42 results about "Point correlation" patented technology

The invention discloses a personalized test question recommendation method based on user learning behavior, the method is as follows: obtaining user history problem data, test questions and knowledgepoint information from an online education platform; constructing a user based on user history data data; R, according to the relationship between the test questions and the knowledge points, constructing the test questions-Knowledge point correlation matrix Q; constructing the user cognitive diagnosis model through the DINA model, obtaining the user knowledge point mastering matrix A; obtainingthe user adjacent test set according to the matrix A, according to Matrix Q the test questions-Adjacent test sets, constructing alternative test sets; non-negative matrix decomposition of matrix R, obtaining the implicit feature matrices W and H of users and test questions, find the estimated values of W and H matrices, and get the score prediction Model; calculating the potential answering situation of the user, and recommending the test questions of the target user's own difficulty range to the target user. The invention can accurately recommend the test questions suitable for the target user to the user. The invention is applicable to the field of online education.

The invention discloses a method for continuous tracking association of radar detection equipment to moving and stationary targets. The method for continuous tracking association of the radar detection equipment to the moving and stationary targets includes the following steps that trace point information parameters of the multiple moving targets are obtained; point trace information that the corresponding parameter difference value is less than a preset threshold is filtered and defined as similar trace point information; according to the trace point information parameters, similar trace points are fused; according to information of the velocity, the acceleration and the turning rate in the trace point information parameters, the fact that the detected trace point information is correlated or excluded is judged; the obtained at least two trace point information are correlated; a prediction region according to the correlated trace point information is created, and the prediction regionis a region range which is formed before a trace point and predicts the next position where the trace point occurs; and in the prediction region of the trace point, continuous scanning acquisition ofthe trace point is carried out. According to the method for continuous tracking association of the radar detection equipment to the moving and stationary targets, through trace point fusion, trace point correlation and other methods, the corresponding trace point information of the moving targets are identified accurately, and the handling capacity of system data is reduced.

The invention discloses a serialized student cognition diagnosis method. The method comprises the steps of obtaining historical question-answering information of multiple students; performing modeling by using a serialized cognition diagnosis method according to the obtained historical question-answering information, and obtaining ability vectors and a test question-knowledge point correlation matrix subjected to partial order limitation; and predicting an ability value and a score of a student in the next time period according to the ability vectors and the test question-knowledge point correlation matrix subjected to the partial order limitation. According to the method, by performing continuous and long-time analysis processing on test question information and question-answering conditions of the students, the overall ability levels and knowledge mastery degrees of the students in different time periods can be accurately analyzed.

The invention relates to a time frequency mask-based single acoustic vector sensor (AVS) target voice enhancement method. According to the method, the arrival angle of the target voice is known, a method of combining a fixed beam former and a post-positioned Wiener filter is adopted for realizing target voice enhancement, and calculation of the weight value of the post-positioned Wiener filter involves self-power spectrum estimation of the target voice. Time frequency sparse characteristics of a voice signal are used, the time frequency point correlation arrival angle for receiving audio signals is estimated through calculating the ISDR (Inter-sensor data ratio) of component signals outputted by two gradient sensors in the AVS, time frequency mask is designed through calculating errors between the time frequency point correlation arrival angle and a target arrival angle, and thus self-power spectrum estimation of the target voice is acquired. According to the method of the invention, any noise prior knowledge does not needed, the target voice can be effectively enhanced in a complicated environment where multiple speakers exist, and interference voice can background noise can be suppressed. In addition, the operation complexity is low, the adopted microphone array size is small (about 1cm<3>), and application on a portable device is excessively facilitated.

Devices, methods, and programs correct an estimated path found by dead reckoning navigation. A point correlation value s is calculated based on a distance to a reliability circle whose radius is a speculative maximum error e that indicates a distance of an error range with respect to a GPS position. A correlation value Sp of an estimated path and a correlation value Sq of a candidate path are calculated from cumulative values of the point correlation values s. A correction that moves the estimated path is not performed if the correlation value Sq of the candidate path becomes worse than the correlation value Sp of the estimated path, and the correction of the estimated path is performed if the correlation value Sq of the candidate path does not become worse than the correlation value Sp of the estimated path. Thus, false matching can be further reduced, and the travel path can be suitably corrected.

