【摘要】：近幾年來,隨著旅游業(yè)的持續(xù)發(fā)展以及全球氣候的變化,云岡石窟的依存環(huán)境發(fā)生了很大的變化。同時(shí)由于自然條件復(fù)雜且對云岡石窟風(fēng)化作用的機(jī)理認(rèn)識(shí)不足,云岡石窟石質(zhì)文物的防風(fēng)化保護(hù)一直是困擾我國文物保護(hù)工作的難題。因此有必要對以云岡石窟為例的石質(zhì)文物風(fēng)化影響因素進(jìn)行科學(xué)的研究。 本研究使用數(shù)據(jù)挖掘分類方法中的決策樹CART分類算法模型和傳統(tǒng)回歸分析方法中的非條件Logistic回歸模型,探討影響石質(zhì)文物風(fēng)化的因素。并比較CART模型與Logistic模型之間結(jié)果的異同,進(jìn)一步探討CART模型與Logistic模型可以互為補(bǔ)充之處,以達(dá)到更準(zhǔn)確的篩選風(fēng)化影響因素的目的。首先,通過實(shí)地調(diào)研,專家咨詢,文獻(xiàn)研究等方法,了解石質(zhì)文物風(fēng)化機(jī)制,風(fēng)化過程及可能的影響因素,并通過多種途徑獲取相關(guān)研究數(shù)據(jù);其次,通過非條件Logostic回歸分析,建立風(fēng)化影響因素非條件Logistic模型,對模型結(jié)果進(jìn)行分析驗(yàn)證;再次,在理清決策樹CART算法原理的情況下,利用決策樹CART算法建立風(fēng)化影響因素決策樹模型并對結(jié)果進(jìn)行分析驗(yàn)證,并利用決策樹模型提供的交互效應(yīng)信息以及變量分類信息擬合新的Logistic回歸模型,比較其與原Logistic模型篩選所得影響因素的差異;最后,利用各模型預(yù)測概率的ROC曲線下面積來評(píng)價(jià)模型分類的準(zhǔn)確度,并說明CART決策樹模型在篩選影響因素方面的優(yōu)勢以及改進(jìn)后Logistic回歸模型較改進(jìn)前的準(zhǔn)確性。 本文將數(shù)據(jù)挖掘中的決策樹分類方法應(yīng)用到石質(zhì)文物風(fēng)化影響因素研究中,并與非條件Logistic模型相結(jié)合,能夠更加充分的利用相關(guān)數(shù)據(jù)信息,得到更為全面的結(jié)果,這為石質(zhì)文物風(fēng)化影響因素研究提供了一種新的思路與方法,具有一定的理論和實(shí)際參考價(jià)值。
[Abstract]:In recent years, with the continuous development of tourism and the change of global climate, the dependent environment of Yungang Grottoes has changed greatly. At the same time, because of the complex natural conditions and lack of understanding of the mechanism of weathering in Yungang Grottoes, the weathering protection of Yungang Grottoes has been a difficult problem for the protection of cultural relics in China. Therefore, it is necessary to scientifically study the weathering factors of stone relics in Yungang Grottoes. In this study, the decision tree CART classification algorithm model and the unconditioned Logistic regression model in the traditional regression analysis were used to explore the factors affecting the weathering of stone relics. The similarities and differences of the results between CART model and Logistic model are compared, and the complementarities between CART model and Logistic model are discussed in order to screen the influence factors of weathering more accurately. First of all, through field investigation, expert consultation, literature research and other methods, to understand the weathering mechanism, weathering process and possible influencing factors of stone relics, and obtain the relevant research data through a variety of channels; secondly, through non-conditional Logostic regression analysis, The unconditioned Logistic model of weathering influencing factors is established, and the results of the model are analyzed and verified. Thirdly, in the case of clarifying the CART algorithm principle of decision tree, The decision tree model of weathering influencing factors is established by using decision tree CART algorithm and the results are analyzed and verified. The new Logistic regression model is fitted with the interactive effect information provided by decision tree model and the information of variable classification. Finally, the accuracy of model classification is evaluated by using the area under the ROC curve of the prediction probability of each model. The advantages of CART decision tree model in screening influencing factors and the accuracy of the improved Logistic regression model are also explained. In this paper, the decision tree classification method in data mining is applied to the study of the factors affecting the weathering of stone relics, and combined with the non-conditional Logistic model, it can make full use of the relevant data information and obtain more comprehensive results. This provides a new way of thinking and method for the study of the factors affecting the weathering of stone relics and has certain theoretical and practical reference value.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2010
【分類號(hào)】：K879.2;P512.1

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