449 results about "Mathematical Graph" patented technology

The invention relates to an intelligent and automatic delineation method for a gross tumor volume and organs at risk, which includes the following steps: (1) tumor multi-modal (mode) image reconstruction, de-noising, enhancement, registration, fusion and other preprocessing; (2) automatic extraction of tumor image features: automatically extracting one or more pieces of tumor image group (texture feature spectrum) information from CT, CBCT, MRI, PET and/or ultrasonic multi-modal (mode) tumor medical image data; and (3) intelligently and automatically delineating a gross tumor volume and organs at risk through deep learning, machine learning, artificial intelligence, regional growing, the graph theory (random walk), a geometric level set, and/or a statistical theory method. A gross tumor volume (GTV) and organs at risk (OAR) can be delineated with high precision.

A computerized method for modeling a utility network. The method includes retrieving geographical information system (GIS) data, asset management data, and sensor archive data of one or more assets of the utility network. The method also includes generating one or more mathematical elements from the one or more assets and creating probable connections between the one or more mathematical graph elements based on the GIS and asset data. A mathematical graph is generated based on the probable connections, the mathematical graph including one or more asset characteristics of the one or more assets. Analysis is performed on the utility network using the mathematical graph and the mathematical graph data is stored for use by other systems within the utility network.

In one embodiment, a computer readable medium comprises at least first instructions and second instructions. The first instructions, when executed, compute a first plurality of routes. Each route of the first plurality of routes corresponds to a respective net of a plurality of nets in an integrated circuit layout, and represents a theoretically optimal route of the respective net according to a graph theory based algorithm. The second instructions, when executed, compare each of the first plurality of routes to a corresponding route of a current plurality of routes, each of the current plurality of routes corresponding to the respective net of the plurality of nets and currently existing in the integrated circuit layout. A method is also contemplated.

The invention relates to a target tracking method based on character feature invariant and graph theory clustering which overcomes the defects of the existing target tracking method, tackles the difficult problems of target scale changes, rotations, noises, diurnal variations, shadings, conglutinations, camera vibrations and the like in a scene and generates the stable target trajectory and accurate motion information thereof. The tracking method comprises the following steps: demarcating a camera; preprocessing an image; detecting a character; extracting invariant features, calculating invariant features at angular points; matching features, performing invariant feature matching between one angular point of the previous frame and all the angular points of the neighborhood of the local frame; forming angular point trajectories, connecting the frame-matched angular points to form the trajectory of the angular point; performing trajectory clustering based on graph theory, forming a plurality of temporary targets after clustering; combining or splitting targets, determining that the target and the temporary targets obtained by clustering combine or split, performing reasonableness test to update the current set target; performing reasonableness test to judge the reasonableness of the trajectory and scale of the target; and extracting Gaussian background and angular point background.

The invention relates to an EV charging load temporal-spatial distribution prediction method based on real-time traffic and temperature, and belongs to the field of intelligent power grids. The method comprises the steps that S1, various electric vehicles are classified, and the space transferring and charging characteristics of the electric vehicles are analyzed; S2, an urban traffic network is subjected to abstract simulation by utilizing the trip chain theory and a graph theory method; S3, time-space shift models of the electric vehicles are built through Monte-Carlo simulation and a random shortest circuit method based on the Markovian decision; S4, a temperature and traffic energy consumption model is established according to actual test data of the electric vehicles. The method has universality, is suitable for regional distribution network analysis, can conveniently and effectively calculate the temporal-spatial distribution situation in an urban area and can predict charging load changes when the traffic condition and the temperature condition change, and prediction results provide a basis for research of charging station planning, load scheduling and the like.

A method for fingerprint recognition comprises converting fingerprint specimens into electronic images; converting the electronic images into mathematical graphs that include a vertex and an edge; detecting similarities between a plurality of graphs; aligning vertices and edges of similar graphs; and comparing similar graphs.

