本文關(guān)鍵詞： 房地產(chǎn)市場 預(yù)測 多元回歸 神經(jīng)網(wǎng)絡(luò) BP模型　出處：《華中科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：房地產(chǎn)是一個復(fù)雜的綜合性系統(tǒng)工程，關(guān)系的國民經(jīng)濟的命脈。房地產(chǎn)市場自身存在周期性波動規(guī)律，過大的波動幅度不利于房地產(chǎn)市場的持續(xù)穩(wěn)定健康發(fā)展，進而影響到這個國民經(jīng)濟的可持續(xù)發(fā)展。房地產(chǎn)市場預(yù)測正是對房地產(chǎn)相關(guān)指標(biāo)波動幅度的預(yù)測，，建立科學(xué)的房地產(chǎn)預(yù)測系統(tǒng)，可以有效地防止房地產(chǎn)市場的非正常波動，從而促進房地產(chǎn)市場的健康、穩(wěn)定發(fā)展。這也就是本文的研究目的所在。 本文首先是介紹相關(guān)的預(yù)測模型，多元回歸模型和神經(jīng)網(wǎng)絡(luò)模型。包括這兩種模型的原理、算法和檢驗，以及神經(jīng)網(wǎng)絡(luò)模型中本文主要應(yīng)用的BP模型。其次，分別利用多元回歸模型和BP模型在預(yù)測和模式識別領(lǐng)域的成熟運用，以武漢市房地產(chǎn)市場為對象進行實證研究，并運用spss、Matlab等統(tǒng)計數(shù)據(jù)挖掘工具根據(jù)武漢市房地產(chǎn)市場相關(guān)數(shù)據(jù)建立相應(yīng)模型，重點探討基于BP神經(jīng)網(wǎng)絡(luò)理論的房地產(chǎn)預(yù)測的模型和方法，同時對兩種模型的房地產(chǎn)預(yù)測模型和方法分別進行了分析。最后，通過對兩種不同的預(yù)測方法做了預(yù)測分析比較后，得出比較優(yōu)質(zhì)的模型，形成一個綜合預(yù)測分析系統(tǒng)，并以此為依據(jù)提出相關(guān)政策調(diào)控建議。通過對預(yù)測結(jié)果的分析，發(fā)現(xiàn)它基本符合武漢市房地產(chǎn)發(fā)展的實際情況，這表明本文所建立的房地產(chǎn)預(yù)測模型是有意義的，本文理論分析充分，所做的預(yù)測分析有一定實用價值。
[Abstract]:Real estate is a complex comprehensive system engineering, which is the lifeblood of the national economy. The real estate market has its own periodic fluctuation law, which is not conducive to the sustained, stable and healthy development of the real estate market. This will affect the sustainable development of the national economy. The real estate market forecast is precisely the prediction of the fluctuation range of the related indicators of real estate. The establishment of a scientific real estate forecasting system can effectively prevent the abnormal fluctuations of the real estate market. In order to promote the healthy and stable development of the real estate market, this is the purpose of this paper. This paper first introduces the related prediction model, multivariate regression model and neural network model, including the principle, algorithm and test of these two models, as well as the BP model which is mainly used in the neural network model. Using the multivariate regression model and BP model in the prediction and pattern recognition field of mature application, taking Wuhan real estate market as the object of empirical research, Using SPSS Matlab and other statistical data mining tools to establish the corresponding model according to the relevant data of Wuhan real estate market, focusing on the real estate forecasting model and method based on BP neural network theory. At the same time, the real estate forecasting models and methods of the two models are analyzed separately. Finally, after comparing and forecasting the two different forecasting methods, a better model is obtained and a comprehensive forecasting and analysis system is formed. Through the analysis of the forecast results, it is found that it basically accords with the actual situation of the real estate development in Wuhan, which shows that the real estate forecasting model established in this paper is meaningful. The theoretical analysis in this paper is sufficient, and the prediction and analysis made in this paper has certain practical value.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F299.23;F224;TP18

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