The invention discloses a monocular vision mileage calculating device. The monocular vision mileage calculating device comprises a feature detection and correlation module 1 and a pose estimation module 2, wherein the feature detection and correlation module 1 is used for detecting GFtT feature points at each moment when a new image is obtained, and tracking positions of the GFtT feature points in the image at the next moment so as to obtain a GFtT feature point correlation set in a certain time and outputting the GFtT feature point correlation set to the pose estimation module; the pose estimation module 2 is used for modeling by a pose estimation algorithm based on constraint of a vehicle dynamic model according to the GFtT feature point correlation set output by the feature detection and correlation module so as to obtain a relative pose transformation between adjacent moments. The monocular vision mileage calculating device has relatively high efficiency and accuracy, can meet real-time positioning and navigation requirements of an intelligent vehicle, can be used in a complex environment with a large quantity of movement obstacles, is free of assumed limit in static scenes and is capable of meeting the use requirements of an intelligent vehicle in a complex urban road environment.

The invention discloses a vision correlation model progressive rendering method on a three-dimensional scene. The main concept is that a vision correlation factor is calculated according to the distance from a view point to a target, LOD rendering is carried out on geometric data and texture data of a model, the rendering process of the model is controlled through an synchronization strategy and a view point correlation sorting algorithm, and therefore the problems that an existing large-scale three-dimensional model is low in rendering speed, occupies too many system resources such as the inner memory and video memory, has too many rendering areas, is unsmooth in rendering, has the phenomenon of visual mutation, is low in efficiency and the like are resolved.

The invention relates to a multi-characteristic information fusion method for target data correlation and belongs to the technical field of radar data processing. The method comprises the following steps: 1) trace point pretreatment: screening data and storing the screened data according to frame; 2) target classification: classifying targets into three classes according to target speeds; 3) point-point correlation: carrying out track initiation by utilizing an m / n logical approach, and adopting different correlation strategies for different types of targets; 4) point-track correlation: carrying out extrapolation on a target track, and searching target candidate echoes according to a Bayesian data correlation algorithm; 5) feature similarity computation: extracting feature information of the candidate echoes and calculating feature similarity; and 6) comprehensive correlation degree computation: calculating comprehensive correlation degree according to the feature similarity and feature weight, and selecting the candidate echo, the comprehensive correlation degree of which is the largest, as target measurement. The method can reduce the number of the target candidate echoes, reduces operation burden, improves reliability of data correlation under a dense clutter background, and has a popularization and application value.

The invention provides a method for solving location ambiguity of high-repetition frequency signals through the utilization of the consistency of trace modulation of radial deflection of a moving radiation source target and the arrival time of pulses. Through the method, false locating points of a high-repetition frequency target can be well distinguished, and solving time different ambiguity on the target can be achieved in a short time. A specific achievement frame is designed according to the consistency of the trace modulation of the radial deflection and the arrival time of the pulses to complete several key steps of pretreatment of deblurring treatment, trace point correlation, radial deflection amount calculation, and location deblurring. On the condition that the time determination error is smaller than 30ns, as long as the target has a certain radial speed, false locating tracks caused by wrong high-repetition frequency pulse pairing can be distinguished, and the computation time complexity is small.

The invention discloses a co-occurrence correlation function-based porous medium three-dimensional modeling method. According to the method, a new correlation function is designed to be adopted as a constraint function in reconstruction to replace an original two-point probability function in a porous medium three-dimensional modeling process; and a simulated annealing algorithm framework is used in combination, so that a corresponding fast update algorithm is designed; and therefore, three-dimensional reconstruction is performed. The co-occurrence correlation function-based porous medium three-dimensional modeling method is characterized in that the concept of the co-occurrence correlation function and a porous medium three-dimensional modeling algorithm with the co-occurrence correlation function adopted as an objective function are provided; as for the problem that whenever points are exchanged, the co-occurrence correlation function of a whole structure is required to be calculated again can be solved, and the corresponding fast update algorithm is provided, and therefore, reconstruction speed is increased; and the co-occurrence correlation function is adopted as a constraint condition, and therefore, the co-occurrence correlation function-based porous medium three-dimensional modeling method has the advantages of more accurate reconstruction result, no obvious increased in time and high application value compared with a traditional two-point correlation function.

