313results about How to "Improve data utilization" patented technology

The invention discloses a large-scale building information model and a three-dimensional digital city integration method, and belongs to the field of spatial information technology. Interactive construction is carried out on the building information model on the basis of construction drawings, then the building information model is converted into a building component information model through spatial and semantic information mapping, a building component information base is established, and integrated application of building component information is carried out in three-dimensional digital city scenes. A large-scale indoor spatial structure data source is provided for a three-dimensional digital city, and the utilization rate of data is improved; internal spatial structures of buildings and external environments are displayed integrally. The building component information model with consistent semantic and spatial information is established, various sensors in the buildings can be integrated, and useful supports are provided for smart city application.

A synchronous quick calibration method of a plurality of video cameras in a three-dimensional scanning system, which includes: (1) setting a regular truncated rectangular pyramid calibration object, setting eight calibration balls at the vertexes of the truncated rectangular pyramid, and respectively setting two reference calibration balls at the upper and lower planes; (2) using the video cameras to pick-up the calibration object, adopting the two-threshold segmentation method to respectively obtain the corresponding circles of the upper and lower planes, extracting centers of the circles, obtaining three groups of corresponding relationships between circle center points in the image and the centres of calibration ball in the space, solving the homography matrix to obtain the internal parameter matrix and external parameter matrix and obtaining the distortion coefficient, taking the solved video camera parameter as the initial values, and then using a non-linear optimization method to obtain the optimum solution of a single video camera parameter; (3) obtaining in sequence the external parameter matrix between a plurality of video cameras and a certain video camera in the space, using the polar curve geometric constraint relationship of the binocular stereo vision to establish an optimizing object function, and then adopting a non-linear optimization method to solve to get the optimum solution of the external parameter matrix between two video cameras.

The invention discloses a digital management system for project construction processes. The system comprises a data layer, a platform layer and application layers, wherein the data layer comprises a BIM construction module which is created via a division principle of a construction quality management unit; the data layer comprises system attribute data, BIM model data and business management data;the platform layer consists of a B/S architecture-adopted PC platform and a mobile platform; the PC platform application layer consists of a project board module, a BIM board module, a business management module and a statement center module; a business management module comprises a progress management module, a quality management module, a safety management module, an expense management module and a document management module; and a mobile platform application layer is a mobile office layer which consists of a project dynamic module, a model display module and a digital construction site module. The system has the advantage of improving the management precision and efficiency of project construction processes.

The invention discloses a radar echo extrapolation method based on a dynamic convolution neural network. The method comprises a step of offline convolutional neural network training which comprises the steps of carrying out data preprocessing on a given training image set to obtain a training sample set, initializing a dynamic convolution neural network model, training a dynamic convolution neural network by using the training sample set, calculating an output value through network forward propagation, and updating network parameters through backward propagation such that the dynamic convolution neural network converges. The method also comprises a step of online radar echo extrapolation which comprises the steps of converting a test image set into a test sample set through data preprocessing, testing the trained dynamic convolution neural network by using the test sample set, and carrying out convolution of a laster radar echo image inputted into an image sequence and a probability vector obtained in the network forward propagation to obtain a predicted radar echo extrapolation image.

Data analysis applications include model building components and stream processing components. To increase utility of the data analysis application, in one embodiment, the model building component of the data analysis application is managed. Management includes resource allocation and/or configuration adaptation of the model building component, as examples.

The invention relates to a sparse convolutional neural network accelerator and a realization method, and the method comprises the steps: reading the connection weight of a sparse network in an off-chip DRAM into a weight input buffer area, decoding the connection weight through a weight decoding unit, and storing the connection weight in a weight on-chip global buffer area; Reading neurons into aneuron input buffer area, decoding the read neurons through a neuron decoding unit, and storing the decoded neurons in a neuron on-chip global buffer area; Determining a calculation mode of the PE calculation unit array according to the configuration parameters of the current layer of the neural network, and sending neurons and connection weights which are arranged after decoding to a PE calculation unit; Calculating the product of the neuron and the connection weight; In the accelerator, the multipliers in the PE units are all replaced by the shifters, and all basic modules can be configuredaccording to network calculation and hardware resources, so that the accelerator has the advantages of high speed, low power consumption, small resource occupation and high data utilization rate.

The invention relates to a harmonic contribution division method and a harmonic contribution division system. The harmonic contribution division method comprises the following steps of acquiring harmonic voltage data of a bus and harmonic current data of a harmonic source to be calculated on a feeder line; calculating background harmonic impedance by using a leading fluctuation quantity method according to the harmonic voltage data and the harmonic current data; and dividing harmonic contributions of the harmonic source to be calculated by using a quantile regression method according to the harmonic voltage data, the harmonic current data and the background harmonic impedance. The background harmonic impedance is estimated by the leading fluctuation quantity method, fluctuation quantity with a leading function is screened out to calculate the background harmonic impedance, influences of background harmonic and measurement noise fluctuation on a background harmonic impedance estimation result are restrained effectively, and the background harmonic impedance is calculated accurately; and the background harmonic current is calculated according to the background harmonic impedance, and quantile regression is performed to obtain the harmonic contributions of the harmonic source. Calculation deviation caused by background harmonic fluctuation can be reduced, division accuracy is improved, and the stability and the data utilization rate are high.

