34results about How to "The division result is accurate" patented technology

The invention provides a group dividing method of a communication network, which comprises the following steps: preprocessing the communication data; creating a communication relationship network according to the obtained preprocessing result to obtain the nodes representing a communication sender and a communication receiver in the communication network as well as a side representing the communication relationship between the communication sender and the communication receiver; constructing a demand text vector and a communication text vector according to a query word provided by the user; calculating the node centrality of each node in the communication relationship network; calculating the communication relationship strength among the nodes in communication relationship in the communication relationship network, the similarity of the sides among the nodes and the satisfaction degree of the user on the sides among the nodes; performing side clustering operation on the sides in the communication relationship network to generate multiple groups; finding respective core members in the group according to the node centrality and communication theme; expanding the members in the group; and dividing the expanded members in the group to generate a new group.

The invention relates to a method for dividing an urban road network, in particular to a dynamic division method of an urban road network control sub-area based on a macroscopic basic map. The methodsolves a problem that the existing division method lacks theoretical support, is unscientific in the threshold of the index, is not systematic in division, is not comprehensive in target, and cannot achieve real-time adjustment. The method comprises 1) initializing a computer; 2) selecting an influencing factor and collecting the basic data; 3) calculating a relationship between adjacent road segments according to a road network topology structure and traffic information data, and establishing a weight matrix; 4) locally representing the similarity between the road segments and establishing asimilarity matrix; 5) initially dividing the road network; 6) updating the numbers and merging the small sub-areas. The method, based on the basic data of each road segment in the road network, fullyconsiders the mutual influence factors between adjacent road segments, and has sufficient theoretical basis support, can achieve real-time adjustment, and is clear in objective and reasonable in division.

The invention discloses a modeling method for an island-division mixed integer programming model for an active power distribution network. The modeling method comprises the steps of establishing a target function of the island-division mixed integer programming model for the active power distribution network; establishing a branch current power flow constraint by taking a current real part and a current imaginary part as state variables, establishing a network topology reconstruction model, establishing a separation constraint model of the load switching state by dual-linear constraint and node injection current, and linearizing the quadratic component of the line current and the node voltage by a special order set 2; establishing a linearized power characteristic equation of a voltage-source inverter access type DG; establishing a linearized power characteristic equation of a doubly-fed induction-based wind generator; establishing a linearized power characteristic equation of a synchronous generator; and assembling the island-division mixed integer programming model for the active power distribution network by combination with the existing linearized constraint of the active power distribution network, and solving the island-division mixed integer programming model. The modeling method is capable of effectively lowering the solving complexity of the island-division of the power distribution network, and has the characteristics of high solving precision, high fitness, high engineering actual conformity, and the like.

The invention provides a complex network cell discovering method under an adaptive evolution bat algorithm for self-media network data. The method includes the following steps that S1, mass data is acquired, a network structure model is established, according to the bat algorithm, a modularity function serves as a fitness function, a coding mode based on characters is adopted, and an initialized population is improved through a label propagation method; S2, the individual speed of the bat algorithm is converted into a mutation probability value, position update is calculated through a cross operator and a mutation operator, therefore, adaptive evolution of the common bat algorithm is achieved, the adaptive evolution bat algorithm is used for dividing a network, and a more accurate network cell division result is obtained. Compared with other intelligent algorithms for cell discovery, the algorithm has the advantages of being high in convergence rate and solution precision, and is more suitable for cell discovery under the large-scale network.

The invention discloses a reverse engineering modeling method for machine part data by using Gauss sphere cluster. The method includes the steps: allowing a user to scan a machine part into a three-dimensional point cloud by using a three-dimensional scanner; automatically converting the point cloud into a grid through a grid triangularization method; and performing rough decomposition on a whole grid model through a main curvature such that each secondary curved surface of the part independently falls into a relevant sub-zone. The method performs type detection on a sub-grid through a Gauss sphere cluster method, performs zone subdividing and recombination, performs secondary curved surface fitting on each subdivided sub-grid through a nonlinear least square method and a faithful distance, and cuts and sews a curved surface model so as to establish a digital entity model of the machine part. The user can perform parameter editing or curved surface deformation on the entity model so as to innovate a reverse design of the model. The modeling method is simple and efficient, can avoid user interference, and can automatically or semi-automatically complete reverse design modeling of the machine part.