The invention relates to the field of unmanned aerial vehicles, and discloses a multi-unmanned aerial vehicle formation self-organization collaborative control method based on a rigid graph theory. The method includes the following steps: 1. based on a rigid graph, establishing a target rigid network topological structure of an unmanned aerial vehicle formation; and 2. after the establishment of the target rigid network topological structure, if the unmanned aerial vehicle formation comes to a barrier in flight, circumventing the barrier with a virtual force. Compared with prior art, accordingto the invention, the method herein has high efficiency, can be better adaptive to complex environments that have barriers, can circumvent sudden barriers in the environment without collision among unmanned aerial vehicles, ensures good formation in flight, and ensures that the formation returns to the original reference track after circumventing the barrier.

The invention discloses a spacecraft formation flying relative position cooperative control method based on event triggering. The spacecraft formation flying relative position cooperative control method based on event triggering comprises the steps of: establishing a relative position error dynamics model of a spacecraft formation flying process by considering that an external disturbance condition exists; on the basis of a graph theory, performing communication condition description on a spacecraft formation flying system; by considering that communication resources are limited, designing a virtual speed controller based on an event triggering strategy; and designing actual control input based on the virtual speed controller. By means of the method, the formation configuration is kept same while overall position maneuvering of formation spacecrafts is realized; and furthermore, the method has the advantages of being high in anti-interference capability, effectively reducing the communication capacity between the formation spacecrafts and the like, and is suitable for spacecraft formation flying relative position cooperative control.

The invention provides a multi-AUV formation optimization control method under an obstacle environment, and belongs to the technical field of ship control. A path tracking error model is established based on a sight distance navigation method, a path tracking controller is designed by adopting a feedback linear method, a multi-AUV communication topological relation and a coordination error model are established by utilizing a graph theory, and a speed coordination controller is designed, so that the formation control is achieved, and a formation optimization obstacle avoidance strategy considering the environment constraints is designed according to the obstacle environment, the optimal formation topological structure is obtained through solving the environment fitness function, so that the formation can pass through the region in the obstacle environment in an optimal formation mode.

The invention discloses a Bayesian network compensation method for thermal error of a numerical control machine tool, which comprises the following steps: (1) a Bayesian network thermal error prediction model is constructed according to measured sample data; and (2) the real-time compensation of the thermal error of the machine tool is realized according to the prediction result of the Bayesian network model. The compensation system of the invention has a simple structure and reliable application; and the adopted Bayesian network modeling method, on one hand, uses the language of a graph theory to intuitively express the causal dependency relation among various factors which produce the thermal error, on the other hand, analyzes and utilizes the inherent correlation among the factors according to the principle of probability theory to reduce the calculation complexity of inferential prediction, and has the characteristics of intuitive expression, high modeling accuracy and self-adaptation.

The invention discloses an entity attribute information extraction method and device based on syntactic dependency. The method comprises the steps that firstly, a to-be-extracted text is preprocessedto obtain a to-be-extracted text entity; then, according to the syntactic dependency and the part-of-speech relation of the to-be-extracted text, an undirected weighted graph between words is established, and candidate attribute information of the to-be-extracted text entity is obtained according to the part-of-speech relation; the shortest path between the to-be-extracted text entity and the words of the candidate attribute information is searched for, and the words passing through the shortest path form an association information word set; finally, the semantic similarity between each attribute in the attribute set and the association information word set is calculated, an entity attribute is obtained, and the entity, the entity attribute and the attribute information are integrated to serve as a final extraction result. The natural language processing technology and the graph theory model are combined, the ambiguity of text information is solved, and the text extraction accuracy isimproved; the semantic similarity of the keywords is utilized, the attributes of the abstract information are automatically summarized, and the extraction efficiency is improved.

The invention belongs to the numerical control machine tool technology field and relates to a numerical control machine tool fault diagnosis method. The method comprises the following steps of 1, dividing a system part into n component; and establishing a corresponding relation of each component and fault time and a fault propagation relation among the components; 2, establishing a component fault propagation digraph and describing a numerical control machine tool system component fault propagation digraph; 3, calculating a numerical control machine tool system component fault influence; 4, converting the fault propagation digraph into a fault-propagation hierarchical model; 5, modeling based on a numerical control machine tool system component failure rate related to time; and 6, positioning a fault main cause and carrying out numerical control machine tool fault diagnosis. In the invention, a system component fault propagation hierarchy relation and the fault propagation influence are considered and a fault time correlation influence of the system component during component failure rate determination is also considered; component fault modeling accuracy is increased; compared to traditional system component fault incidence rate diagnosis based on a graph theory or single data driving, the method possesses real-time performance and accords with realities.

