210results about How to "Improve algorithm efficiency" patented technology

The invention discloses a method for obtaining a resident travel characteristic parameter based on mobile phone positioning data. The method comprises the following steps of: (1) collecting mobile phone positioning data; (2) filtering the mobile phone positioning data, matching the mobile phone positioning data to traffic zones, and obtaining the matched mobile phone positioning data; (3) using users as units, ordering the matched mobile phone positioning data in one day by time, merging the continuous data in the same one traffic zone into one piece, and obtaining mobile phone positioning pretreatment data; (4) according to the number of emerged pieces and influence duration, judging residing points, restoring a travel path between two residing points, and obtaining the travel distance and the travel speed, and then obtaining a travel log table of all users; (5) on the basis of the matched mobile phone positioning data, statistically obtaining a place of residence and workplace result table; and (6) and conjointly analyzing the travel log table and the place of residence and workplace result table, and obtaining resident travel characteristic parameters. The method has the characteristics of low cost, large sample quantity, high precision and high time validity.

The invention discloses a barrier and travelable area detection method based on a vehicle-mounted binocular camera. The barrier and travelable area detection method comprises the following steps of S1, taking an image through a binocular camera; S2, preprocessing the image; S3, calculating the final matching cost of each pixel point in the image; S4, calculating through the final matching cost to obtain a v-disparity map; S5, determining the horizon line and the road scope by means of the v-disparity map; S6, calculating to obtain a barrier-road intersecting line in the road scope; S7, determining the scope of the current lane and the outermost lane; S8, calculating to obtain the height of the barrier on the part above the barrier-road intersecting line; S9, determining the image areas which belong to the same barrier; and S10, outputting the road area information and barrier information. Under the premise that disparity precision is not reduced, unnecessary binocular disparity map calculation is avoided, and therefore the real-time performance of the algorithm is greatly improved, and the barrier and travelable area detection method based on the vehicle-mounted binocular camera is suitable for fields of driving warning, automatic driving and the like.

The invention relates to a method for constructing a webpage crawler based on the repeated removal of news, which comprises the following steps: constructing an analyzer for analyzing news webpages; constructing a news set; setting a threshold value of the similarity among the webpages; comparing the currently grabbed news webpage with the news set and judging whether the similarity is higher than the threshold value or not; if the similarity is lower than the threshold value, adding the current webpage into the news set; if the similarity is higher than the threshold value, discarding the news and grabbing the next webpage; grabbing a URL of the current webpage and judging whether the URL points at the news webpage or not, if so, judging whether the URL is accessed or not; otherwise, discarding; if the URL is accessed, discarding the URL; if the URL is not accessed, storing the URL into a queue to be accessed; sequentially extracting the URL from the queue to be accessed to access; and repeatedly executing the steps. The invention has the advantages of high algorithm efficiency, less resource waste and convenient data maintenance and prevents from grabbing the webpage with repeated content.

A rotary-table servo system neural network control method comprises (1) building a mechanical dynamic model of a permanent magnet synchronous motor rotary-table servo system, and initializing the system state, sampling time and relative control parameters; (2) according to the differential mean value theorem, enabling a non-linear input dead zone in the system to linearly approximate to a simple time-varying system, avoiding complex calculation of dead-zone inverse compensation, and finally inferring a rotary-table servo system model provided with an unknown dead zone; (3) at each sampling moment, calculating and controlling a system tracking error, a fast terminal sliding mode surface and a first-order derivative of the system; (4) based on the rotary-table servo system model provided with the unknown dead zone, selecting a neural network approaching unknown trend, designing an adaptive robust finite-time neural network controller according to the system tracking error, the fast terminal sliding mode surface and the first-order derivative of the system, and updating a neural network weight matrix; and (5) entering the next sampling moment, and repetitively executing the steps from (3) to (5).

