38 results about "Network decomposition" patented technology

The invention discloses a multi-AGV scheduling method based on petri network decomposition. The method comprises the following steps: step 1, converting a warehouse topological graph into a collision-free petri network model; decomposing the whole petri network model into sub-networks according to the drivable route of the single AGV; step 2, adopting a Dijkstra algorithm to realize global shortest path planning of the single AGV, and further adjusting the obtained algorithm according to the actual motion condition of the vehicle; step 3, establishing a target function; step 4, taking a staticshortest path obtained by a single AGV in each sub-network as a basis; using an external point penalty function method to carry out path iteration, obtaining collision and deadlock problems existingin the operation process of multiple AGVs, analyzing and locally optimizing the types of collision and deadlock, locally optimizing the path by taking time optimization as a principle, and generatingan optimal collision-free scheduling scheme. The method is high in operation efficiency, high in reaction speed and high in adaptability.

Gauss-Seidel-Patel Loadflow (GSPL) loadflow calculation method is invented involving self-iteration over a node within global iteration over (n−1) nodes in n-node power network. Also invented is a network decomposition technique referred to as Suresh's diakoptics that determines a sub-network for each node involving directly connected nodes referred to as level-1 nodes and their directly connected nodes referred to as level-2 nodes, wherein the level of outward connectivity for local solution of a sub-network around a given node is to be determined experimentally. Sub-networks are solved in parallel, and local solution of sub networks are related into network wide global solution using an invented technique. These led to the invention of the best possible parallel computer—a server-processor parallel-processors architecture wherein each of the parallel processors communicate only with the server processor, commonly shared memory locations, and each processor's private memory locations but not among themselves.

The invention provides a time series data missing value automatic filling method, system and device. Through a random mask and a neural network decomposition technology, the time sequence data is decomposed into superposition of different modes, and automatic feature extraction is realized. Therefore, a more accurate and effective end-to-end time series data missing value filling method is constructed. The method comprises three steps of data preparation, model training and model use. In the data preparation step, original time series data is acquired for data preprocessing, a random mask is constructed according to a given missing rate, and the newly generated random mask and the corresponding original data are used as a new data set. In the model training step, the new data set generatedin the data preparation step is used for model training so as to construct a model based on neural network decomposition. In the model using step, corresponding masks are constructed for the time series data with missing values, and the trained model is used for filling the missing values of the time series data.

The invention relates to a preset protection method for a power communication network. The network topology of the power communication network combined with the chain and the grid is analyzed; such atype of power communication network is jointly protected based on the chain protection algorithm and the P-circle algorithm. The preset protection method for the power communication network comprisesthe steps of network decomposition, basic protection path generation, service flow analysis, and configuration protection path. Firstly, the network topology is input, a clustering coefficient of eachnode is calculated, and the network is decomposed by using the clustering coefficient; then, based on the P-circle algorithm and the chain protection algorithm, a basic protection path is generated;finally, a protection path is configured for the network by analyzing the traffic. The preset protection method for the power communication network in the invention is based on the chain protection algorithm and the P-circle algorithm and is suitable for the preset protection of the power communication network combined with the chain and the grid, thereby improving the network protection efficiency and reducing the network redundancy.

The invention provides a power distribution network state estimation method based on network decomposition. The method comprises the following steps that a power distribution network is decomposed; sub-network state variable initialization is carried out; loop iteration solving is carried out; constraint condition equivalent measuration weight is computed; a sub-network state variable is solved; whether a convergence condition is met is judged, if yes, iteration is completed, and power distribution network state estimation results are output; and otherwise, 1 is added to iteration times automatically, and loop iteration solving is carried out. The applicability of a state estimation algorithm is improved, a large network can be subjected to state estimation, by network decomposition, the data scale of a node admittance matrix is lowered, the storage space requirements and computing complexity are lowered, for the large network, compared with direct computing, computing speed is high, and efficiency is high.

The invention discloses a heterogeneous network frame topology mapping method for offline and online data of a power grid, which is characterized by comprising the following steps of: decomposing a primary equipment topology network of a power grid into two stages of networks according to electrical characteristics of primary equipment of the power grid and inherent characteristics of the power grid; wherein the first-layer network is composed of a plant station and a line to form a plant-station-level topological network; the topology network is homologous and isomorphic, and subnet isomorphic algorithm topology mapping of the graph theory is applied; wherein the second-layer network is composed of primary equipment of each plant station, and the offline data and the online data form a topological network according to the connection relationship between the primary equipment and the secondary equipment; and expanding the topological networks of the plant stations and the lines of thefirst-layer network to the topological network of the primary equipment by the first-layer network and the second-layer network through the connection relationship between the bus and the lines, so that the whole-network topological mapping of offline and online data is realized, and the mapping from the node correspondence of the primary equipment of the offline data and the online data to the whole-network topological network is realized.

