, model parameters are optimized, and accordingly an optimal predication model is established; the input attribute which has the great influence on COD and BOD is determined through the collected sewage input data; sewage sample data to be predicted are predicted; the sewage input data after attribute reduction is used as the input of a soft measuring model of the well-trained RVM, namely the output of the model is the prediction result of effluent COD and BOD. By the adoption of the method, prediction accuracy is high, and needed time is short.

The invention relates to the technical field of data processing and artificial intelligence, and discloses a traffic road condition prediction method and device, electronic equipment and a storage medium. The traffic road condition prediction method comprises the steps of acquiring first feature data of a traffic road condition in a to-be-predicted period and a congestion probability of a period previous to the to-be-predicted period; acquiring second feature data corresponding to a plurality of historical periods before the to-be-predicted period and a target label sequence; determining a first target feature sequence based on the relevancy between a feature sequence formed by the second feature data and the target label sequence, wherein the first target feature sequence comprises secondfeature data of at least two historical periods; and according to the first feature data of the to-be-predicted period, the congestion probability of the period previous to the to-be-predicted periodand the first target feature sequence, determining the traffic congestion probability of the to-be-predicted period. By utilizing a traffic condition prediction scheme provided by the invention, theaccuracy of the obtained traffic jam probability of the to-be-predicted period can be improved.

The embodiment of the invention discloses an image compression method, computer equipment and a computer storage medium, a code rate control module at a coding end can map a weight factor into a code rate control vector, and multiplies the code rate control vector with a sparse feature map to obtain potential feature representation of a specified code rate, and the potential feature representation is used for compressing the specified code rate. The quantization unit quantizes floating points in the potential feature representation of the specified code rate into integers to obtain an integer type potential feature representation, and the lossless coding module performs entropy coding on the integer type potential feature representation to obtain a binary code stream, so that only one target neural network image compression model needs to be trained, and the image compression efficiency is improved. And the compression ratio, the code rate and the reconstruction quality of the image can be adjusted at will only by adjusting the weight factor, so that a plurality of image compression models do not need to be trained, a computer device does not need to deploy a plurality of image compression models, and the hardware storage overhead of user equipment is greatly reduced. The number of elements of the sparse feature map is greatly reduced, the calculation amount of a subsequent module can be reduced, and calculation resources are saved.

The present invention discloses a moving platform infrared image-spectrum associated detection system, including an optical hood, a broadband optical system, a two-dimensional servo system, an infrared optical fiber, a Fourier interference spectrum module, an image-spectrum associated detection processing module, a power supply module, and a display module. Incident light enters from the optical hood to the broadband optical system, and is split by a spectroscope. Transmitted light is focused by a long-wave imaging lens group on an infrared detector for imaging. Reflected light is focused by a broadband spectrum lens group to an optical fiber coupler, enters the Fourier interference spectrum module through the infrared optical fiber to form an interference pattern, and undergoes Fourier transform to obtain spectral data. The image-spectrum associated detection processing module effectively merges infrared imaging and broadband spectral data, and the two-dimensional servo system is used to control a center orientation of the broadband optical system, thereby implementing target detection, tracking and spectrum measurement in a moving platform condition. The present invention can effectively isolate the system from disturbance of the moving platform, has the capability of simultaneously performing scene imaging, local area spectrum measurement, and multi-target tracking spectrum measurement, has a high speed and an adequate data amount, and has a broad application prospect.

The invention discloses a text mode generation method which is suitable for being executed in a computing device. The method comprises the steps that a text library comprising multiple pieces of text data is obtained, and word segmentation processing is conducted on each line of the text data; frequency of occurrence of each word is counted from the text data, high-frequency words are screened out, and the high-frequency words and the frequency of occurrence of the high-frequency words are subjected to associative storage; the high-frequency words in each line of the text data are screened out, and a high-frequency word tuple corresponding to the line of the text data is formed; the dependency degree between any two high-frequency words is calculated according to the frequency of occurrence of all high-frequency words in the text data; a preselected text mode of each line of the text data is generated according to the high-frequency word tuple corresponding to the text data; preselected text modes are corrected according to the dependency degree between the high-frequency words, and the corrected text modes of the text data are obtained; similarity merging is conducted on the corrected text modes, and a text mode library is obtained. The invention further discloses a corresponding text mode generation device and the computing device.

The invention relates to the technical field of big data, and provides a risk conduction association map optimization method and device, a computer device and a storage medium. The method comprises the following steps of obtaining the risk nodes in an initial risk conduction association map and the user risk data corresponding to the risk nodes, according to the device label information corresponding to the risk nodes, determining an device label risk weight parameter of the risk nodes, according to the correlation factors between the directly-correlated risk nodes and the corresponding user risk data, determining a reference weight parameter of the correlation factor; according to an association factor combination between the indirectly associated risk nodes, and the correlation levels of the correlation factors in the combination, combining the reference weight parameters, determining the risk conduction weight parameters of the correlation factors under the correlation levels, updating the parameters of the initial risk conduction correlation map, optimizing the risk conduction correlation map, and fully mining the deep relation between the nodes of the correlation map, so that the optimization of the initial risk conduction correlation map is achieved, and the risk analysis efficiency is improved.

The invention relates to a solar photovoltaic assembly monitoring and alarming system which comprises photovoltaic assemblies, assembly monitoring units, a signal reception circuit and a master site. Each photovoltaic assembly is internally provided with one assembly monitoring unit; each assembly monitoring unit is a signal acquisition and emission circuit; the plurality of photovoltaic assemblies are connected in series in sequence, and are connected with a signal reception circuit through DC power lines; and the signal reception circuit is connected with the master site through a communication cable. The system can automatically give an alarm when the temperature and voltage of the assemblies are abnormal, so that power station maintainers are allowed to position combiner box alarm branches accurately in time through the monitoring background, and then, troubleshoot abnormal assemblies of the branches, time is saved and working efficiency is improved.