The invention belongs to the field of maintenance decision-making of hydraulic equipment, and relates to a method for the optimal maintenance decision-making of hydraulic equipment with risk control. The method mainly comprises three steps: 1) judging whether a system is in a status of defect by using a variable-weight association rule algorithm, if so, calculating the probability values of occurrences of latent faults of the system; 2) calculating the comprehensive evaluation value for the consequence of each latent fault by using a BP neural network; and 3) multiplying the probability values obtained in step 1 by the comprehensive evaluation values obtained in step 2 so as to obtain the VaRs (values-at-risk) of the latent faults, judging whether the VaRs are more than a specified threshold, if so, ranking the VaRs in descending order so as to determine the maintenance sequence; otherwise, returning to the step of monitoring. The method can judge whether a device is in a status of defect, judge the type of the latent fault and calculate the probability values of occurrences of latent faults only through a calculation; and compared with traditional risk maintenance methods, the method of the invention improves the accuracy of fault diagnosis, speeds up the diagnosis speed, and provides a better reference for online decision-making.

The invention discloses a real-time pose estimation method and a positioning grabbing system for a three-dimensional target object. The real-time pose estimation method comprises the following steps:acquiring three-dimensional graphic information of the target object; calculating to obtain a local feature descriptor of the target object according to the graphic information; performing three-dimensional pose estimation on the target object through the local feature descriptor by utilizing a pre-established three-dimensional model database to obtain pose information of the target object; and outputting the obtained pose information. According to the application, the real-time pose estimation method requested to be protected is applied to the positioning and grabbing system of the three-dimensional target object; the controller can control the motion mechanism to accurately grab the target object according to the pose information output by the processor, the grabbing accuracy can be effectively improved while the grabbing efficiency is guaranteed, and the practical performance of the positioning grabbing system in the application process is enhanced.

An image restoration method based on MTF includes the following steps: firstly, calculating MTF curve of an image; secondly, constructing dimensional MTF matrix; thirdly, carrying out image restoration in frequency domain by utilizing the MTF matrix. The method aims at remote sensing image with large data volume and is based on MTF theory and image quality degradation theory; and the method provided by the invention is effective for image restoration. Practice shows that the method can effectively restore image and improve image quality and has high algorithm efficiency. Currently, the method is successfully applied in domestic ground satellite pre-treatment system, and practice shows that the method is correct, feasible and universal.

The invention provides a distributed online real-time processing method and system for multi-source and heterogeneous flow-state big data. The method specifically comprises the steps of crawling webpage data of each source by utilizing a distributed crawler duplicate removal algorithm; pre-processing the crawled page, constructing a corresponding tree by utilizing a visual page segmentation algorithm, pruning noise nodes according to a visual rule, classifying multi-layer pages, determining predicates under different types of pages according to different characteristics, and inferring data recording block nodes and data attribute nodes through the rule; Distributing the preprocessed data source by using a distributed message system, providing a data stream, and describing the state of a data node in the data stream to form state information; Selective storage operation is carried out on data streams by utilizing a Hadoop distributed file system based on K- And detecting the processed data by using a means text clustering method, determining a text similar to a predetermined sensitive information text, and screening out the sensitive information.

The invention provides a distributed compressed sensing data fusion method having the privacy protection effect and relates to the field of wireless networks. A privacy protection fusion method based on data sparsity position information hiding is designed in a distributed scene, and by the adoption of data sparsity support set feature learning, real data sparsity position hiding and distributed compressed sensing fusion observation, the additional communication cost brought by a traditional privacy protection fusion method is avoided, and data processing of sensor networks is facilitate. The data privacy protection fusion method has the obvious data privacy protection effect on the sensor networks, meanwhile can effectively reduce network energy consumption and improve the algorithm efficiency and the data processing performance by utilizing a distributed compressed sensing fusion strategy, and facilitates user management, network application and scale expanding.