The invention discloses an intelligent control method for earth pressure balance shield machine tunnel piercing parameters. The intelligent control method is characterized by comprising the following steps of (S1) collecting data and extracting factor nodes affecting shield machine piercing performance, (S2) constructing a topology structure for the factor nodes affecting the shield machine piercing performance to acquire a fuzzy association matrix Wij of each node, (S3) constructing a fuzzy control network map of the earth pressure balance shield mechanism piercing, and dynamically evolving and calculating a state value of each factor node at a t+1 time of period via an iteration rational formula, and (S4) conducting multi-phase decision analysis according to the fuzzy control network map to real-time analyze and control deviation rectification of the earth pressure balance shield machine tunnel piercing parameters. Expert prior knowledge, fuzzy logic and graph theory technologies are employed and ratiocination and real-time analysis and decision make are provided for multi-phase shield machine parameters before, amid and after subway shield machine engineering construction under complicate environment.

The invention relates to a formation satellite configuration containment control method, in particular, a formation satellite finite-time configuration containment control method. The objective of the invention is to solve the problem of low robustness of an existing multiple-satellite system formation control method and the problem of incapability of completely adapting to a practical application environment which is caused by a situation that inter-satellite communication topology is an undirected graph in the existing multiple-satellite system formation control method. The formation satellite finite-time configuration containment control method includes the following steps that: a relative orbit dynamic model of formation satellites i of a satellite formation system and relative reference points is established according to an established relative motion dynamic equation of reference satellites and accompanying satellites, and is simplified as an expression described in the descriptions; a weighted adjacent matrix A and a Laplacian matrix in the graph theory of a directed graph in the satellite formation system are provided according to the formation types of the formation satellites i; and a distributed finite-time configuration containment control laws of the multi-dynamic-pilot-satellite satellite formation system are designed, and therefore, each following satellite can achieve at a configuration convex hull formed by pilot satellites in finite time, and formation satellite finite-time configuration containment control can be realized. The formation satellite finite-time configuration containment control method of the invention is applicable to the control field of formation satellite configuration.

The invention discloses a terminal sector dividing method based on the graph theory and the spectral clustering algorithm. The method is carried out with the help of a computer system which comprises a sector dividing subsystem. The terminal sector dividing method comprises the first step of putting forward a calculating model of a peak connection degree according to the basic airline network structure and air traffic flow in controlled airspace, the second step of effectively dividing peaks of an airspace image based on the spectral clustering algorithm to solve the problem of a division error in short-distance parallel air routes and to achieve construction and division of a sector convex hull, the third step of putting forward a boundary optimized path selection algorithm based on sectors of an MAKLINK image, and the last step of carrying out optimizing to eliminate a sawtooth shape of the boundaries of the sectors to some degree to enable the sector boundaries to be more conform to actual operations so that the final dividing of the sectors can be finished. By means of air traffic flow, reverse deduction is carried out conveniently while the sectors are divided. By means of the terminal sector dividing method based on the graph theory and the spectral clustering algorithm, flows of the sectors are balanced, coordination is small, minimum distance constraint is met, the difficulty of commanding of a controller is reduced, and the security of operation in the terminal area is guaranteed.

A biometric handwriting identification system converts characters and a writing sample into mathematical graphs. The graphs comprise enough information to capture the features of handwriting that are unique to each individual. Optical character recognition (OCR) techniques can then be used to identify these features in the handwriting sample so that drafts from two different samples can be aligned to compare to determine if the features in the writing sample correlate with each other.

