56results about How to "Make up for inaccuracies" patented technology

An embodiment of the invention provides an action assessment system. The system comprises at least one visual sensor, a wireless action capture unit and an assessment device, wherein the at least one visual sensor is used for receiving a collection instruction, collecting position information of a preset target joint at a specified position point and sending the collected position information to the assessment device; the wireless action capture unit is used for receiving the collection instruction, collecting motion information of a preset limb part and sending the motion information to the assessment device; and the assessment device is used for sending the collection instruction to each visual sensor and each wireless action capture unit every a preset time period, receiving and fusing the position information and the motion information to obtain pose information, and comparing the obtained pose information with pose information in a standard action information frame to obtain a comparison result. By applying the technical scheme provided by the system, the accuracy of the comparison result is improved.

The invention provides a front end interface code generation method, and belongs to the technical field of computers. The problem that in the prior art, a front end interface code generation method islow in accuracy is solved. The method comprises the steps that front end interface design data is exported from a front end interface design layout, information collection and conversion treatment are performed on the front end interface design data, control information included in the front end interface is determined, and on the basis of input configuration information and the control information, front end interface codes are generated. According to the method, the control information in the front end interface is exported on the basis of the design layout, the front end interface codes are automatically generated according to the exported control information and configuration information, the interface design information in the design layout is sufficiently reserved, the defect that generated interface codes are not accurate due to the fact that obtained interface information is not sufficient when interface codes are directly generated from screenshots is overcome, and the accuracy of the automatically generated front end interface codes is effectively improved.

The invention relates to a rapid collective Kalman filtering assimilating method for real-time data of high-frequency observation data. The method comprises: collecting the high-frequency observation data and controlling the quality; calculating an observation error covariance matrix; obtaining the error covariance matrix of background fields by calculating a forecast trend, i.e. the difference value of the adjacent background fields; utilizing the covariance matrix, the error covariance matrix of the background fields, the observation data and the background fields currently obtained by the calculation of a marine numerical model so as to carry out the real-time assimilation on the observation data of different moments, assigning the updated analysis field to the initial field of the next-moment integral and continuously forecasting forwards; and repeating the operations, thus realizing the real-time assimilation on the high-frequency observation data of different moments in the integral course. The assimilating method has the advantages that the real-time assimilation of the high-frequency observation data is realized; the assimilation efficiency of the data is enhanced; the defect that a large amount of collective models are simultaneously operated in the implementation course of the traditional EnKF (ensemble kalman filter) is overcome; the problem of non-convergence is avoided; and the purposes of accurate numerical simulation and marine forecasting are reached.

The invention provides a local cabin section model for a ship impact resistance test, which is a box body formed by a dual-layer bottom compartment, a ballast compartment and a buoyancy reserve compartment. The shape of the cross section of the box body is as same as the shape of an area with length being 5-7 times of frame space along the length direction of a ship to be tested, width being halfof the width of the ship along the width direction of the ship and height being above 3-5m from the bottom of the ship up to the inner bottom along a vertical direction. The dual-layer bottom compartment is arranged at the bottom. The buoyancy reserve compartment is arranged right above the dual-layer bottom compartment. The ballast compartment consists of two independent watertight compartments,which are respectively arranged at the front and the rear of the dual-layer bottom compartment and the buoyancy reserve compartment. By designing a 1:1 actual-size typical cabin section model to carry out relevant impact resistance tests to research the local strength of a ship structure, the inaccuracy caused by a too simplified structure during a local grillage model test can be effectively remedied, the defects of high expense, difficult implementation and the like of a real ship test can be avoided and the problem that a scale model test is difficult to be converted into a similar test ofa real ship can be solved at the same time.

The present invention discloses a film recommending method based on visual features. The method comprises: predicating predication scores of films without scoring through users to be recommended through adoption of a film predication model built in advance according to the feature factors of the users to be recommended, the feature factors of the films without scoring, the similarity coefficient between the films without scoring and other films and the visual features of the films without scoring extracted in advance and the weight of each feature in the visual features, wherein the visual features includes a color histogram, SIFT features, CNN features and film category features; and determining whether the films without scoring are recommended to the users to be recommended or not according to the predication scores. The present invention further discloses a film recommending system based on the visual features. According to the embodiment of the invention, the accuracy of film recommending can be improved, and the user experience can be enhanced.

