發(fā)布時(shí)間：2018-03-16 10:32

  本文選題：現(xiàn)代不確定度　切入點(diǎn)：貝葉斯方法　出處：《合肥工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：不確定度作為表征測量結(jié)果的重要參數(shù)指標(biāo),越來越受到社會各個領(lǐng)域的重視。隨著時(shí)代的不斷進(jìn)步、科技的高速發(fā)展以及人們對產(chǎn)品質(zhì)量的高度重視,現(xiàn)代不確定度評定方法和理論應(yīng)運(yùn)而生。研究現(xiàn)代不確定度評定方法,對完善現(xiàn)代不確定度理論,促進(jìn)現(xiàn)代不確定度的廣泛應(yīng)用具有重要意義。分析現(xiàn)代不確定度理論的前提下,對貝葉斯不確定度評定方法進(jìn)行了系統(tǒng)研究;基于共軛貝葉斯原理,提出融合歷史信息和當(dāng)前樣本信息的不確定度分量實(shí)時(shí)、連續(xù)更新方法;針對無信息、共軛先驗(yàn)貝葉斯方法的局限性,提出最大熵原理的貝葉斯不確定度評估方法,引入最優(yōu)化算法和計(jì)算機(jī)編程實(shí)現(xiàn)不確定度的優(yōu)化估計(jì);通過模擬仿真,驗(yàn)證了所提出方法的有效性。以貝葉斯動態(tài)預(yù)測原理和模型為基礎(chǔ),研究了貝葉斯動態(tài)不確定度評定與預(yù)測方法。分析了動態(tài)隨機(jī)過程特征和類型,重點(diǎn)建立了各態(tài)歷經(jīng)隨機(jī)過程動態(tài)不確定度預(yù)測模型;討論了非各態(tài)歷經(jīng)隨機(jī)過程動態(tài)不確定度評定方法;通過測量實(shí)例分析,為實(shí)際動態(tài)不確定度評定提供了普遍意義的指導(dǎo)。鑒于蒙特卡洛方法在不確定度評定中的應(yīng)用優(yōu)勢,提出了蒙特卡洛不確定度驗(yàn)證方法;通過模擬仿真實(shí)例分析,驗(yàn)證了貝葉斯動態(tài)不確定度評定與預(yù)測方法的可操作性,保證了不確定度評定與預(yù)測結(jié)果的可靠性。重點(diǎn)關(guān)注了不確定度在產(chǎn)品檢驗(yàn)中的應(yīng)用,研究了不確定度影響下的產(chǎn)品檢驗(yàn)合格性判定方法;建立了單一產(chǎn)品檢驗(yàn)合格判定誤判率計(jì)算模型;針對批量產(chǎn)品檢驗(yàn),提出了全數(shù)檢驗(yàn)產(chǎn)品合格判定誤判風(fēng)險(xiǎn)評估方法。通過產(chǎn)品檢驗(yàn)實(shí)例分析,綜合運(yùn)用所提出理論,為基于不確定度的產(chǎn)品檢驗(yàn)合格判定方法提供了細(xì)化指導(dǎo),為產(chǎn)品供求雙方協(xié)商決定產(chǎn)品的合格性提供了科學(xué)依據(jù)。
[Abstract]:As an important parameter index to characterize the measurement results, uncertainty has been paid more and more attention by various fields of the society. With the development of the times, the rapid development of science and technology and the high attention to the quality of products, people pay more and more attention to the quality of products. Modern uncertainty evaluation methods and theories come into being. It is of great significance to promote the wide application of modern uncertainty. Based on the analysis of modern uncertainty theory, the evaluation method of Bayesian uncertainty is studied systematically, which is based on conjugate Bayesian principle. A real-time and continuous updating method for the uncertainty components of historical information and current sample information is proposed, and a Bayesian uncertainty evaluation method based on maximum entropy principle is proposed to evaluate the uncertainty of Bayes, which has no information and conjugate prior Bayes method. The optimization algorithm and computer programming are introduced to realize the optimal estimation of uncertainty, and the effectiveness of the proposed method is verified by simulation, which is based on the Bayesian dynamic prediction principle and model. The evaluation and prediction methods of Bayesian dynamic uncertainty are studied, the characteristics and types of dynamic stochastic processes are analyzed, and the prediction models of dynamic uncertainty of ergodic stochastic processes are established. This paper discusses the evaluation method of dynamic uncertainty of non-ergodic random processes, and provides a general guidance for the evaluation of actual dynamic uncertainty through the analysis of measurement examples. In view of the advantages of Monte Carlo method in the evaluation of uncertainty, The verification method of Monte Carlo uncertainty is put forward, and the feasibility of Bayesian dynamic uncertainty evaluation and prediction method is verified by simulation analysis. The reliability of uncertainty evaluation and prediction results is ensured. The application of uncertainty in product inspection is focused on, and the method of product qualification determination under the influence of uncertainty is studied. This paper establishes a model for calculating the misjudgment rate of a single product's qualified judgment, and puts forward a risk assessment method for the batch product's qualification judgment and misjudgment. Through the analysis of a product inspection example, the author synthetically applies the proposed theory. It provides detailed guidance for the method of product qualification based on uncertainty, and provides scientific basis for both supply and demand parties to decide the conformity of product through negotiation.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TG801

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