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  本文選題：建筑物　切入點：變形預測　出處：《江西理工大學》2013年碩士論文

【摘要】：近年來，城市化的加快帶動了房地產(chǎn)的發(fā)展，大量高層建筑隨之產(chǎn)生。高層建筑物的安全問題日益受到人們的關注，建筑物變形預測問題就是其中之一。常見的預測方法對建筑物變形預測存在一些不足之處�；虮磉_式編程是一種基于生物基因結(jié)構(gòu)和功能發(fā)明的一種新型自適應演化算法，已在金融、氣象水文和災害預警等預測領域廣泛應用。因此，本文將基因表達式編程方法應用于建筑物變形預測中。 首先，論文對課題研究的意義以及當前國內(nèi)外變形預測研究進展進行了介紹，闡述了當前變形預測方法以及基因表達式編程應用的研究現(xiàn)狀，確定了本文研究內(nèi)容和研究路線。 其次，根據(jù)基因表達式編程原理，對基因表達式編程的基本流程進行了分析，并根據(jù)問題的復雜度，，采用多個基因組成的染色體作為研究對象并對其進行了編碼；其中個體的選擇采用輪盤賭法；變異、插串、重組等算子通過多次實驗得出了合理的參數(shù)值；同時，為了提高基因表達式編程的效率，針對傳統(tǒng)方法的不足，使用了Kquick算法對K-表達式的求解過程進行了改進。 然后，考慮到建筑物變形數(shù)據(jù)的實際情況，將滑動窗口預測法與標準的基因表達式編程算法加以結(jié)合提出了改進的基因表達式編程算法；使用Visual C++6.0開發(fā)了基于基因表達式編程的建筑物變形預測程序；最后，使用該程序?qū)δ彻⒌某两禂?shù)據(jù)進行了預測，通過多次實驗，獲得最優(yōu)的染色體，并得到了反映建筑物變形規(guī)律的數(shù)學模型。將預測結(jié)果與灰色系統(tǒng)預測模型、BP神經(jīng)網(wǎng)絡預測模型進行對比分析，結(jié)果表明，基于基因表達式編程的預測方法的預測值精度比傳統(tǒng)方法提高近一倍，也就是說基于基因表達式編程的預測方法在建筑物變形預測領域具有推廣應用價值。
[Abstract]:In recent years, the acceleration of urbanization has led to the development of real estate, and a large number of high-rise buildings have come into being.People pay more and more attention to the safety of high-rise buildings, one of which is building deformation prediction.There are some shortcomings in building deformation prediction by common prediction methods.Gene expression programming is a new adaptive evolutionary algorithm based on biological gene structure and function. It has been widely used in the fields of finance, meteorology and hydrology, disaster warning and so on.Therefore, the genetic expression programming method is applied to the prediction of building deformation.Firstly, this paper introduces the significance of the research and the research progress of deformation prediction at home and abroad, expounds the current research status of deformation prediction methods and gene expression programming, and determines the research content and research route of this paper.Secondly, according to the principle of gene expression programming, the basic process of gene expression programming is analyzed, and according to the complexity of the problem, the chromosome composed of multiple genes is used as the research object and encoded.The selection of individuals is based on roulette method; mutation, string insertion, recombination and other operators obtain reasonable parameter values through many experiments; at the same time, in order to improve the efficiency of gene expression programming, aiming at the shortcomings of traditional methods,The Kquick algorithm is used to improve the solution process of K-expression.Then, considering the actual situation of building deformation data, an improved genetic expression programming algorithm is proposed by combining the sliding window prediction method with the standard genetic expression programming algorithm.The program of building deformation prediction based on genetic expression was developed by using Visual C 6.0. Finally, the settlement data of an apartment was predicted by the program, and the optimal chromosome was obtained through many experiments.A mathematical model reflecting the law of building deformation is obtained.The prediction results are compared with the grey system prediction model and the BP neural network prediction model. The results show that the prediction accuracy of the prediction method based on gene expression programming is nearly twice as high as that of the traditional method.In other words, the prediction method based on genetic expression programming has the value of popularization and application in the field of building deformation prediction.
【學位授予單位】：江西理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TU196.1

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本文編號：1701594