A method and device for implementing fault diagnosis, comprising: in the case of receiving a reported communication line (LOC) alarm, decomposing the connection network involved in the LOC alarm into at least two corresponding network elements and at least one unit link; Path detection is performed on each network element and unit link obtained through decomposition; fault diagnosis results are generated according to the path detection of all network elements and unit links. Wherein, the unit link is composed of two adjacent network elements: the line between the network node interface (NNI) of the outgoing port of the westbound network element and the NNI of the incoming port of the eastbound network element. The embodiment of the present invention simplifies the process of fault diagnosis and improves the efficiency of fault diagnosis.

The invention relates to a parallelized distribution network reconfiguration method and system. The distribution network reconfiguration problem is divided into three stages: network decomposition, ring-level reconfiguration and merging process, and the parallelized distribution network reconfiguration system is divided into three stages. The number of sub-networks is the same as the number of loops, the ring-level reconstruction model of each sub-network is established, and the branch switching method is used to calculate the open state of the tie switch and the open state of the segment switch in each sub-network, and extract all sub-networks. The open state of the tie switch of the uncompressed loop in the network and the open state of the segmented switch constitute the reconstruction result of the parallelized distribution network, which realizes the parallelized network reconstruction and effectively reduces the calculation time of the network reconstruction. Improve the efficiency of network reconstruction.

The invention discloses a water transportation pipe network calculation method based on the node parameterization technology, and relates to the field of water conservancy. The method comprises the steps of initializing a pipe network system to be tested; decomposing the initialized pipe network system to be tested into parameterization nodes and a calculation pipeline connected between two adjacent parameterization nodes; by calculating pipeline connection parameters and node connection parameters, connecting and combining the calculation pipeline with the parameterization nodes; judging whether the current calculation time is a model control end time or not, and if yes, completing calculation of the whole pipe network with pressure in the pipe network system to be tested at the current time; if not, executing the step 1 again till the current calculation time is the end time, and completing calculation of the whole pipe network with pressure in the pipe network system to be tested at the current time. According to the water transportation pipe network calculation method, on the basis of pipe network decomposition and rapid calculation, analog calculation precision can be well ensured, and the calculation result is as good as that of business software Hammer.

The invention relates to a parallelized power distribution network reconstruction method and system, and the method comprises the steps: dividing a power distribution network reconstruction problem into three stages: a network decomposition process, a ring-level reconstruction process and a merging process, dividing the parallelized power distribution network reconstruction system into sub-networks with the same number as loops, building a ring-level reconstruction model of each sub-network, adopting a branch switching method, calculating the on-off state of the interconnection switch and the on-off state of the section switch in each sub-network, extracting the on-off states of the interconnection switches and the on-off states of the section switches of the uncompressed loops in all the sub-networks to form the reconstruction result of the parallel power distribution network, so that parallel network reconstruction is achieved, the calculation time of network reconstruction is effectively shortened, and the network reconstruction efficiency is improved.

The invention belongs to the field of aircraft EWIS system wiring design. Provide an automatic wiring design method based on aircraft network decomposition structure, including: step 1: system principle design, design data conversion based on system interface control document (ICD), automatically generate electrical principle model; step 2: aircraft wiring design, based on Decomposition calculation of aircraft wiring network topology, automatic definition of physical wiring harness topology model; step 3: wiring installation design, based on space reservation design of aircraft wiring network structure, establishment of aircraft wiring network structure model and segmental decomposition model of wiring harness products; step 4: Aircraft circuit design, based on the data synthesis of the system electrical principle model and the physical wiring harness topology model, the aircraft circuit model is automatically generated; Step 5: Wire harness product design, based on the topological data of the three-dimensional physical model of the wiring harness and the wiring data of the wiring harness in the aircraft circuit model Extract and automatically generate wire harness product models.

The invention discloses a data collection method for an energy heterogeneous wireless sensor network, which includes the following steps: (1) establishing a corresponding relationship between voltage and power in the network measurement stage, and then collecting voltage information of sensor nodes through an initial routing tree to estimate the power, At the same time, the neighbor information of nodes is collected to construct the network topology. (2) In the network decomposition stage, the network is divided into 2-connected sub-networks according to the topology information. (3) In the subnetwork solution stage, the routing structure of the subnetwork is found by establishing an integer linear programming problem. (4) The route distribution stage distributes the routing structure to the network, and the node updates the routing structure to send data to the sink node. The invention can be used in sensor networks with different remaining power of nodes, and can quickly build a routing structure with the longest survival time.

