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

The invention discloses a substation secondary system operation and maintenance cloud platform, comprising in-place layers and a centralized control layer, which are configured to read data from a production management system directly to realize equipment management, operation management, fault handling, duty management and maintenance management. The in-place layers and the centralized control layer exchange power grid operation data by means of a dispatching data network, and exchange operation and maintenance management data by means of an integrated data network; each in-place layer comprises a substation control layer, a spacing layer and a process layer; each process layer comprises all primary equipment of a substation, and transmits information of the primary equipment of the present layer to the substation control layer by means of corresponding detection equipment; and each spacing layer comprises all secondary equipment of the substation, and transmits information of the primary equipment of the present layer to the substation control layer by means of corresponding detection equipment. The substation secondary system operation and maintenance cloud platform integrates the cloud computing technology, the big data technology, the Internet of things technology and the mobile internet technology, unifies data interfaces and dispatching among different secondary operation and maintenance systems in safety regions, and realizes good management of operation and maintenance information.

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 data integration method and system of a heterogeneous relational database based on XML (Extensive Makeup Language), which aims to solve the problem that large amount of data information cannot be utilized efficiently. The method comprises the steps of: acquiring data integration requirement and integration pre-preparation; executing a database product which adds new support to the system if integration application involves in the new database product; adding a data source related to integration; generating a search request configuration file; entering persistent parameters on a persistent parameter configuration interface of the system; selecting an integration plan file on an integration plan executing interface of the system and executing the integration plan; waiting processing of a software system and repeating the steps 4 to 6 till all integration tasks are completed. The data integration system of the heterogeneous relational database based on XML is a functional module structure consisting of an integration task manager, a data source manager, a query decomposition optimizer, a data extractor, a result aggregator and a result persister.

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 discloses a well-testing interpretation model used for analyzing a series structure of multiple fracture-cave units and methods. The model includes: merging fracture-karst-cave reservoirbodies in fracture-cave-type oil reservoirs into the fracture-cave units; merging fracture-corrosion-hole reservoir bodies in the fracture-cave-type oil reservoirs into the fracture-cave units; for carbonate-rock fracture-cave-type oil reservoirs, using the fracture-cave units and fracture-hole units to approximate radial sector structure bodies; and regarding connection areas between sectors aspressure conducting areas with no pressure dropping, namely being equal to boundary pressure of the preceding sector by pressure of an outflow end of the subsequent sector, and being equal to a boundary inflow amount of the preceding sector by an outflow amount of the subsequent sector. One of the methods includes applying the model to analysis and interpretation technology of the fracture-cave-type oil reservoirs. According to the well-testing technology solution used for analyzing the fracture-cave-type oil reservoirs provided by the invention, a well-testing technology blank of the fracture-cave-type oil reservoirs is filled, a utilization rate of well-testing data is increased, and a well-testing analysis means is provided for knowing and evaluating fracture-cave-type oil reservoir structures.

The present invention relates to a heath care system having proximity-based neighbor device wake-up and automatic user identification function, a method for automatic logging of user's daily activity history, and a method for managing a user activity pattern, and the system comprises: a health or wellness service unit; and an user terminal. The health or wellness service unit transmits a wake-up signal for changing a state of the user terminal from a sleep state into a wake-up state, a low frequency (LF) signal for identifying a physical distance and direction between the health or wellness service unit and the user terminal, and a measured biological signal of a measuring object. The user terminal receives the biological signal, the wake-up signal, and the LF signal through bidirectional wireless communication with the health or wellness service unit, and transmits a terminal identification (ID) and a received signal strength indication (RSSI) corresponding to the received LF signal.

The invention discloses a double-subsegment phase difference frequency estimation method and a device adopted by the method. The method comprises the steps of taking first subsegments and tail subsegments in 2N-1 samples x(-N+1)-x(N-1) to form double subsegments; respectively performing FFT transformation on x0 and xN-1 to obtain corresponding peak value spectrums; performing simple linear treatment on a peak value spectrum phase (shown in description) difference value to obtain a frequency estimation result. The device comprises an analog-digital converter, a DSP device and a driving and displaying module, wherein signals x(t) to be detected are sampled through the analog-digital converter to obtain a sample sequence x(n), the sample sequence is fed into the DSP device in a parallel digital input mode, and parameter estimation of the signals is achieved through internal algorithm processing of the DSP device. Finally, the frequency estimation result and theoretical mean square errors of frequency estimation are displayed through the driving and displaying module. The double-subsegment phase difference frequency estimation method and the device are small in computation amount, and the estimation method is simple, high in efficiency and low in resource consumption, and the hardware cost is greatly saved.

