【摘要】：態(tài)勢預(yù)測是網(wǎng)絡(luò)態(tài)勢感知的重要環(huán)節(jié),可以為網(wǎng)絡(luò)管理員提供必要的決策支撐。為了實(shí)現(xiàn)對網(wǎng)絡(luò)的大數(shù)據(jù)管理模式,針對當(dāng)前預(yù)測算法無法充分利用大數(shù)據(jù)優(yōu)勢的局限,提出了基于關(guān)聯(lián)規(guī)則的態(tài)勢預(yù)測方法。該方法綜合考慮了大數(shù)據(jù)的特點(diǎn)和態(tài)勢預(yù)測的需求,給出了方法的基本思想和實(shí)現(xiàn)流程。實(shí)驗(yàn)結(jié)果表明,提出的方法與傳統(tǒng)預(yù)測方法相比,通過尋找數(shù)據(jù)間的關(guān)聯(lián)物而不是非線性匹配來達(dá)到預(yù)測的目的,大大降低了計(jì)算的時(shí)間復(fù)雜度,提高了預(yù)測效率。
[Abstract]:Situation prediction is an important part of network situational awareness, which can provide necessary decision support for network administrators. In order to realize the big data management mode of the network, aiming at the limitation that the current prediction algorithm can not make full use of the advantage of big data, a situation prediction method based on association rules is proposed. This method considers the characteristics of big data and the demand of situation forecast, and gives the basic idea and realization flow of the method. The experimental results show that compared with the traditional prediction method, the proposed method can achieve the purpose of prediction by finding correlation objects between data rather than nonlinear matching, which greatly reduces the time complexity of calculation and improves the efficiency of prediction.
【作者單位】： 空軍工程大學(xué)信息與導(dǎo)航學(xué)院;
【基金】：陜西省科技計(jì)劃自然基金(2012JZ8005)
【分類號】：TP393.07;TP311.13

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