A graphic module wherein, given a curve P(x,y)=P(x(t), y(t)) between two points P₀(x,y)=P₀(x(t₀), y(t₀)) and P₁(x,y)=P₁(x(t₁), y(t₁)), in the screen coordinates, a calculating circuit computes a curve mid-point P_half(x,y)=P_half(x(t_half), y(t_half)), where t_half=((t₀+t₁)/2 on the curve, computes a segment mid-point P_M(x,y)=(P₀(x,y)+P₁(x,y))/2 on segment P₀P₁, computes a distance function d between the curve mid-point and the segment mid-point, and, given two thresholds THR0 and THR1, with THR0<=THR1, if d<THR0, it generates line segment P_oP₁, and if THR0<=d<THR1, it generates two line segments P₀P_half and P_halfP₁, and if d>=THR1, it repeats the previous steps for the curve portions from P₀ to P_half and from P_half to P₁.

The invention discloses an automatic updating processing method for increments of a land utilization vector database. The automatic updating processing method includes the steps of (1) extracting change information through remote-sensing image comparison, and storing the change information into an change-only information file according to a specific format, (2) reading in the change-only information file, calculating topological relationships between increment targets and existing land utilization land parcels, filtering out the existing land parcels which are two-dimensionally intersected with the increment targets, and calculating subdivision topological relationship types of two-dimensional intersections, (3) automatically constructing updated land parcel targets according to a land utilization increment updating processing rule based on the subdivision topological relationship types of the two-dimensional intersections, and giving corresponding characteristic attribute types, and (4) after updating processing is carried out on all the targets in the change-only information file, detecting the data quality of all the processed land parcel targets and the coincidence between the processed land parcel targets and the targets on the peripheries of the processed land parcel targets, solving corresponding problems or conflicts, generating new land utilization data, and updating the database.

The invention discloses a gesture recognition method based on a depth sensor. The method comprises the steps of sequentially obtaining depth flow information and human skeleton node data; cutting a gesture region; performing positive side and binaryzation are performed on 3D point cloud coordinates of the gesture region; gesture feature extraction, normalization and dimension reduction treatment are performed; gesture features are screened to obtain an optimal gesture feature subset; a support vector machine gesture training classifier is adopted, and a classification result is obtained; filtering is performed on the gesture classification result. The defect in the prior art is overcome, and the gesture recognition precision, stability and efficiency are improved.

The invention discloses an STL model Boolean calculation based method for extracting an inner surface model of a fuel tank in an airplane. An STL file is generated through format conversion of an initial CAD model; the STL file is subject to topological optimization to generate point-line-surface index information and adjacent point-line-surface information; Boolean subtraction operation is performed between an encircled body A formed by the theoretical outline surface of the fuel tank and a real fuel tank model B, the crossed ways of triangular surface patches are classified, and grids are re-divided after crossing; and finally all surface patches of the two models are screened according to a logic relation of Boolean subtraction, reconstruction is performed to form a new model, and the rest surface patches are removed, so that the extraction of the inner surface model is realized. According to the method, the inner surface model is extracted from the complicated CAD model of the fuel tank in the airplane; the method has robustness and timeliness; the calculation complexity is dramatically lowered; and the method greatly runs ahead of similar existing methods.

The invention discloses a robot hand-eye positioning algorithm based on a mechanical arm visual positioning system, and is used for mechanical arm movement processing in mechanical arm visual positioning. Connection of a camera coordinate system and a physical coordinate system is rapidly established according to the characteristics of the camera coordinate system, and the physical coordinate system of any position can be established according to the requirements of the onsite field so that accurate coordinate conversion parameters can be obtained. The finally obtained physical coordinates are accurate, algorithm efficiency is high, a mechanical arm moves in the shortest path, and the final movement position meets the requirement indicators.