The embodiment of the invention discloses a model training method and device, an image category detection method and device and electronic equipment. An embodiment of the method comprises the steps ofobtaining a sample set; determining a target sampling probability of each category of image samples based on the number of each category of image samples, and enabling the number of each category ofimage samples to be inversely proportional to the target sampling probability; using a random sampling mode and a sampling mode based on a target sampling probability respectively for sampling image samples in the sample set, taking the image samples sampled in different sampling modes as inputs of different branch networks in the initial model containing the double-branch network, and training the initial model based on annotation information of the sampled image samples to obtain an image category detection model. According to the embodiment, the data utilization rate in the model training process is improved, so that the model fully learns the characteristics of various types of image samples, and the detection precision of the image type detection model is improved.

The invention relates to a computer identification technology, and specifically relates to a traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data. The methodcomprises: (1) preparing and preprocessing data; (2) designing label types; (3) extracting travel characteristics; (4) establishing an improved traffic mode manual identification process; (5) trainingan initial classifier; (6) judging the traffic mode of an unmarked sample; (7) judging whether the classifier meets a termination condition or not; (8) updating a high confidence coefficient sample data set; (9) optimizing a semi-supervised SVM classifier based on a Tri-training; (10) judging the traffic mode of an unmarked sample; (11) judging whether the classifier meets a termination condition; (12) updating a data set of a low-confidence sample; and (13) optimizing the shell vector-based semi-supervised SVM classifier. The information acquisition cost is reduced, the data utilization rateis improved, judgment is flexible and comprehensive, the precision is high, and the application scene is wider.

The invention discloses a power-stealing prevention analysis method and apparatus. The method includes acquiring the power consumption abnormal events and corresponding event time of a target user based on the records in a power consumption information acquisition system, wherein the power consumption abnormal events include electric energy meter operating events and electric energy meter abnormal events; and determining the target user being suspicious in power stealing when the electric energy meter operating events occur and then the electric energy meter abnormal events occur. According to the invention, some specified sequence modes related to the power-stealing events can be found out through the analysis of a lot of historical data in the power consumption information acquisition system, and whether the user is suspicious in power stealing can be determined. Therefore, the effectiveness and pertinency of the power-stealing prevention and checking of the power consumption information acquisition system can be improved, the effect of the power-stealing prevention of the power consumption information acquisition system can be fully achieved, and the data utilization rate is improved.

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 discloses a method for implementing orbit determination and time synchronization of a Beidou satellite III by utilizing an inter-satellite link and an anchorage station, and belongs to the field of satellite navigation. According to the method, orbit determination and time synchronization are simultaneously implemented by utilizing data of the inter-satellite link and the anchorage station, a ground monitoring station is not required, and the Beidou satellite III can get rid of dependence on the monitoring station and implements autonomous navigation; in the data processing process, epoch naturalization does not need to be carried out, and thus, orbit information does not need to be predicted, and if satellite clock error non-zero-order item coefficients are simultaneously solved or ignored, clock error information also does not need to be predicted; only unidirectional pseudo-range data is required, bidirectional data pairing is not required, and a data utilization rateis high; and a satellite orbit and a clock error are simultaneously solved, statistical optimal solutions can be obtained, and the orbit and the clock error have better self-consistency.

The invention discloses a novel method for analyzing reservoir physical properties by using pressure drop section data in shale gas reservoir fracturing construction. According to the method, change data of oil pressure and discharge capacity along with the construction time in the fracturing process is accurately read from a fracturing construction curve, and abnormal data with the fluctuation amplitude greater than 1 percent is removed; dimensionless pressure is defined, and the pressure drop section time is converted into a dimensionless form; and a theoretical dimensionless pressure value is calculated, the dimensionless pressure data is compared with the theoretical dimensionless pressure value, and if the error exceeds 1 percent, a trial and error method is used for re-adjusting the reservoir physical property permeability, the dimensionless storage coefficient, the single-well control radius and the dimensionless analytic parameter coefficient until the calculation precision is reached. The novel method has the beneficial effects that the pressure drop section data in the shale gas reservoir fracturing construction is used for analyzing the result accuracy of the reservoir physical properties, and the data utilization rate of the fracturing construction data is improved.