The invention provides an electronic coupon data generation method and an electronic coupon data generation device. The method includes: presetting an electronic coupon template which includes template identifiers and basic attribute information of an electronic coupon; according to the electronic coupon template, generating an electronic coupon application form which includes an application form identifier and the template identifier corresponding to the application form identifier, and generating electronic coupon entity attribute information according to the basic attribute information of an electronic coupon; and generating electronic coupon entity data according to the electronic coupon application form, and extracting the electronic coupon entity attribute information according to preset requirements, wherein the electronic coupon entity data include an electronic coupon identifier and an application form identifier and the template identifier corresponding to the electronic coupon identifier. The method and the device can be flexibly adapted to different needs of different electronic coupons to enable creating logic, process data and account checking logic and data to be unified respectively, and thereby reliability of the electronic coupon data is improved greatly.

The invention discloses a tinnitus sound diagnosis and treatment method. Tinnitus diagnosis and treatment methods, including S101: Establishing patient files; S102: Doctors conduct questionnaires on patients through questionnaires and assessment scales, and patients fill in the questionnaires and assessment scales by choosing, and doctors judge the overall situation of tinnitus of patients ; S103: The doctor checks the patient's auditory function; S104: Input and calculate the test data, establish a test result table and compare the data; S105: Output the test data, graphics, images and tinnitus test data, and choose whether to print; S106: According to Desensitization fitting is performed on the detected data. The desensitization fitting includes acoustic stimulation verification and therapeutic sound matching. The selected sounds form a formula, and the formula includes standard stimulation sounds, TRT sounds or background music and other sound types; S107: Combine the sound The treatment formula is output to the treatment device, and the patient is treated with sound through the treatment device.

The invention provides a monitoring and managing system for wind power storing station comprehensive information. The system comprises a wind turbine monitoring system, an energy-storing and power-distributing monitoring system, a wind power predicting system, a battery managing system and a wind storing comprehensive information system. The wind turbine monitoring system, the energy-storing and power-distributing monitoring system and the wind power predicting system are connected to the wind storing comprehensive information system. An energy-storing monitoring system part is composed of the battery managing system and the energy-storing and power-distributing monitoring system. Corresponding wind power data, data in the wind turbine monitoring system, data in an energy storing and converting system and data in the battery managing system are combined, and graphs, tables and other forms are utilized to provide overfull and direct display to operators and managers, display of wind storing comprehensive power generating performance is realized through deep extraction, excavation and analysis of the data, wind-storing coordinating operation is further optimized, and determine support is provided for superior scheduling and the managers.

The invention provides a processing system for three-value weight convolution network. The system comprises at least one storage unit which is used for storing data and an instruction; at least one control unit which is used for obtaining the instruction stored in the storage unit and transmitting a control signal; and at least one calculating unit which is used for obtaining a node value of one layer in a convolution neural network from the storage unit and the corresponding three-value weight data, and obtaining the node value of a next layer through the execution of addition and subtraction operations. The system reduces the data bit width in the calculation process of the convolution neural network, improves the convolution calculation speed, and reduces the storage capacity and work energy consumption.

The invention discloses a multi-signal-source frequency and DOA joint detection method and a multi-signal-source frequency and DOA joint detection device. The multi-signal-source frequency and DOA joint detection method comprises the steps of: conducting Mf-point DFT on L paths of signal samples, correcting frequencies and phases of DFT results by using a Tsui spectrum corrector to obtain a parameter group of corrected D groups of frequencies, phases and amplitude values, and constructing D direction vectors by using the parameter group; grouping and matching the D direction vectors accordingto the minimum distance to obtain D pieces of signal source parameter matching information; constructing a frequency remainder group according to the D pieces of signal source parameter matching information, and substituting the frequency remainder group into a closed type robust Chinese remainder theorem (CRT) model for reconstruction, so as to obtain a frequency estimated value; and acquiring L-1 phase differences according to the D pieces of signal source parameter matching information, constructing a phase reminder group, substituting the phase remainder group and a reconstructed module value group into the closed type robust CRT model for reconstruction to obtain an intermediate parameter, and calculating to obtain a DOA estimated value. The multi-signal-source frequency and DOA jointdetection method and the multi-signal-source frequency and DOA joint detection device realize the high-precision frequency and DOA joint estimation of multiple pairs of targets.

The invention relates to a data storage system based on a Hadoop architecture. The storage system comprises at least one application server, a backup server, a database cluster and at least one core layer switch; the database cluster comprises a first sub-storage cluster and a second sub-storage cluster; basic data of structured data are stored in the first sub-storage cluster, and unstructured and semi-structured loose data are stored in the second sub-storage cluster; the application server, the backup server and the database cluster are respectively connected to the core layer switch; and the application server is connected with the backup server and the database cluster, and used for managing real time data of the backup server and the database cluster. The data storage system based onthe Hadoop architecture provided by the invention uses a distributed storage mode to store the data and uses redundant storage to ensure the reliability of the data. An HDFS (Hadoop Distributed FileSystem) module can reliably store massive files across machines, and stores various files as data block sequences of the same size.

The invention provides a data access control method and device. The method comprises the steps: receiving a database access request of a target user, the database access request comprising user information and a target SQL statement list; sequentially obtaining statement types of all SQL statements which are in an unprocessed state currently in the target SQL statement list, and judging whether the target user has the access permission of the target data or not according to the user information, preset permission information for the user to access the database and a statement type, If so, sending the SQL statement to the target database. According to the invention, the reliability and flexibility of data access control can be improved, and the universality of an application scene can be improved.