The invention discloses a detection method for braking force of an elevator tractor based on big data. The detection method comprises the steps that an elevator operates for preheating; an elevator car stops at a secondary top floor; a brake is power off and holds a traction wheel; a frequency converter drives the tractor to operate under the condition that a contracting brake is not opened; the output power of the frequency converter is monitored; whether the tractor rotates or not is judged through an encoder; when the output power of the frequency converter does not reach Pmax, the encoder senses the moment when the tractor starts to rotate, the power value at the moment is recorded, and the power value is uploaded through the internet; the horizontal comparison is carried out; the longitudinal comparison is carried out; and the elevator continuously operates or the elevator stops for maintenance. The detection method has the beneficial effects that driving power of the frequency converter is an objective value for reflecting the performance of the tractor, and through the methods that the traction wheel is braked through the brake and the frequency converter drives the traction wheel to operate under the condition that the contracting brake is not opened, the driving power of the frequency converter describes and evaluates the braking force more objectively with the assistance of big data of the elevator, so that the defect that a critical value or a threshold value is required to be manually set is broken through, and an evaluation result has more engineering signification.

The invention relates to a secondary shear experimental method for measuring performance parameters of oil displacing polymer solutions. The secondary shear experimental method comprises the following steps: (1) preparing an experimental polymer solution I which refers to a mixed solution of oil field water and polymer dry powder in any ratio; (2) performing primary shearing on the polymer solution I by use of a Wuyin stirrer to obtain a polymer solution II after the primary shearing, and measuring the viscosity, the condensate size, the microstructure, the rheological property, the resistance coefficient, the residual resistance coefficient and the oil displacement effect of the polymer solution II; and (3) performing secondary shearing by use of a core shearing polymer solution II to obtain a polymer solution III after the secondary shearing, and measuring the viscosity, the condensate size, the microstructure, the rheological property, the resistance coefficient, the residual resistance coefficient and the oil displacement effect of the polymer solution III. The secondary shear experimental method is capable of measuring the performance parameters of the polymer solutions in the actual reservoir really and actually.

The invention discloses a dampening control method of an overwater plane and setting of the dampening control device. The method comprises the following steps that: a wireless height meter continuously acquires height information of water levels and calculates average water level information; water wave feature parameters are calculated through a calculation module, thus obtaining basic features of wind waves, surges and nearshore waves; and basic wave features are provided for flight personnel through a display device so as to facilitate the selection of the flight personnel. The dampening control method can overcome the defect that information is not accurate and insufficient through visual observation, relieve the mental burden of the flight personnel, improve the availability of the aircraft, especially improve the availability of the flight in early morning, in the dark and severe weather as well as at night, improve the safety of necessary dampening when the aircraft has an accident, strengthen the all-weather capability of the aircraft, and enhance the driving comfort of the aircraft.

The invention discloses a clear-air channel detection quality control method suitable for assimilation of geostationary satellite data, and the method comprises the following steps of (1) pre-processing the observed radiant brightness temperature and simulated brightness temperature of the geostationary satellite AHI imager data; (2) establishing a minimum residual algorithm to estimate cloud toppressure and cloud proportion of AHI observation pixels; (3) establishing a cloud criterion algorithm to identify cloud types and evaluate cloud pixels; and (4) forming a coupling scheme by the minimum residual algorithm in the step (2) and the cloud criterion algorithm in the step (3), and establishing a dual cloud detection scheme. The method of the invention improves the data quality control level of the infrared channel of the stationary satellite imager, and improves the numerical model prediction level by improving the satellite data assimilation analysis.

The invention discloses an information processing method and apparatus for implementing loan approval, and a computer readable storage medium. The information processing method for implementing loan approval includes the steps: obtaining a credit survey result and a credit score, wherein the credit survey result is a credit survey class in credit survey class distribution; locating an interval inwhich the credit score is located to obtain a mapped credit score class, wherein the credit score class distribution matches the credit survey class distribution, and the two have the same loan risk increase and decrease mapping relationship; according to a credit score dependency, fusing the credit score class and the credit survey result to generate a loan processing class; and executing operation actions matching the loan processing class to complete loan approval. The information processing method for implementing loan approval ensures the automation degree of loan approval, can improve the processing efficiency and quickly complete loan approval, and under the cooperation of the credit survey result and implementation of fusion of the credit score class and the credit survey result, compensates inaccuracy of the credit score, because of the lack of samples, thus effectively improving the accuracy of loan approval.

