73 results about "Small-world network" patented technology

The present invention discloses a social network based message propagation model, which is a method, based on the special line of the crowd in the network and the average degree of the nodes in the social network, for carrying out modeling analysis on message propagation in the social network and proposing a node importance based rumor immune strategy. The dynamic equations of the <k> SLIR message propagation model are established in the small-world network; by virtue of the method disclosed by the present invention, influences of nodes in various states in the social network, on message propagation can be realistically taken into consideration; and according to the node importance based improved rumor immune strategy proposed by the present invention, propagation of rumors in social network can be better inhibited.

The present invention relates to a new network architecture and its data transmission method based on percolation. The disclosed network architecture is a server-free and router-free network structure, wherein efficient routing can be operated with percolations based on the six degrees of separation theory in small world network modeling. An information transmission will be divided into two phases: routing phase and data transmission phase. In the routing phase, probe packets will be transmitted and forwarded in the network thus path selections are performed based on small-world strategy. In the second phase, the information will be encoded and transmitted using the paths selected at the first phase. In such a way, an efficient routing and data transmission mechanism can be built which allow us to construct a low-cost, flexible and ubiquitous network.

The method of the present invention provides an automatic and optimised selection of the network topology for distributing scheduling of jobs on the computers of the modified network topology. The automatic and optimised selection of the network topology starts from the current topology and a desired number of additional connections. In this way the method of the present invention provides a higher convergence speed for the modified consensus algorithm in comparison, e.g., to a simple ring network. The method exploits the so called small-world networks. Small-world networks are more robust to perturbations than other network architectures. The preferred embodiment provides a workload scheduling system which is highly scalable to accommodate increasing workloads within a heterogeneous distributed computing environment. A modified average consensus algorithm is used to distribute network traffic and jobs amongst a plurality of computers.

The invention discloses a method and a system for optimally dispatching cascade reservoirs on the basis of quantum-behaved particle swarm algorithms. The method includes acquiring initialized population according to established objective functions for solving problems for optimally dispatching the cascade reservoirs and utilizing the initialized population as parent-generation particles; constructing small-world networks to obtain adjacent matrixes; updating the parent-generation particles according to the adjacent matrixes and generating child-generation particles; computing the fitness of the child-generation particles according to fitness functions; comparing the fitness of the parent-generation particles to the fitness of the child-generation particles by the aid of competition operators, selecting the child-generation particles with the good fitness and utilizing the selected child-generation particles as parent-generation particles for next iteration; judging whether current iteration numbers are larger than the maximum thresholds or not; carrying out computation if the current iteration numbers are larger than the maximum thresholds and outputting cascade reservoir optimal dispatching computation results. The method and the system have the advantages that the quantum-behaved particle swarm algorithms are improved by small-world network models, so that the population diversity can be kept by improved algorithms, the shortcoming of easiness in trapping in local optimization of basic quantum-behaved particle swarm algorithms can be overcome, and effects of optimally dispatching the cascade reservoirs can be improved.

The invention relates to the network and optical switching technical field and provides a method of constructing a data center switching network and a node apparatus. The method comprises the step S1 of selecting a regular polygonal crystal lattice physical topology according to a preset network scale and application demands. Each dot in the regular polygonal crystal lattice physical topology is corresponding to one optical switching node. Each side is corresponding to one or more fibers. The method further comprises the step S2 of acquiring a logical topology complying with small-world network characteristics in line with the application demands according to the regular polygonal crystal lattice physical topology. The logical topology comprises two logical planes. The first logical plane is a regular crystal plane. The second logical plane is a random graph plane composed of random sides. A data center inner switching network constructed through the method achieves any large-scale port number, random expansion and simple wiring. While the method makes a large scale and flexible expansion achieved, the method further guarantees a relatively high Internet bandwidth and a relatively low average time delay between any two servers.

The invention discloses a myoelectricity classification method based on an improved small-world echo state network. Firstly, a small-world network is used for improving a reserve pool structure of theESN, then an edge adding probability is used for improving the small-world network, and the network is called as an improved small-world echo state network, so that the adaptability of a reserve poolis improved, and the generalization ability and stability of the ESN are improved. Then, the output weight of the network can be obtained by training the network, and the output weight is used as a corresponding feature. Electromyographic signals of six actions of falling down, walking, sitting, squatting, going upstairs and going downstairs are collected, corresponding features are extracted through ISWLESN, and then feature dimensions are reduced through PCV. And finally, the performance of the network features is represented by using the scatter diagram, the class separability index and the DBI. Results show that ISWLESN has good clustering performance, and has high precision when used for support vector machine classification.

The invention discloses a comprehensive assessment method for vulnerability of high-voltage transmission lines in a freezing disaster, and belongs to the technical field of power grid safety analysis. The assessment method comprises: for a small world network based high-voltage transmission line vulnerability analysis result, a Monte-Carlo weather sampling based high-voltage transmission line freezing disaster vulnerability analysis result, and an expert scoring based high-voltage transmission line freezing disaster vulnerability analysis result, conducting united-decision by using a DS evidence fusion theory, and taking a final fusion result as a comprehensive index for assessing the vulnerability of the high-voltage transmission lines in the freezing disaster; and then, according to the value of the index, removing lines with relatively high vulnerability, and calculating a lost load percentage of a power system, thereby finally determining the vulnerability of the high-voltage transmission lines in the freezing disaster. The assessment method has the advantages that the method is a fused decision of a plurality of theories or methods, the accuracy of assessment of a power grid system on the vulnerability of the high-voltage transmission lines in the freezing disaster is improved, and an effective basis is provided for high-voltage transmission line inspection.

