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 relates to a method for planning robot paths on the basis of path expansion ant colony algorithms. The method has the advantages that the ant colony algorithms are applied to the field of robot path planning, path expansion ant colony algorithm optimization strategies are proposed, the robot path optimizing efficiency can be optimized, information element distribution time-varying characteristics, information element updating strategies, path location inflection point optimization and local optimal path expansion are introduced, and location inflection point parameters and general evaluation are additionally used as evaluation standards for the paths; as verified by simulation analysis and practical experiments on the three algorithms, the method is high in robot path planning and searching capacity on the basis of the path expansion ant colony algorithm optimization strategies and is high in algorithm efficiency, and the found paths are short; phenomena that the algorithms run into local optimization can be effectively inhibited, the optimal paths of robots can be searched, and the robots can quickly avoid obstacles to safely arrive at target points.

The invention relates to a smooth path planning method for mobile robots based on a dynamic complex environment, and belongs to the field of robot path planning. The method comprises the steps of starting; searching for an optimal path; conducting smooth treatment on the optimal path; ending. The step of searching for the optimal path uses a two-way RRT algorithm with the idea of gravity of an artificial potential field to perform path searching, that is, the artificial potential field gravity guides a random tree to grow toward a target direction, and the RRT algorithm is prevented from randomly sampling the global; a two-way A* algorithm after a heuristic function is improved is adopted to add angle factors based on distance factors, the units of distances and angles are normalized, thepath planning time is greatly reduced, and the convergence speed of paths is improved; smoothing treatment is conducted on the optimal path, a Freudian smoothing algorithm is adopted to remove redundant nodes, a B-spline method is used three times for smoothly connecting remaining nodes, and the smooth optimal path is finally obtained.

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 Phalf(x,y)=Phalf(x(thalf), y(thalf)), where thalf=((t0+t1) / 2 on the curve, computes a segment mid-point PM(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 PoP1, and if THR0<=d<THR1, it generates two line segments P0Phalf and PhalfP1, and if d>=THR1, it repeats the previous steps for the curve portions from P0 to Phalf and from Phalf 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 an optical remote sensing image registration method which is characterized by the following steps that: first a small surface element is extracted, pretreated and matched at one step so as to more effectively extract a closed border and reduce the algorithm complexity simultaneously; second, boundary correspondence relationship is established according to the similar function of a closed border chain code and a region invariant moment matching strategy; and finally the center of mass of a matched area, i.e. a matching point is extracted for consistency detection, and an affine transformation parameter is estimated for image registration. The optical remote sensing image registration method improves the defect that the prior art is based on a chain code registration method, improves the registration precision and time efficiency, and can meet the automatic registration requirements of optical remote sensing images.

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.

The invention provides a method for accurately moving a mechanical arm to a designated location by a robot. The method comprises the following steps that coordinates of a plurality of designated locations of a first designated image and a second designated image on a preset calibration board are obtained when a robot moving the mechanical arm to the preset calibration board; related physical parameters of the center points of the first designated image and the second designated image are calculated; an image from a fixed camera that captures both the first and second designated images is acquired, and data processing is carried out to determine related image parameters of the center points of the first and second designated images; a mapping relation between physical coordinates of the robot moving mechanical arm and coordinates of the camera is established according to the related physical parameters and the related image parameters of the center points of the first designated image and the second designated image; and one of the pixel point coordinates of the image of the fixed camera is assigned and subjected to converting, and the physical coordinates of the robot moving mechanical arm are obtained and the robot moving mechanical arm is driven to reach the physic coordinates. According to the method for accurately moving the mechanical arm to the designated location by therobot, by establishing the connection between the camera coordinates and the physical coordinates, the robot can move the mechanical arm to the designated location accurately.

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 PEm (−n≦m≦n, n represents a search range), data latches FFk (−n<k≦n) and selection circuits MUXh (−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 FFk is coupled to an input-end of FFk+1 and a first input-end of PEk. The output-end of MUXh is coupled to a second input-end of PEh. 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 MUXh, and the right sector of the sub-search-window SW′ is input into the second input-ends of PE2˜PEn and MUXh.

The invention discloses a heterogeneous network link prediction method based on a meta-path. Rich and complex semantics of the heterogeneous network are processed by utilizing meta-paths; meta-path instances are extracted from the network and network node weights are learnt; the network topology characteristics are integrated to update the network node embedding, the updated network node embeddingis utilized to perform classification, clustering, link prediction and other work, the applicability in the actual life is high, and the accuracy of the classification, clustering, link prediction and other work of the heterogeneous network can be effectively improved.

A rapid inspection system for a power line corridor based on laser scanning guidance comprises a flight platform and a ground monitoring system. The flight platform comprises a fuselage structure, a power system and a flight control system. The fuselage structure further carries a laser scanner and a wireless data transmission module. The flight control system comprises a processing control unit and further comprises an inertial navigation unit and a satellite navigation unit which are connected with the processing control unit. A rapid inspection system for the power line corridor based on laser scanning guidance comprises the steps that three-dimensional point cloud resolving is conducted according to laser scanning data, position data and attitude data, three-dimensional point cloud ofthe power line corridor is obtained, and the relative position relation is obtained through extracting of the power line point cloud; adjusting information of the next flight path is planned, the adjusting information is compared with a set clearance threshold value, and clearance hidden danger points are judged; hidden danger point data are sent back to the ground monitoring system in real time;the hidden danger point data are sent to a hidden danger guiding terminal; and the hidden danger guiding terminal displays the hidden danger point data, and a navigation track for advancing for hiddendanger trouble shooting is formed.

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.