The invention belongs to the field of natural language processing research, and discloses a title selection method and system of a read robot. The title selection method includes the following steps:1, a chapter main point extraction unit; 2, a title and chapter main point correlation analysis unit; 3, a title structure unit; 4, a relevancy matrix and title structure fusion unit; and 5, an answerselection unit for sorting options and selecting a suitable answer. The title selection method provides a tile and chapter main point correlation analysis method firstly, can construct a title and chapter main point based relevancy matrix by analyzing the relevancy between a title and a chapter main point, and is integrated with a title structure feature on the basis, and can select a title mostrelevant with a chapter. The method complies with a solution law, can solve the problem of title selection and question answering of the read robot, and can effectively fill in the gap of intelligentanswering of Chinese reading comprehension title selection questions.

The invention provides a non-cooperative target positioning method aiming to solve the problem that the conventional positioning method is sensitive to group path errors of echo signals and instable in performance. The method includes the following steps: forming a synchronous data transfer chain between a receiving station and a transmitting station through a signal synchronization network in time domain, frequency domain and space domain; detecting non-cooperative target scattering information with a receiver by a multi-base positioning system to obtain a group path of a target echo signal, and making a distance information based irrational equation set simultaneous; all the bases transmitting measured target data to a central processing unit through a data transfer chain network, performing trace point correlation, positioning and track processing, and determining a target solving function; if a Tth coordinate information group in a coordinate range satisfies target function conditions, the central processing unit solving position coordinates of a non-cooperative target with the non-cooperative target positioning method so as to finish positioning of the non-cooperative target, and outputting the coordinates of the non-cooperative target.

The invention discloses a compression method and a decompression method of a handwritten terminal track, belonging to the field of image compression. The method for compressing the trajectory of the handwriting terminal includes: calculating the coordinate difference between the actual coordinates of each trajectory point and the predicted coordinates of the point; performing entropy encoding on the coordinate difference to obtain a code word to complete the compression of each trajectory. The decompression method of the trajectory of the handwriting terminal includes: performing entropy decoding on the saved codewords to obtain the coordinate difference between the actual coordinates of each trajectory point and the predicted coordinates of the point; obtaining the predicted coordinates of each trajectory point according to the predicted tap coefficient; The coordinate difference between the predicted coordinates and the actual coordinates of the point and the predicted coordinates of the point is used to obtain the actual coordinates of each track point. In the present invention, the correlation of the coordinates of the track points is utilized when compressing and encoding the track, which overcomes the disadvantage of large storage space caused by uniformly adopting fixed-length encoding to encode the track in the prior art.

The invention provides an audio guide display system and method. Audio guide display data are accurately acquired through a Bluetooth base station, due to Bluetooth transmission, data can be transmitted with low power consumption, and the service cycle of the system is prolonged; besides, explanation points of the audio guide display data are searched for, previous content and later content of the explanation points are correlated, and explanation point correlation bodies based on semantics are established and combined in a digitalized mode and then pushed to a user. On the one hand, due to the optimization of the data structure, data can be conveniently pushed to the user orderly and efficiently; on the other hand, due to the digitalized combination, picture data, text data and video data are perfectly combined to be displayed to the user so that the user can obtain information of the current place in terms of many aspects from multiple angles; besides, a photo album generation module is further arranged, when the user finishes visiting the current place and needs to take photos, multiple photos can be taken according to a preset frequency and made into a photo album, and thus the multi-dimensional audio guide requirements of the user are met, and good user experience can be achieved.

The invention discloses a gas turbine combustion system online monitoring method based on an exhaust temperature measuring point correlation. The invention relates to the gas turbine combustion system online monitoring method. The invention mainly aims at solving a problem that early warning for a combustion system cannot realized in the prior art, and discloses the gas turbine combustion system online monitoring method based on the exhaust temperature measuring point correlation. The method comprises following steps: 1, achieving the temperature of n temperature measuring points at the time t; 2, obtaining a-hat and b-hat according to the temperature of the n temperature measuring points at the time t; 3, determining the [Ti]'-hat according to the a-hat and the b-hat obtained in the step 2; 4, defining the relation coefficient [alpha]i according to a formula that [alpha]i = [Ti]'-hat / T-hat; 5, setting the range of the [alpha]i being [[alpha]i1, [alpha]i2]; and 6, drawing dots with the upper limit [alpha]i1, the lower limit [alpha]i2 and the [alpha]i being polar radiuses and with (2[pi]*i) / n being the polar angle in polar coordinates, sequentially connecting the dots drawn from i=1 to i=n by straight lines, and connecting the dot drawn when i=1 and the dot drawn when i=n by a straight line, so that an enclosed polygon is obtained. If the range of the polar radius [alpha]i is [[alpha]i1, [alpha]i2], a gas turbine is in a normal operation state. The monitoring method is applicable to the field of gas turbine combustion system online monitoring.