The invention discloses a network protocol analysis method of a malicious code and belongs to the network security technical field. The network protocol analysis method of the malicious code comprises the following steps: (1), deploying the to-be-analyzed malicious code in a monitoring server, marking data which are received from a network by a malicious process as original stain source data; (2), recording all of operational orders of the malicious process to the stain data in a tracking mode; and recording application program interface (API) which is called in the process of implementing the malicious process and is relative to the security of an operational system; (3) starting grammatical division to the network protocol data of the malicious code based on the recorded operational orders and the operational characteristics of the malicious process; and (4), as to a grammatical character field which is regarded as API function parameters, and acquiring the final semanteme of the grammatical field based on the corresponding API function. The network protocol analysis method of the malicious code has generality and anti-interference performance on a protocol element recognition aspect, and enables a division result of a protocol element to be clear and accurate.

The invention discloses a yield loss root cause analysis method based on information fusion, and relates to the technical field of OLED, display, panel and semiconductor manufacturing industry. Aimingat the root cause analysis of yield loss, the invention constructs a problem parameter rapid automatic positioning method and a factor level automatic division method based on information fusion, andsolves the problems of low automation degree, low data information utilization rate and low problem positioning precision of a traditional analysis method. According to the method, the data is labeled and grouped, the pertinence of the data is improved, different rule combinations are designed, the information of reject ratio data and parameter data in all aspects is fused, and the relationship between the reject ratio data and the parameter data is comprehensively considered, so that the positioning analysis of problem parameters is more accurate and efficient. Meanwhile, in order to determine the abnormal fluctuation range of problem parameters, a clustering-based parameter level division method is provided, and the problems that an existing division method is low in speed, low in precision and not beneficial to big data analysis are solved.

The invention provides a decision tree generation method and a system thereof. The method comprises the following steps of acquiring a training sample set and a sample attribute; calculating a type number of different values of each sample attribute in the training sample set; according to the type number, calculating a distinguishing degree of each sample attribute respectively; selecting the sample attribute with the highest distinguishing degree as a basis attribute of decision tree branch dividing; carrying out recursion calculation dividing on the divided training sample set according to the above method till that a branch node reaches a preset threshold so that decision tree generation is completed. The invention also provides the corresponding system. Through the method in the invention, selection of decision tree attribute dividing can be reasonably performed so that a dividing result is accurate and possesses a practical value.

The invention belongs to the technical field of coal testing, and relates to an intelligent coal quality testing system. At present, all operation processes and equipment are difficult to combine in order, the operation is complicated, the testing efficiency is low, the quality condition and the quality grade of coal are difficult to automatically obtain, and the use effect is poor, the invention just aims to solve the above problems. The system comprises an intelligent control unit, a sample supply unit, a sample transportation unit, a coal detection unit and a coal analysis unit. Through automatic and intelligent control, traditional coal detection items and links are connected in series, ordered combination of all operation processes and equipment is achieved, operation is easy, the testing efficiency is high, time and labor are saved, the testing cost is reduced, and the testing efficiency is improved. By means of the sample analysis unit, various detection data can be combined and automatically analyzed and calculated to obtain the quality condition of the coal, the function of automatically dividing the coal quality grade can be achieved, the analysis result and the division result are very accurate, and the use effect is good.

The invention discloses a user community division method and device, relates to the field of data processing, and can improve the accuracy of user community division, and the method comprises the steps: obtaining call features between to-be-divided users, and constructing a topological structure according to the call features; calculating a link relationship between any two nodes according to thecall features and a first formula; calculating the constraint of any node on the adjacent node according to the link relationship between any two nodes; calculating the adjacent energy sum of the first node according to the constraint of the first adjacency node on the second node; calculating the importance degree of the third node according to the adjacency energy sum of the first node; if the importance degree of the third node is greater than or equal to the first threshold and the node degree is greater than or equal to the second threshold, determining the third node as a core node; anddividing the core node and the adjacent nodes of the core node into the same community. The application used for realizing accurate community division.

