96results about How to "Accurate Data Base" patented technology

The invention discloses an original article influence analysis system based on collection of media information. The system comprises a media article data acquisition module, an update module for article page views, comments and likes, an original article clustering analysis module and an original article influence calculation module. The media article data acquisition module is used for acquiringarticle information issued by a media platform in the internet, extracting content text from article information and storing the content text. The update module for article page views, comments and likes is used for obtaining dissemination feedback data of the article information and storing the dissemination feedback data of the article information. The original article clustering analysis moduleis used for clustering all content texts stored in a text database in order to obtain original articles. The original article influence calculation module is used for calculating influence of the original articles in the media platform and used for calculating influence of the original articles in all media platforms. The invention further discloses an original article influence analysis method based on collection of media information. By quantitative analysis of original article influence, analysis efficiency is high and accuracy of analysis is great.

The present invention discloses a method and system of decoration project construction management based on the technology of internet of things. The decoration and fitment product data is standardized, the connection with a DPM management system is established, the site collection and the real-time monitoring are realized based on the technology of internet of things, the real-time monitoring comprises construction material storage/retrieval and usage condition monitoring, construction schedule track, construction quality monitoring and analysis, and site worker construction task completion condition monitoring and analysis, and the project dynamic construction cost track is realized. The technology of the internet of things, the two-dimensional barcode technology and the RFID technology are employed, a laser scanner and a wireless sensor are used, the information of people, materials and machines on the construction site is collected to a route device through the ZigBee protocol and is transmitted to a central information system through adoption of the internet to realize the real-time transmission and sharing of the information such as the decoration project cost, the schedule, the quality and the safety and solve the problem of the timeliness and the accuracy of the information collection of the DPM system.

The embodiment of the invention provides an evaluation method and a device for panoramic monitoring index of a distribution network. The evaluation method for panoramic monitoring index of the distribution network comprises the following steps: obtaining original monitoring data of the distribution network; Classifying that original monitor data according to the data type, and generating a plurality of monitoring data sets; Constructing panoramic monitoring index system of distribution network according to each monitoring data set; According to the panoramic monitoring index system of distribution network, evaluating each evaluation object of distribution network, and generating the comprehensive evaluation results. By implementing the invention, the panoramic monitoring index system of the distribution network is established to evaluate each evaluation object of the distribution network, thereby realizing the panoramic monitoring and evaluation function of the whole distribution network, and the obtained comprehensive evaluation result provides an accurate data basis for the planning and decision-making of the distribution network.

The invention discloses a high-frequency resonant soft switch circuit fault prediction method and a high-frequency resonant soft switch circuit fault prediction device based on compressed sensing. Characteristic parameters are sampled based on compressed sensing, generation of massive data is avoided, and the difficulty coefficient of data processing is reduced. Fault prediction is carried out on a high-frequency resonant soft switch based on chaos, the maximum Lipschitz exponent is calculated by taking current and historical recovery signals as a data basis, the maximum Lipschitz exponent is used to predict the fault of the high-frequency resonant soft switch, and the accuracy of fault prediction is improved. A multivariate time series is built based on the recovery signals of seven characteristic parameters, and the multivariate time series is of information completeness and can overcome the noise effect on the accuracy of fault prediction. The input signals of the characteristic parameters are sparsely transformed, an irrelevant linear measurement matrix is designed according to the sparse transform base, and during sampling of the characteristic parameters based on compressed sensing, the linear measurement matrix is used to linearly measure original signals to provide an accurate data basis for signal recovery.

