In this thesis , two on - line algorithms for providing qos tuning at the intermediate nodes are proposed 本論文中提出兩種線上演算法,目的在中間點上作調(diào)整以提供有保證的服務(wù)品質(zhì)。
This paper continues to survey the progress on semi on - line algorithms on parallel machine scheduling problems and studies the relation between different semi on line scheduling problems 摘要繼續(xù)介紹半在線平行機排序問題的研究進展。主要介紹第二類、第三類半在線模型。研究兩個(或兩個以上)半在線模型間關(guān)系:復(fù)合與限制。文章最后給出了一些待研究的問題。
In this paper , we study an on - line version of the two - dimensional bin packing problem that is the problem of packing a list of rectangular items into a minimum number of unit - square bins in an on - line manner . an on - line algorithm called rtdh ( refined two dimensional harmonic ) is proposed and analyzed . we show that rtdh can achieve an asymptotic worst - case ratio of less than 2 . 7687 , which beats the best - known bound 2 . 85958 目前,對該問題的研究有各種算法,主要有harmonic和round算法,本文針對harmonic和round算法存在的問題,提出一種算法rtdh ( refinedtwodimensionalharmonic ) ,做了相應(yīng)的分析,并且給出了該算法的最壞性能比是2 . 7687的證明,這個結(jié)果刷新了目前最好的結(jié)果2 . 85958 。
This method utilizes an on - line algorithm based upon lssvm ( least square support vector machine ) , which can build adaptive models to predict the cod values of unknown water samples quickly and accurately . in the modeling process , every training sample is also assigned a prior weight to take their significance to the final predictive model into account 該方法是一種基于最小二乘支持向量機的在線自適應(yīng)加權(quán)算法,這種算法可以自適應(yīng)地選取和未知水樣最相近的標(biāo)準(zhǔn)樣本進行建模,同時在建模中又利用加權(quán)的方法分別考慮了各個標(biāo)準(zhǔn)樣本重要性。