發(fā)布時間：2018-04-01 19:00

  本文選題：房地產(chǎn)市場　切入點：預(yù)警　出處：《哈爾濱工業(yè)大學(xué)》2014年碩士論文

【摘要】：房地產(chǎn)業(yè)作為國民經(jīng)濟支柱產(chǎn)業(yè)，其異常的波動會給經(jīng)濟發(fā)展帶來不利的影響。哈爾濱作為典型的二線城市，其房地產(chǎn)市場有著自身的特征。哈爾濱房地產(chǎn)市場起步較晚，至今雖然未發(fā)生過劇烈波動，，但是仍存在著問題和挑戰(zhàn)�；�于這種情況，建立房地產(chǎn)行市場預(yù)警模型，對市場異常進行合理調(diào)控是非常必要的。本文在對哈爾濱房地產(chǎn)市場進行預(yù)警研究時，選取粗糙集理論作為研究主線，灰色模型作為預(yù)測模型，相似度為評價標(biāo)準(zhǔn)，研究出適合于哈爾濱房地產(chǎn)市場的預(yù)警模型。 本文通過對哈爾濱房地產(chǎn)市場的分析，認為哈爾濱房地產(chǎn)市場總體來說發(fā)展良好，但是仍存在房價較人均收入太高，商品房空置嚴(yán)重，房地產(chǎn)開發(fā)融資渠道狹窄等問題。結(jié)合這些問題，本文從房地產(chǎn)市場健康發(fā)展的目標(biāo)出發(fā)，在房地產(chǎn)與社會經(jīng)濟的協(xié)調(diào)性、房地產(chǎn)市場供求關(guān)系、房地產(chǎn)業(yè)自身的發(fā)展情況三個方面選取了10個預(yù)警指標(biāo)。 本文利用粗糙集屬性約簡的思想確定指標(biāo)的重要等級，并且組合粗糙集代數(shù)觀和信息觀權(quán)重得到優(yōu)化后的預(yù)警指標(biāo)權(quán)重，結(jié)合指標(biāo)重要等級的劃分確定權(quán)重的合理性。預(yù)警最重要的是需要對未來情況做出預(yù)測，本文提出自調(diào)整新陳代謝灰色模型對預(yù)警指標(biāo)數(shù)據(jù)信息進行預(yù)測，并通過與傳統(tǒng)新陳代謝灰色模型算法計算結(jié)果對比驗證了本文提出的預(yù)測模型更為精確。而對于未來待評價年份的房地產(chǎn)市場的風(fēng)險狀態(tài)的判斷則是通過相似度計算尋找歷史相似年份，找出最相似的狀態(tài)，即為待評價年份的狀態(tài)。 基于1999-2013年哈爾濱市房地產(chǎn)市場的相關(guān)數(shù)據(jù)，本文利用所構(gòu)建的房地產(chǎn)市場預(yù)警模型，借助Matlab軟件獲得計算結(jié)果，得出哈爾濱房地產(chǎn)市場在2014年將有轉(zhuǎn)冷的趨勢。對重點預(yù)警指標(biāo)的分析得出哈爾濱房地產(chǎn)市場在2014年房地產(chǎn)投資與固定資產(chǎn)投資比可能會突破歷史最低記錄，房地產(chǎn)開發(fā)貸款延續(xù)近幾年下降的趨勢，商品房空置與竣工面積比則繼續(xù)走高,需要引起重視。綜合上述分析結(jié)果，本文最后提出了哈爾濱市房地產(chǎn)市場后續(xù)發(fā)展的建議。
[Abstract]:As a pillar industry of national economy, the abnormal fluctuation of real estate industry will bring adverse effects to economic development.Harbin as a typical second-line city, its real estate market has its own characteristics.Harbin real estate market started late, although has not had the violent fluctuation, but still has the question and the challenge.Based on this situation, it is necessary to establish a real estate market early warning model and to regulate the market anomalies reasonably.In this paper, we select rough set theory as the main line of study, grey model as prediction model, similarity as evaluation standard, and study the early warning model suitable for Harbin real estate market.Based on the analysis of Harbin real estate market, this paper thinks that Harbin real estate market is developing well, but there are still some problems such as higher house price than per capita income, serious vacancy of commercial housing and narrow financing channels for real estate development.Combined with these problems, this paper selects 10 early warning indexes from the aim of healthy development of real estate market, including the coordination of real estate and social economy, the relationship between supply and demand of real estate market, and the development of real estate industry itself.In this paper, we use the idea of attribute reduction in rough set to determine the important grade of index, and combine the weight of algebra and information of rough set to get the weight of pre-warning index after optimization, and determine the rationality of weight combining with the division of important grade of index.The most important thing in early warning is to predict the future situation. In this paper, the grey model of self-adjusting metabolism is proposed to predict the early warning index data.Compared with the calculation results of the traditional metabolism grey model, the prediction model proposed in this paper is more accurate.The judgment of the risk state of the real estate market in the years to be evaluated in the future is to find out the most similar year by similarity calculation, that is, the state of the year to be evaluated.Based on the relevant data of Harbin real estate market from 1999 to 2013, this paper makes use of the pre-warning model of real estate market, obtains the calculation result with Matlab software, and draws the conclusion that Harbin real estate market will turn cold in 2014.The analysis of key early warning indicators shows that the ratio of real estate investment to fixed asset investment in the Harbin real estate market in 2014 is likely to break through the lowest record in history, and real estate development loans continue to decline in recent years.Commercial housing vacancy and completion of the area ratio continues to go high, need attention.Synthesizing above analysis result, this article finally put forward the suggestion of Harbin real estate market follow-up development.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F299.27

【參考文獻】

相關(guān)期刊論文 前7條

1 雷振華;;房地產(chǎn)預(yù)警指標(biāo)體系建立思考[J];財會通訊;2009年17期

2 楊佃輝;陳軼;屠梅曾;;基于聚類分析和非參數(shù)檢驗的房地產(chǎn)預(yù)警指標(biāo)體系選擇[J];東華大學(xué)學(xué)報(自然科學(xué)版);2006年02期

3 李斌;房地產(chǎn)市場預(yù)報預(yù)警系統(tǒng)建立過程中的誤區(qū)及應(yīng)注意的要點[J];中國房地產(chǎn);2004年02期

4 丁烈云;房地產(chǎn)周期波動成因分析[J];華中科技大學(xué)學(xué)報(社會科學(xué)版);2003年02期

5 胡清華;于達仁;謝宗霞;;基于鄰域�；�和粗糙逼近的數(shù)值屬性約簡[J];軟件學(xué)報;2008年03期

6 崔嘯;周克成;曹冬冰;李秀婷;吳迪;董紀(jì)昌;;北京市商品住宅系統(tǒng)動力學(xué)模型構(gòu)建及其在預(yù)警中的應(yīng)用[J];系統(tǒng)工程理論與實踐;2011年04期

7 袁韶華;施松;汪應(yīng)宏;劉勤俠;翟鳴元;;中國房地產(chǎn)市場調(diào)控效果分析及房地產(chǎn)健康發(fā)展的建議[J];現(xiàn)代城市研究;2014年02期

相關(guān)博士學(xué)位論文 前2條

1 趙軍;基于GIS空間統(tǒng)計分析的區(qū)域房地產(chǎn)動態(tài)預(yù)警模型[D];中國地質(zhì)大學(xué)（北京）;2011年

2 崔立志;灰色預(yù)測技術(shù)及其應(yīng)用研究[D];南京航空航天大學(xué);2010年

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