The invention discloses a method and a system for predicting power of a microgrid group. The method comprises steps: a microgrid graph theory model is built according to a communication relation between sub microgrids in the microgrid group; according to an intelligent agent node consistency theory and in combination with a micro Calman filter prediction algorithm, a power prediction algorithm for distributed prediction for needed power by a total grid of the microgrid group is determined; on the basis of the already-built communication relation graph theory topology, each sub microgrid in the microgrid group integrates grid needed power information of a local sub microgrid system and an adjacent sub microgrid system and uses a prediction algorithm to distributively perform short-term prediction on the needed power by the total grid of the microgrid group in the local sub microgrid system. Short-term prediction is carried out on the overall grid needed power of the microgrid group formed by multiple microgrids, and strong guarantee is provided for aspects of stable operation and power dispatching for the microgrid group power sharing system.

The invention discloses a method and system for automatically extracting a building outline of a static three-dimensional map, and relates to the field of geographic information technology. The methodincludes the steps of loading a three-dimensional model in blocks according to the frame buffer size and the map resolution; obtaining a color buffer of a single building object by using a depth buffer partitioning algorithm; performing edge detection by using a Canny operator; then performing edge processing and connecting straight line segments; and next, based on the graph theory, taking a line segment as a vertex and the connection probability of the line segment as the weight of an arc, grouping the line segments by a perceptual organization method, and extracting the outline of a building model. The method and system in the invention can automatically and reliably extract the building outline in the static three-dimensional map from any angle of view.

A construction method of a personalized learning feature model based on a knowledge graph comprises the steps: constructing a course-oriented knowledge graph, wherein entities correspond to knowledgepoints and learning resources; describing a relationship between knowledge point entities by adopting a directed acyclic graph; describing and learning a relationship between resource entities by utilizing a Bloom cognitive hierarchy; constructing a student personalized cognitive model, and adopting transfer learning to solve the problem of scarcity of personalized information of a single student;adopting active learning to solve the value evaluation problem of the selected data; and constructing a dynamically evolved student personalized cognitive model by utilizing a Markov chain theory. The invention discloses a construction method of a personalized learning feature model based on a knowledge graph. By comprehensively utilizing the knowledge graph, the graph theory, the Markov chain, the Bloom cognitive hierarchy theory and other methods, the personalized learning characteristics of the students are effectively positioned, the accuracy of positioning the personalized characteristics of the students is improved, and therefore quantitative decision support is provided for improving the learning efficiency and the teaching effect.

The invention provides a key transmission section identification-based cascading failure analysis method for an alternating current/direct current power network. The method comprises the following steps: (A) searching all transmission sections between a direct current transmitting end and a direct current receiving end by a graph theory-based transmission section traversal algorithm, forming a node set S0={vS} from a node vS of the direct current transmitting end, searching all cut sets of branches between S0 and the adjacent point thereof, and finishing traversal searching in a manner of expanding the node set S0 outwards step by step; (B) further identifying key transmission sections which can cause a relatively large cascading failure risk by indexes of a power flow transfer coefficient and section maximum overload rate; and (C) giving cascading failure sets with relatively large risks and key branches which should be mainly monitored in the key transmission sections through transient stability calculation. By the method provided by the invention, the key transmission sections and the key braches, which are prone to cascading failures after a direct current monopole is locked can be effectively determined.

The invention relates to the technology of topology analysis in the field of an electric power system, and specifically relates to a method for rapid topology analysis and the establishment of a topological island based on a graph theory. The method includes three steps: modeling, generating topology points, and generating the topological island. According to the method, topology analysis of the electric power system can be conducted via a graph theory recognition analysis method; advantages and disadvantages of breadth and depth first search algorithms can be comprehensively considered, and search advantages of depth first for a ring network are fully used; rapid topology analysis of the electric power network and the establishment of the topological island are realized, and the accuracy and rapidity of the topology analysis result of the electric power network are greatly improved.

The invention relates to an automatic order arranging and scheduling method in warehouse management. Firstly, goods are stored according to preset rules and order information is managed. Secondly, theroute planning management is carried out according to the storage situation of goods and the order information. In the path planning management, by introducing the TSP problem in graph theory, multi-AGV path planning is carried out for orders with large demand, and a collision-free and coordinated path is planned for each AGV by using the time window and one-way directed graph method, so as to eliminate collision and deadlock in multi-AGV path planning. For the orders with small demand, the single AGV path planning is carried out, and the TSP problem in graph theory is used to solve the problem, so as to achieve the shortest total distance. The invention can save time and improve the picking efficiency.