The invention discloses a probabilistic neural network-based equipment analog circuit fault diagnosis method, comprising the following steps: S1: constructing a probabilistic neural network model for analog circuit fault diagnosis; Decompose and screen out the useful components; S3: calculate the BCM value of the useful components, and construct the corresponding fault feature vector; S4: use the fault feature vector based on the training samples to train the probabilistic neural network model, and set The minimum optimal probability value Z, optimize the three types of parameters until the fault state set output by the model meets the predetermined requirements, and save the training results; S5: Construct the corresponding fault feature vector of the test samples according to the operations of steps S2 and S3, and input Fault diagnosis is carried out in the probabilistic neural network model trained in step S4. The circuit fault diagnosis method in the present invention provides a technical approach for the selection of fault categories in fault diagnosis.

A large-scale bridge network connectivity probability assessment method based on network decomposition, relating to a bridge network assessment method. Apply the multi-level k-way partition algorithm to recursively divide the bridge network into multiple subnets in series; define the adjacent components and local networks of the subnetwork and build the adjacency matrix respectively, and divide the subnetwork status into subnet connected, subnet unconnected, etc. Connected but the network as a whole may be connected, the subnet is not connected and the network as a whole is not connected, the probability of each state is calculated, and the subnet is not connected and the network as a whole is not connected during the calculation. According to the connection status of the subnet terminal nodes, the The minimum item that belongs to the subnetwork is not connected but the network as a whole may be connected is further divided into multiple categories, and all terminal nodes in the subnetwork are connected to each other; the terminal nodes of each subnetwork and the edges between the subnetworks are further simplified into a simplified network , the sum of the overall connectivity of the simplified network is obtained to obtain the connectivity probability of the bridge network.

The present invention relates to an open fronthaul device and a network system comprising same, the open fronthaul device and the network system comprising same, according to the present invention, being able to realize, as software, various network functions, while not being locked in to a vendor, by applying network dis-aggregation to a wired and wireless network.

This application discloses a UUV cluster self-organizing network method and system based on underwater acoustic communication. The self-organizing network method includes: network establishment: multiple UUV nodes select a master node through a competition mechanism, and other UUV nodes are automatically configured as slaves Node, establish UUV cluster ad hoc network; network merging: two or more ad hoc networks are merged; network decomposition: the master node of the network to be decomposed transmits an underwater acoustic network decomposition signal, and performs network exit according to the underwater acoustic network decomposition signal. After exiting, the node re-establishes the self-organizing network according to the network establishment mechanism; network reconstruction: when the master node of the UUV cluster self-organizing network is damaged or missing, the competition mechanism re-selects the master node, and other UUV nodes are automatically configured as slave nodes. Reconstruct the UUV swarm ad hoc network. Combining centralized and distributed UUV clusters, it has the characteristics of autonomous state transition, data exchange, resource sharing, etc. It supports node join / exit mechanism and network merge / decompose mechanism within the range of acoustic action distance.

The present invention relates to a social network key node discovery method and system based on network decomposition, belonging to the technical field of network analysis. The method comprises the steps of: primarily determining a candidate key node set according to the central value of each node in the network, and determining the key nodes of the social network according to the communicating branch node quantity of the candidate key nodes in the network. The social network key node discovery method and system overcome the influence of the connection sides between the adjacent nodes on the network destroy capacity, design more accurate node central indexes, select more reasonable node replacing policy, do not need parameter arrangement, and are more efficient and accurate in social network key node discovery.

The present invention proposes an essential image analysis method based on multi-scale attention and label loss, introduces the circular convolution attention mechanism and confrontation idea into the essential decomposition problem, and constructs a multi-scale attention MSA for essential image analysis Net network, the network structure follows the basic framework of the Generative Adversarial Network (GAN), including two parts, the generator and the discriminator. The generator consists of two parts: attention subnetwork and codec subnetwork, which are used to decompose the image into reflection map and light map. The role of the discriminator is to give the probability that the image is the correct essential image for any input image. At the same time, the present invention also provides a new label loss function for improving the reflection map decomposition effect. The loss function is constructed based on the label image (ground truth) in the data set, which can make the reflection map obtained by network decomposition have better local Texture consistency effects and quantitative evaluation metrics.