The invention discloses a geomagnetic model online approximation method based on a Legendre polynomial and a BP neural network. The method includes the following steps that: 1, position information and aircraft navigation error which are indicated by a current integrated navigation system, and the measured value of a geomagnetic sensor are read; 2, a Legendre polynomial model is established according to a priori geomagnetic map; 3, a BP neural network is constructed, with the position information and aircraft navigation error adopted as input, the difference value of the measured value of thegeomagnetic sensor and the read value of the Legendre polynomial adopted as output, the constructed BP neural network is trained, so that the expression of input and output can be obtained, and geomagnetic model error at the current moment is obtained according to the read position information and aircraft navigation error; and 4, the geomagnetic value of the geomagnetic model at the current position at the current moment is corrected. The method is applicable to the measurement modeling of a regional geomagnetic assisted inertial navigation system and can realize the online approximationof the geomagnetic model, improve the accuracy of the geomagnetic model, and improve the positioning accuracy of the integrated navigation system.

The invention provides an autonomous charging system comprising: a charging pile 1, a guide post on the charging pile; a first charging module, a first relay, a first communication module; a second charging module, a second relay, and a second communication module. The first communication module and the first relay are arranged on the side of the guide post. The second charging module, the second communication module, and the second relay are arranged on the side of a guide block. The first communication module is in communication correspondence to the second communication module. The first charging module is in circuit correspondence to the second charging module. A robot base is provided with two guide blocks at intervals between which a guide groove is formed. The guide groove match the guide post in shape. The autonomous charging system can overcome errors caused by angle and position deviation during the charging and docking of a robot so as to guarantee that the robot can be successfully docked with the charging pile and that the charging pile is not in an alive state in the case of unreliable contact, thereby ensuring charging safety.

The invention discloses a water quality mechanism modeling and water quality prediction method based on a fruit fly optimization algorithm, belonging to the technical field of environmental engineering. At first, the invention combines the water quality evolution mechanism, and proposes a lake reservoir water quality mechanism modeling and water quality prediction method based on a fruit fly optimization algorithm. Based on the known water quality measurement data, the unknown parameters of the water quality mechanism model are estimated by using Drosophila optimization algorithm. On this basis, the water quality evolution process is predicted by Monte Carlo simulation, and the probability distribution of water quality indexes in the future is obtained, and the water quality prediction isrealized. The invention can establish an accurate water quality mechanism model, and the water quality mechanism modeling method based on the drosophila optimization algorithm can accurately estimateunknown parameters of the water quality mechanism model, which improves the optimization accuracy and speed compared with the prior method; water quality prediction method can effectively realize water quality prediction, and consider more comprehensive, accurate, and overcome the contingency of single-value prediction results.

The invention relates to the technical field of automatic driving, and in particular relates to a driving track prediction method and device and an automatic driving vehicle. The method comprises the following steps: acquiring driving characteristic information of a target vehicle; the driving characteristic information comprising a position, a vehicle speed and a steering angle; the steering angle being a wheel steering angle or a steering wheel steering angle; and predicting the driving track of the target vehicle according to the driving characteristic information. According to the embodiment of the invention, the future driving track of the target vehicle is predicted by utilizing the steering angle (such as the wheel steering angle or the steering wheel steering angle) of the target vehicle, and the steering angle of the target vehicle can reflect the steering intention of the target vehicle more accurately than the vehicle course angle used in the prior art; the accuracy of predicting the driving track of the target vehicle can be improved, so that whether the vehicle collides with the target vehicle or not can be judged more accurately according to the predicted driving track, the situation that the driving vehicle decelerates improperly is relieved, and the riding experience of passengers is improved.

The invention relates to a multimedia resource pushing method and device, a server and a storage medium, and belongs to the technical field of the Internet. The method comprises the steps that in response to the fact that the length of a search term exceeds a target length, determining the similarity between multiple multimedia resources and the search term; determining mark features of the plurality of multimedia resources according to the similarity between the plurality of multimedia resources and the search term; determining a pushing sequence of the plurality of multimedia resources underthe search term according to the search term and the plurality of multimedia resources added with the mark features; and pushing according to the pushing sequence of the plurality of multimedia resources. According to the invention, when the length of the search term exceeds the target length, the marking features of the multimedia resources are determined according to the search terms, and the marking features can represent the correlation between the multimedia resources and the search terms, so that the pushing sequence of the multimedia resources determined on the basis of the marking features can solve the problem of inaccuracy caused by less interaction data with the user, and the accuracy of the pushed multimedia resources is improved.

