38 results about "Network decomposition" patented technology

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.

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 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.

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.

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.