Evolution Mechanism And Some Dynamical Processes On Weighted Networks

Complex networks have been much interest from all research circles in the last few years.Its development caused the network to set up the renew of model. People start using variousstandpoint which constitute a network factor to change continuously to re- know a network, building up model emulation a network to evolve process and reappearing its topological attributes. Because the complexity of world, how the reality reconstructs a network to evolveprocess reasonably, and network structure as to it's whole dynamic state behavior's havinginfluence have already become the core problem that the complex network studies. Former research work mainly is the circumambience rushes toward meaning under of the network launch, relevant the research work which adds a power network very few. In this text, we will add apower network of evolve mechanism and system dynamics behavior as research objects, passestablishment model to imitate a real world network property, in the meantime make use ofcovariance theories analytical the method combine a great deal of calculator to imitate an experiment. Inquiry in to add the relation of of the power network structure and network dynamicsbehavior. These research with problem have to the influence direction which knows networkfunction and understanding network tiny view structure variety to the network whole propertyCertain theories and reality guide meaning.In chapter 1, the present condition and some hot problems of the complex network areintroduced. It is carried on a point overview towards adding a power network of the researchprogress of model and dynamics property. Moreover, conduct and actions prepares knowledge, we introduced concerning the complex network of the generous character is standard, elaborating the complex network to study a work of meaning with practical value.In chapter 2, two evolving models are proposed. Firstly, through the double preferential attachment choose method, the network which constructs the dynamic state growth of aside power evolves model, giving that model orders resolution process and number that weightdistribute to imitate a result, and make these two results and substantial evidence data a com parison, confirmed that model to match many of detection in the true network rush toward acharacteristic, the result enunciation model mainly suits to use to imitate the technical networkin the real world and living creature network. Secondly, and then through the double preferential attachment choose method constructs a network to evolve model, passing that model tomainly inquiry into a conjunction mechanism to network the edge weight distributes with theinfluence of the network relativity. To this model we gave its number emulation results.In chapter 3, based on local world(LW) model, the model evolves network from unweighted to weighted with local information is proposed. Through local world model and internal double preferential attachment choose method, built up that model, and give the strengthand weight distribute, two extreme limit circumstances of analyze a result. Carried on numberemulation to that model in the meantime, the number expanded imitated as a result predict withtheories consistently. That model exhibits an alteration from assortative networks to disassortative networks. According to changing the area of local world, it also exhibits a crossoverbetween exponential and scale-free weighted networks. These extensively adjustable propertiesthat the model displays make that model be able to imitate many true networks, which make ithaving good applied foreground.In chapter 4, the relation between the synchronous ability and weights is discussed. Weanalyze how the weights' distribute influence the network synchronous ability, and get a conclusion which weights distribute more even network synchronous ability more strong, namelythe weights distribute with quality to distribute and can even improve the synchronous ability of network than the differences. Build up model through chapter 2 and chapter 3 imitatedexperiment and calculation to confirm the credibility of that conclusion respectively.