The excellence and disadvantage of them are analyzed . 2 . the grset ( generate rules by using set - enumeration tree ) algorithm is proposed based on the research of predecessor Grset算法采用的是集合枚舉樹的數(shù)據(jù)結(jié)構(gòu),采用深度優(yōu)先的方法遞歸地生成關(guān)聯(lián)規(guī)則的后件。
So data warehouse technique is introduced in fault diagnosis . takes gear case as the instance , the paper uses the data mining to generate rules distinguishing the faults of gear case , and then uses these rules to diagnose unknown fault 對(duì)此,在故障診斷領(lǐng)域引入數(shù)據(jù)倉(cāng)庫(kù)技術(shù),并以齒輪箱為例,通過(guò)數(shù)據(jù)挖掘產(chǎn)生區(qū)分齒輪箱各種故障的規(guī)則,并利用這些規(guī)則來(lái)診斷未知故障。
Based on the analysis of the working principle of snort and some of its source codes , it introduces the structure of snort ' s rule database , how to generate rule trees and analyzes the processes of information collecting , parsing and rule matching after exploring the existing software and hardware technology , it puts forward an embedded ids design model based on ixp2400 network processors and describes the design scheme in detail Snort是一個(gè)輕量級(jí)的nids系統(tǒng),在嵌入式ids系統(tǒng)中的數(shù)據(jù)包分析檢測(cè)部份,擬借鑒它的部份原理和技術(shù)?;趯?duì)它工作原理及部份源碼的分析,本文介紹了snort的規(guī)則庫(kù)的結(jié)構(gòu)、規(guī)則樹生成方法,分析了其信息收集、解析和規(guī)則匹配過(guò)程。
The reasons lie in that , firstly , some ba - sic conditions are ready to generate rule of law , but rather immature ; secondly , during the process of the construction of the order of rule of law in contemporary china , only the extrinsic values and the choices of extrinsic value objectives are emphasized while the intrinsic values and the pursuit of the intrinsic values of rule of law are ignored , which make things go contrary to wishes 究其原因,一方面是中國(guó)的法治生成的一些基本條件已經(jīng)具備,但相當(dāng)不成熟,這種不成熟性就是上述現(xiàn)象產(chǎn)生的一個(gè)原因;另一方面是當(dāng)代中國(guó)在法治秩序的建構(gòu)過(guò)程中僅強(qiáng)調(diào)法治的外在價(jià)值及外在價(jià)值目標(biāo)的選擇而過(guò)分忽視法治的內(nèi)在價(jià)值及對(duì)法治的內(nèi)在價(jià)值的追求所產(chǎn)生的事與愿違的結(jié)果。
Third , generation rule device in this model also uses the genetic algorithm to generate rule . but this genetic algorithm is different from the genetic algorithm used to optimize bp nerve network . their different point is that space of solution in this genetic algorithm isn ’ t a simple number value and space of string , but a space of function 第三、該模型中的規(guī)則生成器也是使用遺傳算法來(lái)生成規(guī)則,但是這里的遺傳算法和遺傳算法優(yōu)化bp神經(jīng)網(wǎng)絡(luò)模塊中的遺傳算法不同之處在于此遺傳算法的求解空間不是簡(jiǎn)單的數(shù)值與符號(hào)空間而是函數(shù)空間,它所得到的結(jié)果不是一個(gè)簡(jiǎn)單的定長(zhǎng)字符串,而是表示待求解問(wèn)題的一個(gè)求解模型的字符串。