A data storage and retrieval system includes a data space area where a set of data belonging to a predetermined category and definition data describing definition of the structure and the presentation form of the data are stored, a data space retrieval section for retrieving data and definition data made to correspond to the data from the data space area, a data space operation section for rewriting the definition data made to correspond to the data retrieved by the retrieval section on the basis of another definition data stored in the data space area, and a display for displaying the data retrieved by the retrieval section on the basis of the definition data rewritten by the operation section.

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 relates to a travelling information management system which comprises a cloud platform, a basic platform and an application platform. The cloud platform utilizes cloud computing technology for constructing a basic operation environment for supporting operation of the basic platform and the application platform. The basic platform is used for performing data acquisition, processing an interface calling request which is transmitted from the application platform and performing comprehensive analysis processing. The application platform is used for transmitting the interface calling request for acquiring an analysis processing result of the basic platform. The application platform is further used for determining a corresponding management plan and supplying a traveling information service according to an analysis processing result which is fed back from the basic platform. Management plans in different angles are supplied according to different requirements. The travelling information management system has advantages of reducing system operation cost, facilitating dynamic expansion, simplifying maintenance, improving data utilization rate, etc.

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 present invention relates to a heath care system having proximity-based neighbor device wake-up and automatic user identification function, a method for automatic logging of user's daily activity history, and a method for managing a user activity pattern, and the system comprises: a health or wellness service unit; and an user terminal. The health or wellness service unit transmits a wake-up signal for changing a state of the user terminal from a sleep state into a wake-up state, a low frequency (LF) signal for identifying a physical distance and direction between the health or wellness service unit and the user terminal, and a measured biological signal of a measuring object. The user terminal receives the biological signal, the wake-up signal, and the LF signal through bidirectional wireless communication with the health or wellness service unit, and transmits a terminal identification (ID) and a received signal strength indication (RSSI) corresponding to the received LF signal.

The invention discloses a production method of ammonium phosphate containing trace elements. The production method is characterized by adopting a manner of dissolving by phosphoric acid and carrying out full ammonolysis reaction on oxides or salts containing trace elements in the ammonium phosphate production process, and specifically comprises the following steps: adding oxides or salts containing trace elements into an acidolysis tank; recovering a scrubbing solution, phosphoric acid and water from an ammonium phosphate scrubbing system and mixing and stirring; fully decomposing the oxides or salts containing trace elements to ions or complexes to form a phosphoric acid solution containing trace elements; conveying to an acid preparation tank of a tubular reactor by a feed pump; adding phosphoric acid, the scrubbing solution and process water to mix; quickly ammonifying in a tubular reactor and grouting and pelleting in a pelletizer; and then drying, sieving, cooling and wrapping to obtain an ammonium phosphate compound fertilizer containing trace elements. The ammonium phosphate compound fertilizer containing trace elements obtained by adopting the method has good solubility.

The invention relates to an emergency vehicle hybrid lane changing decision-making method based on reinforcement learning and avoidance strategies. The method comprises the following steps: determining an optimized road section and execution strategies of ICCV and ICEV to be planned; initializing a DQN network of the ICEV to be planned; obtaining a state space of the DQN network based on the stateinformation of the ICEV to be planned, the six neighbor vehicles of the ICEV to be planned and the avoidance strategy execution condition of the preceding vehicle of the ICEV; obtaining an output value based on the state space of the DQN, and obtaining a preliminary decision and an action space based on the output value; establishing an action selection barrier, and verifying and selecting the obtained preliminary decision until the action finally selected from the output value or the action space meets the traffic rule and the road physical structure; defining a reward function for calculating a total reward corresponding to the action; and training the DQN network to obtain a trained DQN network. The method can be widely applied to the field of road lane changing decision control.

The invention discloses a method for measuring an azimuth angle of a mobile communication base station antenna, and includes the steps of: performing a drive test on a cellular mobile communication network, and measuring radiation relative gain distribution information of a target base station antenna at each azimuth angle of an installation horizontal plane; based on the shape characteristics of a gain envelope line formed by the radiation relative gain distribution information, extracting main lobe distribution of the target base station antenna in a horizontal direction and a central ray angle; and obtaining the azimuth angle of the antenna according to the main lobe distribution information and the central ray angle. According to the method for measuring the azimuth angle of the mobile communication base station antenna, people do not need to purchase or install special hardware by climbing up to a tower, and can complete measurement only by utilizing drive test data of an existing drive test terminal and sweep generator, the cost is low, and engineering implementation is easy; and a calculation result is high in degree of accuracy and stability, and a requirement for optimizing work of the cellular mobile communication network can be satisfied.

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.