本文關(guān)鍵詞： 置信規(guī)則庫 粒子群算法 油品檢測 透氣度檢測 故障診斷　出處：《昆明理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：為了綜合利用人類在決策過程中的不確定信息和定性知識,實(shí)現(xiàn)復(fù)雜決策問題建模的要求,置信規(guī)則庫(Belief Rule Base,BRB)專家系統(tǒng)應(yīng)運(yùn)而生。和傳統(tǒng)IF-THEN規(guī)則相比,BRB在規(guī)則中加入了置信框架,使得可以更充分的利用各種類型的數(shù)據(jù)知識,挖掘輸入輸出之間的非線性信息,從而實(shí)現(xiàn)復(fù)雜決策問題的建模。置信規(guī)則庫專家系統(tǒng)以其智能性和多信息知識表達(dá)等優(yōu)勢,備受學(xué)者們的關(guān)注。置信規(guī)則庫允許專家直接介入,而專家知識具有主觀性,加上實(shí)際工程中的問題多是復(fù)雜的,這些都給準(zhǔn)確快速設(shè)置置信框架的參數(shù)和結(jié)構(gòu)帶來了挑戰(zhàn)。為了解決以上問題,本論文對置信規(guī)則庫專家系統(tǒng)的建模方法進(jìn)行了研究。論文的主要工作如下:(1)針對置信規(guī)則庫優(yōu)化模型求解效率差的問題,采用了一種基于粒子群智能算法的BRB參數(shù)訓(xùn)練方法。以食用油摻偽檢測問題為背景,對所提方法進(jìn)行了驗(yàn)證。相對于傳統(tǒng)參數(shù)優(yōu)化策略,粒子群優(yōu)化算法明顯提高了油品檢測BRB模型的求解效率。(2)為了克服在確定BRB結(jié)構(gòu)時(shí)專家知識的局限性,通過將前提屬性的參考值和輸出評價(jià)等級的效用作為推理模型中的待估計(jì)參數(shù),提出了結(jié)構(gòu)和參數(shù)同時(shí)優(yōu)化的 BRB 模型(Optimize Structure and Parameters of BRB,OSP-BRB)。以煙草打孔水松紙透氣度為研究對象,與相關(guān)BRB結(jié)構(gòu)辨識的方法相比,OSP-BRB更加真實(shí)的反映了透氣度的實(shí)際情況,證明了該方法可以更合理的構(gòu)建BRB結(jié)構(gòu)。(3)針對多決策因子引起的BRB規(guī)模過大的問題,基于屬性重要度,增加前提屬性權(quán)重的優(yōu)化,提出了 BRB約減模型(BRB-reduction,BRB-R)。以油浸式變壓器故障診斷為例,該方法縮減BRB規(guī)模的同時(shí),將故障診斷的正確率提高了三個(gè)百分點(diǎn),說明該方法是一種有效的屬性約減方法。針對置信規(guī)則庫專家系統(tǒng)在建模時(shí)存在的不足,從置信規(guī)則庫參數(shù)和結(jié)構(gòu)辨識,以及規(guī)模約簡三個(gè)方面進(jìn)行了研究改進(jìn),在三個(gè)領(lǐng)域的應(yīng)用效果說明了文章改進(jìn)后的建模方法可以有效克服專家知識局限性,較準(zhǔn)確的設(shè)置置信規(guī)則庫的置信框架,具有重要的工程實(shí)用價(jià)值。
[Abstract]:In order to comprehensive utilization of human beings in the decision-making process of uncertain information and qualitative knowledge, realize the modeling of complex decision problems, belief rule base (Belief Rule, Base, BRB) expert system came into being. Compared with the traditional IF-THEN rule, BRB added confidence in the framework of the rules, can make various types of data and make full use of knowledge mining, nonlinear information between input and output, so as to realize the modeling of complex decision problems. The belief rule base expert system to the intelligence and information knowledge expression and other advantages, has been the concern of scholars. The letter rules allowing experts directly involved, and expert knowledge is subjective, and the problem in practical engineering is these are complex, to quickly and accurately set confidence frame parameters and structural challenges. In order to solve the above problems, this paper on the belief rule base of expert system. Model method is studied. The main contents are as follows: (1) according to the belief rule base optimization model of solving the problem of poor efficiency, using a BRB parameter training method based on particle swarm algorithm. The edible oil adulteration detection problem as the background, the proposed method is verified. Compared with the traditional parameter optimization strategy of particle swarm optimization algorithm significantly improves the solving efficiency of oil detection. The BRB model (2) in order to overcome BRB in determining the structure of expert knowledge limitations, the premise of attribute reference value and output rating utility as the reasoning model of the parameters to be estimated, BRB model is put forward to optimize the structure and at the same time the parameters (Optimize Structure and Parameters of BRB, OSP-BRB). The tobacco perforated tipping paper permeability as the research object, comparing with the BRB structure identification, OSP-BRB reflect. The bearing of the actual situation, the result shows that this method can construct BRB structure more reasonable. (3) the decision factor of BRB caused by large scale, based on attribute importance, increase and optimize the weights of attributes, proposed BRB reduction models (BRB-reduction, BRB-R). The oil immersed transformer fault diagnosis an example, the method to reduce the size of the BRB at the same time, the fault diagnosis accuracy is improved by three percentage points, indicating that this method is an effective attribute reduction method. Aiming at the problems in modeling the belief rule base of expert system, from the belief rule base structure and parameters identification are studied and improved size reduction three, the application effect in three areas that the modeling of the improved method can effectively overcome the limitations of expert knowledge, confidence framework accurately set the belief rule base, has important practical engineering Use value.

【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP182

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本文編號：1493143