The invention discloses a robot chassis for paddy field multifunctional operation and an agricultural robot, the robot chassis comprises a walking device, a profiling device and a control system, and the control system is connected with the walking device and the profiling device; the profiling device comprises a parallel four-bar mechanism, an electric push rod, a profiling module and a suspension mechanism, the parallel four-bar mechanism is installed in the middle of the walking device, the profiling module and the suspension mechanism are installed on the parallel four-bar mechanism, and the suspension mechanism is used for installing an operation machine tool; when the electric push rod is located at the shortest position, the parallel four-bar mechanism is lifted to enable the operation machine tool to keep a certain height from the ground, when the electric push rod is located at the extension position, the parallel four-bar mechanism is put down to enable the operation machine tool to make contact with the ground and operate, and the profiling module detects fluctuation of the ground in real time and feeds back the fluctuation to the electric push rod for telescopic adjustment. Therefore, the profiling device plays a role in profiling. According to the robot chassis, the intelligent level of an agricultural robot is improved.

The invention relates to a method for determining a current position (5) of a motor vehicle (6) in a geodetic coordinate system from a time series of first geodetic position data (2), in particular recorded by means of a position sensor (8) associated with a global navigation satellite system, and of ego-motion data (3) recorded by means of at least one ego-motion sensor (9), wherein the position is determined by applying a transformation into the geodetic coordinate systemonto a displacement vector of the motor vehicle (6) derived from the latest of the ego-motion data (3) starting from a reference time to which the transformation relates, wherein the transformation is determined in a regression analysis as an optimal mapping of a progression of displacement vectors determined over a defined time period to a progression of the position data (2) determined for the same time period.

The invention provides a distance measuring method based on a monocular camera and a laser radar. The distance measuring method comprises the following steps: firstly, collecting historical traffic scene image data and point cloud data; processing the data, and respectively training an initial target detection model and an initial depth completion model by using the processed historical image data and historical point cloud data; obtaining a trained target detection model and a depth completion model, wherein the target detection model takes real-time image data as input and outputs information of obstacles in the traffic scene, the depth completion model takes the real-time image data and the real-time sparse depth map as input, outputs a dense depth map; and finally calculating the distance of an obstacle in the traffic scene according to the output of the target detection model and the depth completion model. The advantages of the monocular camera and the laser radar are fully combined, the output results of the target detection model and the depth completion model are fused, object-level distance measurement is realized, the result is reliable, and the precision is high.

The invention discloses a process early warning method and system for analysis and estimation of a full measurement point coupling structure. The invention provides a full-measurement-point synchronous estimation and monitoring model based on analysis of a coupling structure between measurement points and measurement point estimation errors, and aims to solve the problems that an original monitoring method based on working condition estimation is incomplete in monitoring and insufficient in modeling of a coupling relation between the measurement points. On the basis that full measurement points are regarded as a full measurement point diagram, a multi-kernel graph convolutional layer is provided and applied to a full measurement point synchronous estimation and early warning model, and synchronous working condition estimation and monitoring of full sensor measurement points are achieved by explicitly modeling the coupling relation between the measurement points. According to the method, a self-iteration strategy based on feature approximation is designed for the provided model, so that the problem that estimation values of part of measuring points are abnormal due to strong coupling between the measuring points when a system is abnormal in a traditional method is solved, and the method has important significance on accurate monitoring of the industrial process.

The invention discloses a system and a method for predicting the insulator surface non-soluble deposit density. The system comprises an original data acquisition unit, a series gray neural network prediction unit, a parallel gray neural network prediction unit, an embedded gray neural network prediction unit, a NSDD (Non Soluble Deposit Density) predicted value output unit and an NSDD early warning unit. Insulator surface non-soluble deposit density data and local meteorological data are inputted into the series gray neural network prediction unit, the parallel gray neural network prediction unit and the embedded gray neural network prediction unit, and prediction is performed on an insulator NSDD value through the three prediction units; then judgment is performed on the prediction accuracy of the three prediction unit by using a test sample, output of the prediction unit with high prediction accuracy is enabled to act as an insulator NSDD predicted value; and an early warning is given out through the NSDD early warning unit according to whether predicted values outputted by two or more of the prediction units reach a preset graded early warning threshold or not.

The invention relates to an automobile safety reminding device. The safety reminding device includes a warning device, laser rangefinders and a computer chip; the three laser rangefinders are arrangedon the two sides of the head of an automobile and the center of the head of the automobile respectively; laser sent by the laser rangefinders is parallel to the forwarding direction of an automobilebody; the laser rangefinders measure the distance between the head of the automobile and a barrier on the front every a seconds; the computer chip is used for recording the transmission distance of each laser rangefinder respectively, the computer chip processes the distance values every b seconds to obtain time values, and the time is output on a display screen. When the output time exceeds the safety range, the computer chip is communicated with the warning device so as to remind a driver. The reminding device is small in structure and unique in principle, can timely remind the driver of thedriving situation of vehicles in front of the driver, effectively avoids the occurrence of rear-end collision, reduces traffic accidents, and ensures safe and smooth driving on a highway.