The invention relates to an optimization method for a measuring point of a measuring sensor for a satellite angular rate based on a correlation matrix. The optimization method comprises the following steps: (1) dividing function modules for the measuring sensor for the angular rate, establishing a signal flow graph for each of the function modules, and marking all the measuring points in the signal flow graph; (2) performing FMEA (Failure Mode and Effects Analysis) on the measuring sensor for the angular rate, confirming failure mode and failure effects of the measuring sensor for the angular rate, and adding the failure mode to the signal flow graph according to the failure effects; (3) establishing a fault-measuring point correlation matrix; (4) performing assignment on the correlation matrix according to the signal flow graph; and (5) performing fault testability analysis on the measuring sensor for the angular rate according to the fault-measuring point correlation matrix D established in the step (4). According to the optimization method provided by the invention, the defects of the prior art are overcome, the faults can be detected and separated as much as possible under the condition of meeting resource restraint, and a basis is supplied for diagnostic design of a satellite control system.

The invention discloses a rotating equipment vibration monitoring protection device channel abnormity detection method. The rotating equipment vibration monitoring protection device channel abnormity detection method comprises steps that a vibration monitoring protection device is used to acquire correlation coefficients of various channels according to positions of detection points corresponding to the various channels and the characteristics of the rotating equipment, and weights are set according to engineering experience; the vibration monitoring protection device is used for the real-time monitoring of the vibration data of the various channels, and is used to detect whether the changing trend of the vibration data meets the correlation constraints of the channels; the vibration signals of one channel are enhanced or weakened abnormally, and the vibration signals of other related channels are not changed, and the situation is repeated a plurality of times, the channel is determined to be abnormal, and abnormality of sensors and abnormity of device sampling channels are included. By adopting the analysis and the real-time detection of the vibration detection point correlation, whether the abnormal change of the single channel meets the correlation constraints is determined, and therefore the self-inspection of the rotating equipment vibration monitoring protection device is completed, and the reliability of the device is improved.

The present invention relates to a double-threshold detection method for scanning radar, belonging to the technical field of radar target detection. The method comprises the following steps of: the step 1, receiving radar echo for more than three times; the step 2, performing down conversion, pulse pressure and MTD for the current radar echo and then performing modulo to obtain a frequency domainecho; the step 3, determining whether data in the current frequency domain echo is higher than a second threshold, if yes, jumping to the step 6, or else, jumping to the step 4; the step 4, finding out a target point being higher than the first threshold in the current frequency domain echo; the step 5, performing target trace point correlation of the target point between the current frequency domain echo thresholds and the frequency domain echoes twice in the certain threshold range of the speed, the distance and the orientation; the step 6, recording the detected distance, speed and orientation of the target; the step 7, removing the detected target in the frequency domain echo to obtain noise spectrum; and the step 8, subtracting the noise spectrum from the frequency domain echo to obtain a target trace point after double-threshold detection. The method provided by the invention can reduce the noise pedestal and can effectively improve the target detection probability.

The invention discloses an interference optimization method and system, and relates to the technical field of mobile communication. The method specifically comprises the steps: firstly carrying out the positioning of a TSC (training sequence code) of an interference community, and carrying out the multi-dimensional calculation of an interference coefficient of the TSC after positioning, and then determining the interference community according to the interference coefficient. The method gives full consideration to the distance correlation, angle correlation, BCCH (broadcast control channel) frequency-scanning CC testing point correlation and BCCH frequency-scanning time gap receiving power correlation between the interference channel and a service channel in a process of multi-dimensional calculation of the interference coefficient. Therefore, in the embodiment of the invention, the method and system give full consideration to BCCH and TCH carriers and co-channel interference among different communities in a process of interference positioning, improve the degree of fine analysis of a wireless network, greatly improve the accuracy of interference positioning, and enable the obtained interference optimization to be more reasonable and accurate.