The invention discloses a device and method for judging the fractured-rock-mass perfection degree. The problems that a fractured rock mass in the prior art cannot be sampled, and the perfection degreeof a fractured-rock-mass model simulated through similar materials cannot be determined are solved; the device and method have the advantage that a reference basis is provided for indoor-model mechanical test researching of a fractured rock mass with a perfection degree classifying method. According to the technical scheme, the device for judging the fractured-rock-mass perfection degree comprises a test platform for containing the fractured rock mass, angle-shape baffles, a supporting frame, side frames and a wave speed tester, wherein the angle-shape baffles are perpendicularly arranged relative to the test platform to limit the fractured rock mass; the supporting frame crosses the test platform, is connected with a vertical pressing part to apply normal pressure to the fractured rock mass, and is connected with a first transverse pressing part; the side frames are connected with a second transverse pressing part, and the first transverse pressing part and the second transverse pressing part apply confining pressure to the fractured rock mass; the wave speed tester is arranged on the side of the test platform.

According to the efficient and accurate division method for the ultrasonic positioning fibromyoma image, a computer-aided ultrasonic image division method is adopted for overcoming the defects that inthe prior art, division of an ultrasonic positioning navigation image is mostly completed manually, and is tedious and time-consuming. According to the ultrasonic image division method based on segmentation and merging, pixel points are not directly clustered, but superpixels are clustered, so that the calculation amount is greatly reduced, and the efficiency of the whole ultrasonic image division method is improved. Characteristic extraction is performed on superpixels rather than pixel points, so that the obtained texture characteristics are more robust, and the method adapts to the characteristics of poor HIFU ultrasonic positioning navigation image quality. According to the image division method, various situations of the ultrasonic image can be processed, and a good division effect on the ultrasonic image with an extremely low signal-to-noise ratio is achieved. The method is accurate in division result and low in manual intervention degree, and can be efficiently applied to actual ultrasonic positioning navigation for HIFU treatment of fibromyoma.

The invention discloses an ultrasonic image processing method and a communication terminal. The method comprises: dividing a to-be-processed ultrasonic image into a non-edge region and an edge region;for each pixel point in the to-be-processed ultrasonic image, determining a dispersion degree value of a pixel value in each preset direction in a preset neighborhood of the pixel point; if the pixelpoints are the pixel points in the non-edge area, carrying out image filtering processing on the pixel points according to discrete degree values of the pixel points in all preset directions; and ifthe pixel points are the pixel points in the edge area, determining an edge direction according to the discrete degree values and the gradient values of the pixel points in each preset direction, andperforming directional smoothing processing and edge enhancement processing according to the determined edge direction. Through the method, the distinguishability and continuity of tissues and organsare improved, and the method is used for at least solving the problems of abrupt points, flicker points or image pasting caused by marginal enhancement in related technologies.

The invention discloses an urban main road traffic flow blocking state division method in combination with macroscopic traffic flow and microscopic traffic flow information. The method specifically comprises the following steps: placing a camera on an investigation road section for traffic investigation; preprocessing traffic data information acquired by a camera, removing invalid data, and determining a time headway frequency distribution interval; comparing the traffic parameter standard deviation under each statistical interval, and determining an optimal statistical interval; clustering the speed by using a K-means method, selecting an optimal traffic state number, and obtaining a speed threshold value of each traffic state; carrying out free flow and following state division on the traffic flow in each state based on a time headway method; and obtaining a clear time headway threshold value by using a coordinate conversion method. The method can better consider the interaction between the vehicles in the microscopic traffic flow and the overall characteristics of the traffic flow in the macroscopic traffic flow, guarantees the overall fitting of the traffic flow, and is of great significance.

The invention discloses a method for dividing an image area based on an RGB change trend. The method mainly uses two rounds of similarity judgment for dividing an image area, and judgeswhether a pixelpoint is one of certain area clusters or not according to the change direction similarity of RGB three-primary-color channels and the physical position proximity of the pixel point, and the method belongs to a picture preprocessing method. According to the method for dividing the image area based on the RGB change trend, judgment can be carried out according to the change trend of the color signal, so that edge division is clearer, and the accuracy of image area division is effectively improved.