The invention relates to a method for acquiring the airplane vertical occupancy rate. The method comprises the following steps: the acquired flight flow sample data is processed to obtain the data information of all flights; the position information of each way point of the flights on the flight line and the flight information of the flights to pass through each way point are extracted from the data information of each flight; two flights are compared in sequence according to the position information of the way point and the flight information of the flights to pass through each way point to determine the number of the flight pair with collision risk; and the vertical occupancy rate is determined according to the number of the flight pair with collision risk. The flight pair with collision risk does not depend on the individual empiric parameter value, and not adopt the direct statistical method for the complex parameter. Therefore, not only the accuracy of the calculated vertical occupancy rate is high, but also the use is simple and convenient, and the invention is convenient for engineering realization, is favorable for the quantitative description of busyness of the aerial traffic to realize, provides the accurate data basis for the airspace running analysis and the safety assessment, and has wide application prospect.

The invention discloses a mobile terminal-based lane deviation forewarning method and system, comprising: step S10, acquiring boundary line data of a lane which a vehicle is currently on; step S20, calculating an axis position of the lane, a forewarning line position and an axis position where the vehicle is currently located, according to the boundary line data and current body width of the vehicle; step S30, judging whether a distance between the axis position where the vehicle is currently located and the forewarning line position reaches a forewarning value or not, if yes, executing step S40, and if not, executing step S10; step S40, sending out driving path forewarning information.When a vehicle departs a lane and potential safety hazards are posed, a driver is reminded in time to adjust a driving path of the vehicle, thus avoiding traffic accidents.

The invention belongs to the technical field of computer vision, and provides an AGV space obstacle avoidance method based on 3D vision. The obstacle avoidance method comprises the steps: judging whether obstacle 3D point cloud information exists in the advancing direction of a preset track of the AGV or not within the preset distance threshold range of the current position of the AGV: if not, determining that the AGV operates normally, otherwise, enabling the AGV to enter an obstacle avoidance state; when the AGV enters an obstacle avoidance state, analyzing the shape, size and position of the obstacle based on the 3D point cloud information of the obstacle, and then calculating the speed of the obstacle in a global coordinate system according to the 3D point cloud information sampling period; obtaining the state of the obstacle based on a pre-trained support vector machine, and enabling the AGV to execute a temporary obstacle avoidance path matched with the current obstacle state from a preset obstacle avoidance execution position according to the shape, size and position of the obstacle. Obstacle avoidance precision and AGV stability can be improved.

The invention relates to a method for estimating the time variant failure rate of a relay protection device based on Rayleigh distribution. The method comprises the following steps that (1) failure data of the relay protection device are obtained and whether the obtained failure data are accidental failure data or aging failure data is judged; (2) when the failure mode is an accidental failure mode, the accidental failure rate is estimated through the estimating method of the constant failure rate; (3) when the failure mode is an aging failure mode, the aging failure rate is estimated through the estimating method of the time variant failure rate; (4) the overall time variant failure rate of the relay protection device is estimated, and the overall time variant failure rate satisfies the equation that lambda (t)=lambda 0 + lambda 1 (t). The time variant failure rate of the relay protection device is estimated through different methods according to different failure modes. The method for estimating the time variant failure rate of the relay protection device based on Rayleigh distribution can be widely used in failure rate estimation of relay protection devices.

The invention provides a lung lobe segmentation method and device based on a CT image, electronic equipment and a storage medium, and solves the problem of how to perform lung lobe segmentation. The lung lobe segmentation method comprises the following steps: extracting a group of lung region images from a CT image sequence; identifying a plurality of lung fissure key points in the group of lung region images by utilizing a first neural network model; and performing lung lobe segmentation on the group of lung region images according to the plurality of lung fissure key points to obtain a groupof lung lobe segmentation images.

The invention provides a method and a device for compensating for a harmonic voltage measurement error of a capacitor voltage transformer (CVT). The method comprises the following steps of (1) establishing a CVT equivalent circuit model, and specifically converting the used CVT into the corresponding equivalent circuit model; (2) calculating a transfer function, specifically based on the CVT equivalent circuit model, calculating an equivalent impedance value of each port step by step, then calculating the transfer function, and obtaining frequency characteristics; and (3) compensating for themeasurement error, specifically according to the CVT frequency characteristics, correspondingly compensating for the harmonic measurement result of the CVT. The invention further provides the device for compensating for the harmonic voltage measurement error of the capacitor voltage transformer (CVT), in order to implement the above method and export the monitoring data after compensation. By adopting the method and the device provided by the invention, the problem of large measurement errors of the CVT is solved, and the accuracy of harmonic voltage measurement of the CVT is improved.