The invention discloses a fault diagnosis method of a switching current circuit. The fault diagnosis method comprises the steps of: first, carrying out sensitivity analysis on components of the switching current circuit, setting the fault types and collecting fault information; then, carrying out pre-processing on the acquired information to acquire a dimensionality reduction characteristic vector and a cloud model digital characteristic value; optimizing a wavelet neural network structure weight value and a threshold value by adopting a fish swarm algorithm; and finally, carrying out diagnostic analysis on parameter data to acquire the fault type. Through adopting the fault diagnosis method, the mode of data processing is more reasonable, the network structure is more stable, the diagnosis accuracy is higher, and the convergence rate is higher.

The invention provides a display method and system for optical fiber detection and an optical time domain reflectometer. According to the method, the system receives and collects reflected signals of tested optical fibers based on testing signals sent to the tested optical fibers to obtain detection data of the corresponding reflected signals, and the dead zone width of events in the tested optical fibers is preset; wavelet domain transformation is carried out on the collected detection data, and an extreme point is determined in high-frequency coefficients; detection data with a peak value and a valley value are determined in the dead zone width behind the detection data corresponding to the extreme point, and the detection data corresponding to the extreme point, the peak value and the valley value are used as key points; inter-partition average calculation is carried out on the other detection data spaced by the determined key points, and detection data are selected from the detection data of partitions as the key points corresponding to the average value of the corresponding partitions; the determined key points are connected and displayed according to the time sequence. Therefore, the detected waveform is displayed accurately and fast.

The invention relates to a government affair data synchronization method, device and system, computer equipment and a storage medium. The method comprises the steps of obtaining a synchronization task; wherein the synchronization task is created after it is detected that government affair data updating operation of the source platform is completed; determining target government affair data and a target synchronization mode according to the synchronization task; wherein the target government affair data is changed government affair data on the source platform corresponding to the updating operation; and synchronizing the target government affair data to the target platform according to the target synchronization mode. By adopting the method, the data volume to be synchronized can be reduced; the synchronization task is not easy to lose in the synchronization process, the creation of the synchronization task does not need the comparison operation of total data, the calling frequency of the synchronization interface is reduced, millisecond-level government affair data synchronization can be realized, the real-time accuracy of data synchronization is ensured, and the performance of a synchronization system and the use experience degree of a user are effectively improved.

The invention relates to a predication control method for a brushless DC motor drive system. According to the invention, current value of a practical system and a current value based on a hybrid logic dynamic model and subjected to state estimation are collected and compared, and future parameters are predicated according to history parameters of the system, namely, state estimation is performed on the system. Current is taken as the major control object of the design in the invention. The controller takes comparison signals of inverter output signals of the practical brushless DC motor drive system and output signals of the state estimator as reference signals. After estimation of future moment parameters of the system is performed, an optimized target function is set, so that the optimal control volume of the next moment is selected and an aim of prediction control is achieved. By adopting the method, data volume is simplified, control features of the brushless DC motor are improved, inhibition on electromagnetic torque pulse is realized and practical application is facilitated.

The embodiment of the invention discloses a mapping method and device based on an image group. The method comprises the following steps: acquiring multiple groups of road images when a vehicle travelsfor multiple times in the same position area and a positioning pose corresponding to each road image; performing data association among the semantic features in each group of road images to obtain associated semantic features belonging to the same road sign among each group of road images, and determining a first position of the associated semantic features in a world coordinate system; determining a reprojection error between the associated semantic feature and the corresponding semantic feature in each road image according to the first position and the positioning pose corresponding to eachroad image, determining a projection error sum value between the reprojection errors, and determining a second position of the associated semantic feature in the world coordinate system according tothe projection error sum value; and adding the associated semantic feature and the second position to the map. By applying the scheme provided by the embodiment of the invention, the accuracy of the constructed map information can be improved.

The invention provides a vector tile generation method and system adaptive to multiple data sources in the technical field of electronic maps, and the method comprises the following steps: S10, calculating a longitude and latitude range based on the level and the row and column number of a tile pyramid where a vector tile is located, and obtaining a map layer corresponding to the vector tile from a configuration file; s20, acquiring spatial data corresponding to the vector tiles from a spatial data source based on the longitude and latitude range and the map layer; step S30, carrying out data assembly and format conversion on the spatial data; step S40, acquiring a proportional scale of a vector tile, and simplifying the spatial data after format conversion based on the proportional scale; and step S50, generating a vector tile from the simplified spatial data based on a vector tile specification of Mapbox. The invention has the advantages that the data is assembled according to needs, the compatibility of the data source is greatly improved, and the data volume is greatly reduced.

The invention provides an axial mode recognition method for a structure. The axial modal identification method comprises the following steps: firstly, establishing a finite element model of a structure; setting constraint conditions and carrying out modal analysis; then reading effective quality data of each order of mode from a generated result file, defining and calculating an axial quality ratio function (EMP) of each order of mode, performing preliminary screening, then reading corresponding node displacement data, defining and calculating an axial motion node proportion (ANP) of the corresponding mode, and finally classifying and identifying the structure modes. According to the analysis and recognition method, a high-degree-of-freedom complex finite element model composed of hundredsof thousands of units can be processed, modal results can be accurately classified and recognized in dozens of or even hundreds of orders of modes, and the method is beneficial for improving the simulation efficiency, shortening the simulation period and improving the guiding effect of simulation analysis on actual production.