The invention relates to a hybrid recommendation method based on sparse edge noise reduction automatic coding, belonging to the personalized recommendation field. The invention comprises the followingsteps: firstly, merging each commodity comment into a comment document; using TF-IDF processes the review text for each product and selects the word with the highest TF-IDF value to construct the commodity content vector as the feature representation of the commodity. Secondly, the sparse edge denoising automatic coding model is trained with commodity content vector, the commodity features are extracted from the commodity content vector with the trained model, and the similarity of the commodity feature vector is calculated with cosine similarity, so as to obtain the influence of the nearestneighbor commodity. Finally a predication score is obtained through combination of neighbor commodity influence and user-evaluation matrix deposition. The invention effectively improves the algorithmefficiency and the recommendation accuracy.

The invention discloses a genetic-algorithm-based method for automatically generating data stream test cases. At present, in genetic-algorithm-based technologies of automatically generating data stream test cases, crossover and mutation points of a genetic algorithm are selected at free positions of individual genes randomly, good genes are produced, and meanwhile the possibility that existing good genes are damaged also exists; whether the maximum adaptation degree of each individual in an offspring population is greater than the maximum adaptation degree of each individual in a parent population or not, the offspring population continues to inherit, and an iteration process is prolonged. According to the genetic-algorithm-based method for automatically generating the data stream test cases, a specific branch which does not satisfy a target path is found when an adaptation function is calculated, structural information of the branch is used for constraining a range of crossover operation and mutation operation of the genetic algorithm, and meanwhile offspring with the adaptation degrees being greater than those of parents are abandoned by comparing the maximum adaptation degree of each individual in the offspring population with the maximum adaptation degree of each individual in the parent population; thus, transferring of the good genes is guaranteed, the number of iterations is reduced, and computational efficiency is improved.

The invention relates to computer network technology and discloses a system and a method for monitoring the abnormity of a border gateway protocol (BGP) network. The method comprises the following steps: collecting BGP advertisement update messages in the BGP network, constructing a character string v corresponding to each collected BGP update message, adding the character strings v to a character string assembly V, searching a character substring vsub with the highest appearance frequency as the position where the BGP network abnormity occurs, and speculating the reason inducing the BGP network abnormity according to the content of the character substring vsub following a routing behavior analysis method. The invention can more effectively monitor BGP network abnormity and analyzing abnormity reason, with remarkably improved accuracy and simplicity.

The invention discloses an urban traffic dispatching system and method based on image fusion in severe weather. The system comprises a traffic dispatching center, a synthetic aperture radar and an optical remote sensing radar, wherein the synthetic aperture radar and the optical remote sensing radar are carried on a satellite. The traffic dispatching center comprises an image processing sub-center used for processing real-time images to obtain real-time traffic flow levels of roads and an information issue sub-center used for issuing the real-time traffic flow levels of the roads to vehicle groups. The method includes the steps that image sequences of SAR images and PAN images of a city are shot through the satellite in real time; the images are transmitted and preprocessed; the SAR images and the PAN images are fused; the traffic flow levels of the roads are divided; road information is issued. According to the urban traffic dispatching system and method based on image fusion in severe weather, through image fusion, urban road traffic conditions are recognized and the traffic flow levels of all the roads are evaluated, information is broadcast to vehicles through the traffic dispatching center in real time, and thus urban traffic dispatching is achieved, and traffic jams caused by severe weather can be effectively prevented.

The invention discloses an electric energy meter calibrating method. The method comprises the steps that first, the source value of the electrical parameter of an electric energy meter calibration table body is acquired; meter calibrating coefficients are reset for a calibrated meter; then, the table body is manually switched to the next meter calibrating point; the stability of the table body is judged according to the current measured value of the calibrated meter and the source value of the table body, and if the table body is unstable, it needs to wait until the table body is stable; afterwards, the current state of the table body is judged, and the meter calibrating points are automatically selected for the calibrated meter; then, the precision of the calibrated meter is obtained according to the current measured value, the filtering value and the source value of the table body of the calibrated meter; afterwards, the meter calibrating coefficients of the calibrated meter are obtained respectively according to a set formula; at last, the meter calibrating coefficients are set and stored. According to the electric energy meter calibrating method, a 485 bus channel is needless, the support of related upper computer software and equipment is of no need, the state of the table body and the state of the electric energy meter of the electric energy meter calibration table body can be intelligently distinguished, and the whole meter calibrating process only needs dozens of seconds at the soonest.