The invention relates to the technical field of ice storage air conditioning, and particularly provides an air conditioning self-learning optimal control system. The air conditioning self-learning optimal control system aims to solve the technical problem of how to reduce the economic cost of using air conditioners by users. For the purpose, the air conditioning self-learning optimal control system is applicable to an ice storage air conditioner. The ice storage air conditioner includes an ice storage device, an air conditioner refrigerator and a cold quantity converter, wherein the ice storage device is connected with the cold quantity converter. The air conditioning self-learning optimal control system includes a cold load demand acquisition device for acquiring a cold load demand, an approximate optimal control strategy acquisition device for obtaining an approximate optimal control strategy, a local iterative judging device used for updating an optimal performance index value and the approximate optimal control strategy and a global iterative judging device for obtaining the optimal control strategy and calculating the user cost. Through the air conditioning self-learning optimal control system, the cold supply load can be balanced, the cold supply requirements of the users are met, and the economic cost for the users to use the air conditioners is saved.

The invention discloses an unmanned plane aerial photography image calibration method suitable for slope measurement. According to the method, firstly, an image calibration model is established; secondly, points are vertically acquired by an unmanned plane, slope map image data and calibration data are acquired, and a slope angle Slope and a slope image azimuth Azimuth are acquired through calculation according to the acquired data; whether a distance measurement module is available is determined, if yes, the distance measurement module is employed to measure the vertical distance Length; if not, calibration points are acquired to replace the vertical distance Length; according to the acquired vertical distance Length, a slope image scale SlopeScale, a geographic three-dimensional coordinate of an image origin Origin and a geographic three-dimensional coordinate of a target point are calculated, and calibration is accomplished. The method is advantaged in that the unmanned plane measurement calibration technology is made not to be limited to the plane, scientific basis is further provided for slope measurement and projection measurement demands, effective guarantee is provided foraccurate measurement, rapid and easy calibration is realized, and slope image calibration accuracy and calibration efficiency are improved.

The invention discloses a shelf commodity display information identification method, device and equipment and a storage medium, and the identification method comprises the steps: extracting the angle information of shelf commodities from a target image, correcting the target image based on the angle information of the shelf commodities, and obtaining a corrected image; and carrying out shelf commodity information identification according to the corrected image to obtain commodity display information in the target image. According to the method, the target image is corrected to obtain the corrected image at the standard angle, so that the influence of different shelf postures on the commodity display recognition accuracy can be avoided; and meanwhile, accurate identification of image commodity display information is realized according to the corrected image, and an accurate data basis can be provided for subsequent intelligent distribution display recommendation.

The invention discloses an actual pupil distance measuring method, device and equipment based on a monocular camera. According to the concept, a plurality of reference points and a monocular camera are preset, specific imaging parameters are extracted from a plurality of images when a driver gazes at each reference point, camera parameters and reference point position parameters are then combined,the actual distance between the midpoint of two pupils of the driver and the camera is obtained, a pupil distance value corresponding to each image is solved based on the actual distance and each parameter, all pupil distance values based on a plurality of reference points and a plurality of images are obtained in the way, and finally rigid body parameters, namely real pupil distance characteristic information of the driver, of the driver individual is calibrated and saved through a preset pupil distance standard and all the pupil distance values. High-precision pupil distance information ofa driver individual can be obtained based on a low-cost monocular camera, and a reliable and accurate data basis is provided for subsequent human eye positioning operation.