The invention relates to a network service dynamic identification and division system, method and device and a storage medium. The system comprises a network feature extraction module, a network topology discovery module and a service identification and division module. The network feature extraction module obtains real-time traffic data, preprocesses the obtained real-time traffic data, performs structured feature extraction and quantitative feature calculation after the preprocessing operation, performs persistent processing on a feature calculation result, and stores the result into a structured feature library; the network topology discovery module discovers network topology and constructs network topology information; and the service identification and division module is used for identifying and dividing network services. According to the invention, the problem that a traditional network service identification and division method is not applicable in an internal environment of a cloud data center under the condition that only traffic data is used as a single data source is solved, and the requirements of rapid, dynamic and real-time network identification and division are further met.

The invention relates to a road network operation characteristic change point identification method based on dynamic planning, and the method comprises the following steps: S1, constructing a time sequence through the average vehicle speed data of a traffic zone, and extracting time-space change characteristics; s2, solving a minimum segmentation error through a dynamic programming algorithm, and obtaining an optimal segmentation scheme under different segmentation segment numbers; and S3, selecting an optimal segmentation segment number through an improved elbow method, determining a segmentation breakpoint, and obtaining a road network operation feature change point. Compared with the prior art, the method has the advantages of low time complexity and high accuracy of change point identification.

The invention discloses an image acquisition method and an acquisition device for track gauge detection. The method adopts rotary shooting, and can collect the image information of the same track from different angles and different positions, and the obtained track information is comprehensive and complete. Edge time-sharing can combine multi-angle and multi-position shooting images, the division result is more accurate, and the track gauge information obtained by detection is also more accurate. The invention also provides an image acquisition device, through which the functions of automatic walking and automatic rotation to photograph the track can be realized, and the image acquisition efficiency can be improved.

The invention discloses a community detection method based on backbone network extension, which is used for rapid community discovery in large-scale complex networks. The present invention mainly includes: use the improved PageRank algorithm (WP) based on node weight to calculate the input network, select the node whose WP value is greater than the threshold as the backbone node of the network; traverse the whole network, extract the backbone node and connect any two backbone nodes The edges of the nodes constitute the backbone network; the hierarchical clustering algorithm is run in the backbone network to obtain the backbone community structure; the extension algorithm is used to extend the backbone community to the entire network to obtain the community structure of the overall network. The invention narrows the operating range of the hierarchical clustering algorithm to the backbone network, avoids clustering in the whole network, has relatively small time complexity, and is suitable for community discovery in large-scale complex networks. In addition, the present invention can quickly capture the change details of the overall community by tracking the change of the backbone community, and is suitable for community discovery in a rapidly evolving network.

The invention discloses a method for classifying the state of blocked traffic flow on an urban trunk road combined with macroscopic traffic flow and microscopic traffic flow information. Invalid data, determine the headway frequency distribution interval; compare the standard deviation of traffic parameters under each statistical interval to determine the best statistical interval; use the K-means method to cluster the speed, select the optimal number of traffic states, and get The speed threshold of each traffic state; based on the headway method, the traffic flow in each state is divided into free flow and car-following states; the coordinate transformation method is used to obtain a clear headway threshold; the present invention can better consider the vehicles in the microscopic traffic flow The interaction between them, as well as the overall characteristics of the traffic flow in the macroscopic traffic flow, while ensuring the overall fit of the traffic flow, is of great significance.

The invention relates to a method for dividing an urban road network, in particular to a dynamic division method of an urban road network control sub-area based on a macroscopic basic map. The methodsolves a problem that the existing division method lacks theoretical support, is unscientific in the threshold of the index, is not systematic in division, is not comprehensive in target, and cannot achieve real-time adjustment. The method comprises 1) initializing a computer; 2) selecting an influencing factor and collecting the basic data; 3) calculating a relationship between adjacent road segments according to a road network topology structure and traffic information data, and establishing a weight matrix; 4) locally representing the similarity between the road segments and establishing asimilarity matrix; 5) initially dividing the road network; 6) updating the numbers and merging the small sub-areas. The method, based on the basic data of each road segment in the road network, fullyconsiders the mutual influence factors between adjacent road segments, and has sufficient theoretical basis support, can achieve real-time adjustment, and is clear in objective and reasonable in division.