Disclosed a multi-foot robot gait optimization control method based on the multidimensional workspace coupling algorithm. The method comprises the following steps: step 1, solving a virtual constraint radius and parsing robot body swing leg movement constraint K space according to the virtual constraint radius; step 2, solving the swing leg ideal foothold constraint R space and the robot body stability constraint B space, coupling the robot body swing leg movement constraint K space, the swing leg ideal foothold constraint R space and the robot body stability constraint B space, solving the multidimensional robot body workspace W, and then putting forward the robot body 'dead-lock' instability situation and countermeasures; step 3, parsing the mapping relation between the standing leg joint output position and the robot body workspace according to the multidimensional robot body workspace obtained in step 2, and finally, making polynomial interpolation calculation on the joint rotation angle, and finishing a gait plan for the robot in a non-structural environment. The method guarantees the gait stability and gait high-efficiency of the robot in the non-structural environment.

The invention discloses a method and a device for obtaining synonyms, belonging to the field of computers. The method comprises the steps of: creating a set of matching pairs between words and result addresses; taking each word in the set as a word to be searched, and searching the matched result address from the set according to the word to be searched; and according to the result address, searching the word matched with the result address from the set and taking the word which is found as a synonym. The device comprises a creation module, a first searching module and a second searching module. The method and the device can more easily obtain the synonyms, reduce the consumption of manpower and material resources and improve algorithm efficiency.

The present invention provides a motion estimation circuit and an operating method thereof. The motion estimation circuit includes processing elements PE_m (−n≦m≦n, n represents a search range), data latches FF_k (−n<k≦n) and selection circuits MUX_h (−1≦h≦1). The processing element receives a current block data and the corresponded block data in a search window and performs a comparison operation on the two block data. The output-end of FF_k is coupled to an input-end of FF_k+1 and a first input-end of PE_k. The output-end of MUX_h is coupled to a second input-end of PE_h. Wherein, each 4×4-pixel sub block of the current block is input into PE_−n and FF_−(n−1), the left sector of the sub-search-window SW′ is input into the second input-ends of PE_−n˜PE₋₂ and the first input-end of MUX_h, and the right sector of the sub-search-window SW′ is input into the second input-ends of PE₂˜PE_n and MUX_h.

A system for detecting a lane line of a road and a method thereof is disclosed. An image-retrieving device retrieves an image in front of a vehicle to generate a picture, and transmits the picture to a processing device. The processing device transforms one or two lane lines on the picture into a plurality of characteristic values, processes the characteristic values to generate one or two prediction lane lines, and uses them to dynamically predict and complete the lane lines, thereby forming a lane line prediction model. The processing device uses the lane line prediction model to determine whether the vehicle deviates, and transmits the picture and the lane line prediction model to a display device to display. When the vehicle deviates, the display device warns. The present invention can improve to recognize an unclear lane line, a single lane line and a far lane line.

The present invention discloses a correcting method for the inclination of a vehicle license based on a supporting vector machine. The implementing steps of the method include an images collection, a gray processing, a binary processing, an inclination correction of the vehicle license (comprising that a matrix of an image datum collection is founded, the image matrix is centralized, the matrix is calculated, the inclination vector is calculated and an image is obtained after the inclination correction via transforming the coordinate), an expanding correction of the image and an erosion correction of the image. The correcting method for the inclination of a vehicle license of the present invention supports that a new machine learning tool (the vector machine) is applied. The traditional optimal-requesting problem of a Hough space of a vehicle license image is converted to a solution-requesting problem for a linear matrix. The calculation is simplified and the arithmetic efficiency is improved. The randomicity and instability existing in the searching process of the optimal points of parameters such as the obliquity are avoided. For the images with indistinct frame or noise, a better effect can still be obtained.