similarity variable 中文意思是什麼
similarity variable
解釋
相似變量- similarity : n. 1. 類似，相像，相似。2. 類似點；類似物，相似物。
- variable : adj 1 易變的，變化無常的，無定的 （opp constant steady）。2 可變的，能變的；變換的。3 【數學】變...
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When studying the network performance, flow control and resource provisioning of communication networks, traffic model plays a very important role. the recent studies show that the date network traffic is self - similar, so the markovian model, which describes telephone networks accurately, is not suitable for date networks. the self - similarity of the network traffic has severe impact on flow control and queuing analysis in date networks, therefore it has received significant attention. in this paper, g m 1 queuing model is used to analyze the queuing performance of generic variable length packet networks for the first time. the self - similar traffic is generated by multiplexing a large set of independent pareto heavy - tailed interarrival on off sources. the simulation results show that the heavy - tailed traffic results in queuing performance deterioration for variable length packet networks, which is in accordance with the analytical results for atm switches
業務量的自相似特徵顯著影響網路的流量控制與排隊分析，已經引起人們的極大重視。採用g m 1排隊模型對分組長度可變的網路的排隊性能進行了分析和模擬，其中自相似業務量是通過疊加大量獨立的到達間隔為pareto重尾分佈的on off源來生成的。模擬結果表明，自相似業務量導致網路的排隊性能劣化，這與有關文獻對atm交換的分析結果一致。 -
Cooperative objective was the mediator variable between co - workers organizational tenure similarity and supportive behaviors, and job burnout
合作性目標在員工任職期限的相似性與相互支持行為、工作倦怠之間的關系方面起完全中介作用。 -
15 lowe d. similarity metric learning for a variable - kernel classifier
提出了一種新型的人臉識別框架seir 。 -
We do researches on constructing normal model of network traffic, analysizing self - similarity of network traffics - hurst parameter, and its time variable function h ( t ). experimental analysis confirmed the validity of the novel mechanism, limiting the extent of network traffic in time and detecting the ddos attack through measuring the change of h parameter brought by the attacks. moreover we use database to refine the ddos attack
主要成果為： （ 1 ）對網路流量的自相似性? hurst參數、 hurst參數的時變函數h （ t ）進行分析，建立正常網路流量模型，比傳統的特徵匹配更準確描述了網路流量的特性； （ 2 ）通過實驗驗證了，基於正常網路流量模型，對網路流量進行實時限幅，由自相似性的變化來預測ddos攻擊方法的正確性； （ 3 ）對于不同的攻擊方式，我們使用不同的方法進行檢測，並用數據庫對流經的包頭信息進行統計分析，來對攻擊定位。
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