The invention discloses an extended target tracking method based on an automobile radar. The method comprises the following steps: establishing a random finite set model of an actual target automobileaccording to a state set; establishing a random finite set model of a measurement target automobile according to the measurement set; correcting abnormal Doppler velocities; after azimuth-Doppler velocity pre-partitioning processing, using Gibbs sampling for data association; under the condition of successful association, updating the posterior density of multi-target PMBM; predicting the multi-target PMBM prior density at the next moment; determining whether a new target enters under the condition of unsuccessful association, predicting the multi-target PMBM priori density of the new targetat the next moment; calculating an output result by combining a complete state vector; otherwise, removing the clutter. Therefore, the tracking efficiency and the tracking precision are substantiallyimproved by increasing a small amount of time complexity.

The invention discloses an urban municipal road operation safety monitoring method based on big data analysis and cloud computing and a cloud monitoring platform. The urban municipal road operation safety monitoring method based on big data analysis and cloud computing comprises the steps: counting the number of water accumulation areas corresponding to an urban road; acquiring basic information corresponding to each ponding area of the road; collecting the accumulated water depth corresponding to each accumulated water area of the road; obtaining the rainfall of the city in each time period; collecting road information corresponding to each ponding area of the road; collecting information corresponding to each water outlet of the road; and analyzing and processing the acquired information of the road. Through detailed detection and analysis of the basic information, the water level, the rainfall information, the road information and the drainage port information of the road ponding area, the problem that the drainage efficiency of the ponding area cannot be effectively improved by an existing urban municipal road ponding safety monitoring method is solved.

The invention discloses a data automatic collection method and apparatus. The method comprises the steps of providing a data collection interface, and establishing a communication connection with an antibiotic detection instrument selected in the data collection interface by detection personnel; after the detection personnel select a general detection option in the data collection interface, obtaining identifier information of a to-be-detected sample; receiving a detection item selected in the data collection interface by the detection personnel; obtaining a detection item value of the to-be-detected sample for the detection item from the antibiotic detection instrument; and controlling the detection item of the to-be-detected sample and the corresponding detection item value to be displayed in the data collection interface. According to the method, automatic collection of antibiotic detection data is realized, and detection data of an electronic balance does not need to be manually recorded, so that the manual recording errors are avoided, the manual operation is reduced, the working efficiency is improved, an accurate data basis is provided for subsequent results, and the accuracy of the subsequent results can be improved.

The invention relates to an ultra-high speed flight model front light and shadow imaging device. A time sequence controller of the imaging device is used for triggering the light emitting of a light source and the starting of all the cameras according to the time sequence, and all the cameras are started synchronously. Pulse laser beams generated by the light source are coupled and output throughoptical fibers, are collimated by a first collimating lens and then irradiated to a flight model in a test area. The collimated light beams passing through the flight model are converged through a second collimating lens, and a shadow camera is arranged at the position of 1 cm to 10 cm away from the focal point of the second collimating lens. The imaging main axis of the first front light camera and the imaging main axis of the second front light camera are arranged in a mirror symmetry mode, and the first and second front light cameras are used for imaging the illumination surface of the flight model. The device is used for simultaneously obtaining the front light image and the shadow image of a flight model.

The invention provides a three-dimensional environment online monitoring system and method based on LoRa. The three-dimensional environment online monitoring system based on LoRa comprises: a data acquisition layer which comprises a plurality of LoRa acquisition nodes, wherein the LoRa acquisition nodes are preset at pre-segmented grid positions in a to-be-monitored environment, and each LoRa acquisition node sends the acquired environment information and the current geographic position information to a data management layer; a data management layer which comprises a LoRa gateway and a server,wherein the LoRa gateway is used for receiving data transmitted by each LoRa acquisition node and transmitting the data to the server, and the server is used for matching the current environment information at each geographic position with the corresponding historical information to predict environment change early warning information and determining standard-exceeding pollutants and the moving speed and direction of the standard-exceeding pollutants according to the change of the environmental information at all geographic positions at each time point; and a UI interface layer which is usedfor displaying the environmental change early warning information, the standard-exceeding pollutants and the moving speed and direction information of the standard-exceeding pollutants.