翻訳と辞書 Words near each other ・ FitzAlan ・ Fitzalan Chapel ・ Fitzalan High School ・ Fitzalan Pursuivant Extraordinary ・ Fitzalan Square ・ Fitzbek ・ Fitzcarrald District ・ Fitzcarraldo ・ Fitzcarraldo (disambiguation) ・ Fitzcarraldo (Frames album) ・ FitzClarence ・ Fitness function ・ Fitness International ・ Fitness landscape ・ Fitness model ・ Fitness model (network theory) ・ Fitness Olympia ・ Fitness professional ・ Fitness proportionate selection ・ Fitness Report ・ Fitness Republic ・ Fitness to dive ・ Fitness to plead ・ Fitness to Practice ・ Fitness Tour ・ Fitness trail ・ Fitness Universe ・ FitNesse ・ Fitnete Rexha ・ Fito & Fitipaldis Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Fitness model (network theory) ： ウィキペディア英語版 Fitness model (network theory) In complex network theory, the fitness model is a model of the evolution of a network: how the links between nodes change over time depends on the fitness of nodes. Fitter nodes attract more links at the expense of less fit nodes. It has been used to model the network structure of the World Wide Web. ==Description of the model== The model is based on the idea of fitness, an inherent competitive factor that nodes may have, capable of affecting the network's evolution.〔Albert R. and Barabási A.-L., "Statistical mechanics of complex networks", ''Reviews of Modern Physics'' 74, 47 (2002)〕 According to this idea, the nodes' intrinsic ability to attract links in the network varies from node to node, the most efficient (or "fit") being able to gather more edges in the expense of others. In that sense, not all nodes are identical to each other, and they claim their degree increase according to the fitness they possess every time. The fitness factors of all the nodes composing the network may form a distribution ρ(η) characteristic of the system been studied. Bianconi and Barabási〔Bianconi Ginestra and Barabási A.-L., 2001a, ''Europhys. Lett.'' 54, 436.〕 proposed a new model called Bianconi-Barabasi model, a variant to the Barabási-Albert model (BA model), where the probability for a node to connect to another one is supplied with a term expressing the fitness of the node involved. The fitness parameter is time independent and is multiplicative to the probability : $\backslash Pi\_i\; =\; \backslash frac.$ Thus, the system of equations for the time evolution of the degrees $k\_$ according to the continuum theory introduced by the same model will have the form : $\backslash frac\; =\; m\backslash Pi\_\; =\; m\backslash frac\}k\_\}$ where ''m'' the number of edges the newly coming node has. If we require the solution to have a similar form to the one it had without the insertion of the fitness factors (to avoid ruining the power-law degree distribution of scale-free networks), then the exponent of the solution has to change and become fitness dependent : $k\_(t,t\_)\; =\; m\backslash left(\backslash frac\backslash right)^$ where : $\backslash beta(\backslash eta)\; =\; \backslash frac\backslash mboxC\; =\; \backslash int\backslash rho(\backslash eta)\backslash frac\backslash ,d\backslash eta.$ Hence, the more fit nodes increase their degree faster than the less ones. This characteristic attributes the network with a different behavior regarding its evolution. Without the introduction of the fitness property, all nodes had the same exponent in the power-law degree evolution formula. This means that the older nodes in the system would have more edges compared to newcoming ones. After the fitness property is introduced, this exponent, and accordingly, the slope of $k(t)$ change, giving thus the opportunity to newcoming nodes to dominate the system. It was seen through this example how can a network's evolution change behavior through the introduction of a new parameter in the model. However, we require the network to preserve its overall scale-free character. By forcing the fitness dependence to be accumulated in the exponent only, the degree-distribution will still be a power-law relationship, composed though by a weighted sum of different power-law in degree-evolution formulas : $P(k)\; \backslash sim\; \backslash int\backslash rho(\backslash eta)\backslash frac(m/k)^\backslash ,d\backslash eta$ where ρ(η) is the fitness distribution depending on the system's composition The fitness model can be extended to in corporate additional processes, such as internal edges, which affect the exponents.〔Ergun, G. and G. J. Rodgers, ''Physica A'' 303 (2002) 261–272〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Fitness model (network theory)」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.