本文選題：TEI@I方法論 + 多元預(yù)測模型��； 參考：《青島理工大學(xué)》2013年碩士論文

【摘要】：房地產(chǎn)業(yè)是國民經(jīng)濟(jì)的重要組成部分，其發(fā)展?fàn)顩r的好壞將直接關(guān)系到我國國民經(jīng)濟(jì)的發(fā)展水平、人民生活的和諧程度。商品住宅作為房地產(chǎn)業(yè)的一個重要組成部分，在國民經(jīng)濟(jì)中發(fā)揮的作用也越來越大，對廣大人民群眾的基本生活也產(chǎn)生著重大的影響。商品住宅在高速發(fā)展的同時其價(jià)格也在逐年飆升，房價(jià)成為影響社會發(fā)展的重要因素。 青島西海岸經(jīng)濟(jì)新區(qū)是2011年《山東半島藍(lán)色經(jīng)濟(jì)區(qū)發(fā)展規(guī)劃》明確建設(shè)的新區(qū)。為了進(jìn)一步促進(jìn)青島西海岸經(jīng)濟(jì)新區(qū)一體化的發(fā)展，2012年12月經(jīng)國務(wù)院批復(fù)，將膠南市和黃島區(qū)行政區(qū)劃調(diào)整為新的黃島區(qū)，為西海岸經(jīng)濟(jì)新區(qū)的一體化推進(jìn)和國家級新區(qū)的設(shè)立創(chuàng)設(shè)了一個很好的基礎(chǔ)。青島西海岸經(jīng)濟(jì)新區(qū)未來的發(fā)展直接關(guān)乎青島市經(jīng)濟(jì)社會發(fā)展的興衰與走向。而商品住宅的價(jià)格波動以及未來的發(fā)展趨勢，對新區(qū)的發(fā)展有十分重要的意義。因此，從商品住宅市場入手，尋求影響商品住宅價(jià)格變動的各因素，通過分析各影響因子在時間上的變動趨勢，來對房價(jià)進(jìn)行科學(xué)合理的預(yù)測，對指導(dǎo)政府宏觀管理與調(diào)控，促進(jìn)住宅市場健康發(fā)展有著重要的意義，同時對其他類似城市住宅市場的發(fā)展研究也有一定的借鑒性。 本文以TEI@I方法論作為理論基礎(chǔ)，從青島市青島西海岸經(jīng)濟(jì)新區(qū)商品住宅平均銷售價(jià)格和影響住宅價(jià)格的因素入手，通過構(gòu)建多元分析預(yù)測模型，對青島西海岸經(jīng)濟(jì)新區(qū)2013年商品住宅價(jià)格進(jìn)行研究預(yù)測。論文主要從四個部分進(jìn)行分析研究。 （1）對青島西海岸經(jīng)濟(jì)新區(qū)的總體概況及商品住宅市場的現(xiàn)狀進(jìn)行分析，總結(jié)了商品住宅市場的特點(diǎn)，以及存在的問題。 （2）分析影響青島西海岸經(jīng)濟(jì)新區(qū)商品住宅價(jià)格的因素。首先從供需方面定性的分析影響價(jià)格變動的因素；然后利用主成分分析法，結(jié)合青島西海岸經(jīng)濟(jì)新區(qū)的實(shí)際情況，通過定量分析確定影響青島西海岸經(jīng)濟(jì)新區(qū)商品住宅價(jià)格的主要因素。 （3）基于TEI@I方法論的文本挖掘(Text mining)+經(jīng)濟(jì)計(jì)量(Econometrics)+智能技術(shù)(Intelligence)@集成技術(shù)(Integration)的思想，提出 了商品住宅價(jià)格預(yù)測模型的設(shè)計(jì)與構(gòu)建思路。主要以多元回歸、Bayes線性預(yù)測模型以及GM(1,1)非線性預(yù)測模型為計(jì)量模型，然后利用IOWA算子對這些預(yù)測模型進(jìn)行集成分析，進(jìn)一步精確預(yù)測結(jié)果。 （4）運(yùn)用基于TEI@I方法論構(gòu)建的多元預(yù)測模型，對青島西海岸經(jīng)濟(jì)新區(qū)商品住宅價(jià)格進(jìn)行預(yù)測，通過對多年預(yù)測值與實(shí)際房價(jià)的比較，，得出本預(yù)測模型具有較高的準(zhǔn)確性，可以較準(zhǔn)確的預(yù)測未來青島西海岸經(jīng)濟(jì)新區(qū)商品住宅的價(jià)格。根據(jù)預(yù)測的結(jié)果，對青島西海岸商品住宅價(jià)格做出分析，提出對策和建議。
[Abstract]:The real estate industry is an important part of the national economy, and the quality of its development will directly affect the development level of our national economy and the harmonious degree of people's life. As an important part of the real estate industry, commercial housing plays a more and more important role in the national economy and has a great impact on the basic life of the broad masses of the people. With the rapid development of commercial housing, its price is also soaring year by year, which has become an important factor affecting the development of society. Qingdao West Coast Economic Zone is a new area which is clearly constructed in 2011 "Shandong Peninsula Blue Economic Zone Development Plan". In order to further promote the integration of the new economic district on the west coast of Qingdao, in December 2012, with the approval of the State Council, the administrative divisions of Jiaonan City and Huangdao District were adjusted to the new Huangdao District. It provides a good foundation for the integration of the new economic zone along the west coast and the establishment of the national new zone. The future development of Qingdao West Coast Economic Zone is directly related to the rise and