The present application relates to a method for establishing a shale graptolite belt division model and a shale graptolite belt division method, wherein the method for establishing a shale graptolite belt division model includes: performing graptolite on key wells based on the characteristic graptolite of key wells According to the division of the graptolite zone and the position depth of the graptolite zone boundary in the key well, the multiple logging curves of the key well correspond to the position depth of the graptolite zone and the graptolite zone boundary according to the depth; analyze the graptolite zone boundary According to the characteristic changes of multiple well logging curves at the location, multiple well logging curves are selected for the graptolite zone division model; Corresponding to the log curves, the graptolite zone division model is obtained. This shale graptolite zone division method uses this model to delineate the graptolite zones of uncored wells. The division of uncored wells is realized, and the problem that the graptolite belt with inconspicuous natural gamma ray curve characteristics cannot be accurately divided is solved.

The invention relates to a method for dividing power supply areas of distribution networks based on cluster analysis. This method first selects the scope of the power supply area to be divided, analyzes its current situation and the main factors affecting the division of the power supply area, and establishes an evaluation index system for the division of the power supply area; then analyzes the distribution of the current status indicators and planning indicators of the power supply area , and choose an appropriate method to process the data, so that the processed data basically obeys the normal distribution; then, using SAS software, choose an appropriate method to carry out cluster analysis on the sample data of each indicator or several indicators together Cluster analysis, so that the cluster results basically obey the normal distribution; finally, according to the cluster analysis results, establish the division standard of the power supply area. This method has high adaptability and can be applied to the division of power supply areas of different scales in different regions, and can lay a foundation for the formulation of differentiated technical guidelines for distribution network planning and design and related technical standards.

The invention provides a group dividing method of a communication network, which comprises the following steps: preprocessing the communication data; creating a communication relationship network according to the obtained preprocessing result to obtain the nodes representing a communication sender and a communication receiver in the communication network as well as a side representing the communication relationship between the communication sender and the communication receiver; constructing a demand text vector and a communication text vector according to a query word provided by the user; calculating the node centrality of each node in the communication relationship network; calculating the communication relationship strength among the nodes in communication relationship in the communication relationship network, the similarity of the sides among the nodes and the satisfaction degree of the user on the sides among the nodes; performing side clustering operation on the sides in the communication relationship network to generate multiple groups; finding respective core members in the group according to the node centrality and communication theme; expanding the members in the group; and dividing the expanded members in the group to generate a new group.

The embodiment of the invention discloses a CT angiography CTA source image processing method, device and equipment, and the method comprises the steps: extracting a brain parenchyma region from a CTA source image, obtaining a brain parenchyma CTA source image, inputting the brain parenchyma CTA source image and a template image corresponding to the CTA source image into a registration model generated through preset training, and obtaining a target deformation field; based on the obtained target deformation field, deforming the MCA brain atlas image corresponding to the template image to obtain an MCA brain atlas image corresponding to the brain parenchyma CTA source image; and obtaining a division result of each MCA blood supply area in the brain parenchyma CTA source image through an MCA brain map image corresponding to the brain parenchyma CTA source image obtained through the target deformation field. According to the MCA brain atlas image corresponding to the brain parenchyma CTA source image obtained based on the target deformation field, the MCA blood supply area in the brain parenchyma CTA source image can be accurately divided.

The embodiment of the application discloses a virtual partitioning method and device for service index intervals and electronic equipment. The method comprises the steps of: displaying a plurality ofintervals corresponding a service index according to entries, wherein one entry is used for representing a range of one interval of the service index; receiving an operation of regulating the displayed entries; and based on interval distribution corresponding to the regulated entries, carrying out secondary regulation on entries related to intervals which are overlapped or omitted.

The invention discloses a network protocol analysis method of a malicious code and belongs to the network security technical field. The network protocol analysis method of the malicious code comprises the following steps: (1), deploying the to-be-analyzed malicious code in a monitoring server, marking data which are received from a network by a malicious process as original stain source data; (2), recording all of operational orders of the malicious process to the stain data in a tracking mode; and recording application program interface (API) which is called in the process of implementing the malicious process and is relative to the security of an operational system; (3) starting grammatical division to the network protocol data of the malicious code based on the recorded operational orders and the operational characteristics of the malicious process; and (4), as to a grammatical character field which is regarded as API function parameters, and acquiring the final semanteme of the grammatical field based on the corresponding API function. The network protocol analysis method of the malicious code has generality and anti-interference performance on a protocol element recognition aspect, and enables a division result of a protocol element to be clear and accurate.