A chaotic secret communication system based on a digital chaotic coding algorithm comprises (1) a channel used for enabling an information sending end A to be communicated with an information receiving end B and (2) digital chaotic networks connected with the channel and used for generating chaotic numerical codes. A function g1 is generated through codes of chaotic coding according to the selected chaotic numerical codes with certain lengths from the numerical codes generated in the digital chaotic networks and converted to a chaotic code k1(t), wherein an equation that k1(t)=g1(X, p) is satisfied. The digital chaotic networks are characterized in that (1) the digital chaotic networks are identical in topologic and dynamics structures, driven by common signals and in a chaotic synchronic state, the digital chaotic networks comprise a complex chaotic network which is of a random topologic structure, a regular network, a random network, a small-world network, a freedom scaling network and a module network; (2) the information sending end A is used for complex chaotic networks which generate the chaotic numerical codes and a kinetic equation is decrypted by a differential kinetic equation.

The invention provides a wireless digital image transmission system based on Android in the field of electronic information science and technology, which comprises a construction and configuration unit of a server, a communication unit of a server and a client, a client data processing unit and a display unit of a client image file. Under the Small World Network, The server can implement the function of sharing image files with multiple clients, That is, the client can download the image file of the server synchronously for display, and upload the local image file to the server for sharing with other clients, and the Android device with various screen resolutions has no adaptation problem, which has certain practical value for meetings and teaching in small and medium-sized occasions.

The invention discloses a fractional order PD controller design method based on an N-W small world network model. The method comprises steps that firstly, the stability characteristics and the balancepoint information of the N-W small world network model are analyzed; secondly, a fractional order PD controller is applied to the N-W small world network model, and a balance point is solved; thirdly, the controlled N-W small world network model is linearized at the balance point, and characteristic equations of the linearized controlled N-W small world network model are obtained; and lastly, delay parameters are selected as bifurcation parameters, and stability analysis and bifurcation analysis of the characteristic equations of the linearized N-W small world network model are carried out, proper fractional PD controller parameters are selected, and the controlled N-W small world network model is stabilized at the balance point. The method is advantaged in that relatively strong applicability is realized, generation of bifurcation can be effectively controlled by a fractional-order PD controller, so critical bifurcation is made ahead or lag.

The embodiment of the present invention discloses a multi-regional economic scheduling method based on the improved quantum particle swarm algorithm. The improvement of the quantum particle swarm algorithm by using the NW small world network can improve the shortcoming that the basic quantum particle swarm is easy to fall into a local optimum in the optimization process. The method in the embodiment of the present invention includes: S1: Establishing the objective function of the multi-regional economic scheduling problem; S2: Optimizing the objective function using the NW small-world network improved quantum particle swarm optimization algorithm, specifically including: S2-1: Population initialization; S2 ‑2: Build a small-world network and get the adjacency matrix; S2‑3: Update individuals and update the population; S2‑4: Calculate the fitness based on the updated population; S2‑5: Use the competition operator to adapt the parent particles Compared with the fitness of offspring particles, the one with better fitness is reserved as the parent of the next iteration; S2‑6: If the number of iterations calculated reaches the preset maximum number of iterations, calculate and output the multi-regional economic dispatch calculation If not, go to step S2‑2.

The invention discloses an image retrieval method, a device, a computing device and a medium based on a small world network. The method includes creating an image base; extracting the local features of each image in the image library; learning the local features of each image in the image library to obtain a learning dictionary; according to the learning dictionary, the eigenvector of each image in the image library is generated, and the small world network of the eigenvector is constructed; extracting local features of the target image; matching the local features of the target image with thefeatures of the image in the small world network; according to the matching result, the images that satisfy the similarity threshold condition in the image library are selected and/or the images in the image library are sorted from high to low according to the similarity measure. A learn dictionary is obtained by machine learn, and a small-world network with image characteristics is constructed according to that learn dictionary, and the small-world network is used as an image retrieval model, thereby greatly improving the processing efficiency and accuracy of image retrieval and increasing the service throughput.

An FPGA-based graph data processing method is provided for executing graph traversals on a graph having characteristics of a small-world network by using a first processor being a CPU and a second processor that is a FPGA and is in communicative connection with the first processor, wherein the first processor sends graph data to be traversed to the second processor, and obtains result data of the graph traversals from the second processor for result output after the second processor has completed the graph traversals of the graph data by executing level traversals, and the second processor comprises a sparsity processing module and a density processing module, the sparsity processing module operates in a beginning stage and/or an ending stage of the graph traversals, and the density processing module with a higher degree of parallelism than the sparsity processing module operates in the intermediate stage of the graph traversals.