fall of Qingdao's economic and social development. The fluctuation of commodity housing price and the future development trend are of great significance to the development of the new district. Therefore, starting with the commodity housing market, this paper seeks the factors that affect the change of commodity housing price, analyzes the changing trend of each influencing factor in time, makes a scientific and reasonable forecast of the house price, and guides the government to manage and regulate the house price. It is of great significance to promote the healthy development of housing market. On the basis of TEI@I methodology, this paper starts with the average selling price of commercial housing and the factors affecting housing price in Qingdao West Coast Economic New area, and constructs a multivariate analysis and prediction model. This paper studies and forecasts the commodity housing price in the new economic district of Qingdao west coast in 2013. The thesis mainly carries on the analysis and research from four parts. This paper analyzes the general situation of Qingdao West Coast Economic New area and the present situation of commercial housing market, summarizes the characteristics of commodity housing market and the existing problems. (2) analyze the factors that influence the commodity housing price in the new economic zone of Qingdao west coast. First, qualitatively analyzing the factors that influence the price change from the aspect of supply and demand; then using the principal component analysis method, combining with the actual situation of Qingdao West Coast Economic New area, Through quantitative analysis to determine the main factors affecting the commodity housing prices in the new economic zone of the west coast of Qingdao. 3) text Mining based on TEI@I Methodology) econometrics) Intelligent Technology / Integration Technology, and puts forward the idea of Integration The design and construction of commodity housing price prediction model are presented. The multivariate regression Bayesian linear prediction model and the GM1 / 1) nonlinear prediction model are taken as the econometric models. Then the integrated analysis of these prediction models is carried out by using IOWA operator, and the prediction results are further accurate. 4) using the multivariate forecasting model based on TEI@I methodology to forecast the commodity housing price in the new economic area of Qingdao west coast. By comparing the forecasted value with the real house price, it is concluded that this forecasting model has high accuracy. Can accurately predict the future of Qingdao West Coast Economic Zone commodity housing prices. According to the forecast results, this paper analyzes the commodity housing prices in the west coast of Qingdao, and puts forward some countermeasures and suggestions.
【學(xué)位授予單位】：青島理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F299.233.4;F224

【引證文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 孔煜;城市住宅價(jià)格變動的影響因素研究[D];重慶大學(xué);2006年

相關(guān)碩士學(xué)位論文 前1條

1 陳楚月;電動汽車充換電需求分析與預(yù)測[D];北京交通大學(xué);2015年

本文編號：1864016