The invention discloses a method for determining the diagnosability of an angular rate measuring sensor of a satellite based on a correlation matrix. The method comprises the following steps of: (1) dividing functional modules of the angular rate measuring sensor, establishing a signal flow diagram of each module, and marking specified measuring points in the signal flow diagram; (2) performing failure mode and effect analysis (FMEA) on the angular rate measuring sensor, determining the failure mode, failure occurrence probability, failure severity and failure effects of the angular rate measuring sensor, and according to the failure effects, adding the failure mode into the signal flow diagram; (3) establishing a failure-measuring point correlation matrix; (4) assigning the failure-measuring point correlation matrix; (5) according to the failure-measuring point correlation matrix D which is established in the step (4), performing failure detectability analysis on the angular rate measuring sensor; (6) according to the failure-measuring point correlation matrix D which is established in the step (4), performing failure isolability analysis on the angular rate measuring sensor; and(7) determining the diagnosability of the angular rate measuring sensor, and measuring the diagnosability according to failure detection rate RD and failure isolation rate RI.

The invention discloses an unmanned aerial vehicle flight path planning decision-making method based on fusion weighing. The unmanned aerial vehicle flight path planning decision-making method comprises the following steps: firstly inputting a to-be-selected flight path set for unmanned aerial vehicle flight path planning and a corresponding attribute cost matrix; performing objective weighting on the column-normalized attribute cost matrix through a fusion attribute entropy method based on an analytic hierarchy process; then calculating a point correlation coefficient of each of flight paths to the best flight path and a correlation metric matrix and further obtaining a correlation metric ranking; finally outputting the flight path with maximum correlation metric as a decision-making result. Compared with an existing flight path planning decision-making method, the flight path planning decision-making method disclosed by the invention has the benefits that an objective weighting result with smaller difference can be obtained according to a secondary adjusted weight; meanwhile, the subjectivity of weighing is avoided, and the defects of the single attribute decision-making result during final decision-making are overcome; the flight path planning decision-making method is simple and is strong in realizability.

The invention discloses a self-service novelty search method. The method involves 6 modules including (1) a sci-tech academic abstract innovation PMR (Problem, Method, Result) sentence mode identification module, (2) a PMR automatic classification and extraction module, (3) an RDF PMR knowledge base, (4) a semantic correlation relationship discovery model, (5) an intelligent novelty search and recommendation system, and (6) a user novelty search type identification and novelty search interaction interface. According to the technical scheme, innovation points in sci-tech literatures are deeply mined in advance, and a novelty search platform of an innovation point correlation relationship is formed. By adopting the technical scheme, the problems of fuzzy search range caused by a conventional mode of matching a literature resource library in a keyword combination retrieval manner, difficulty in accurately identifying the innovation points of the sci-tech literatures in a conventional method, and the like are solved. The method is high in intelligent level, is simple and easy, is high in efficiency, and greatly reduces the workload of novelty search. Users and working personnel can directly perform self-service novelty search to discover new innovation points in time.

The invention belongs to the technical field of simulation, and discloses a big data-based evaluation method for parameter pairs of a simulation mathematical model, and a big data-based evaluation system for the parameter pairs of the simulation mathematical model comprises a big data collection module, a main control module, a parameter setting module, an optimization module, an estimation module, a data storage module, and a display module. The industrial big data can be ensured to be transmitted safely in real time through the big data acquisition module, so that the pressure of network transmission is relieved, Most distorted data can be filtered through the estimation module, and the unbiased performance of a parameter estimation result is improved. Meanwhile, a row key composed of the measuring point ID and the time sequence is designed through the data storage module to store the industrial big data row by row, so that the data with time correlation and measuring point correlation in service logic are adjacently arranged row by row in physical storage, meanwhile, the read-write performance is optimized, and the balance between the query efficiency and the write-in efficiencyis achieved.

The invention discloses a distance measurement method of multiple lanes. The method comprises the following steps: 1, performing lane feature extraction; 2, obtaining a maximum confidence lane and correlation information thereof; 3, obtaining disappearance line correlation information; 4, obtaining disappearance point correlation information; 5, obtaining other lanes and correlation information thereof; and 6, performing curve type lane parameter searching optimization and performing distance measurement work. According to the invention, the multiple lanes can be rapidly and accurately identified, accurate distance measurement is performed, and the method can help an intelligent auxiliary driving system in its control over vehicles.