發(fā)布時間：2018-07-31 07:25

【摘要】：由于單宗評估方法在房地產(chǎn)價值評估過程中存在評估標(biāo)準(zhǔn)不一、成本過大等諸多問題，進(jìn)而導(dǎo)致一定程度上稅收流失、社會不公等現(xiàn)象的產(chǎn)生，許多歐美發(fā)達(dá)國家多年前就開始采用計算機(jī)輔助的批量評估方法。計算機(jī)輔助批量評估（Computer-assisted Mass Appraisal，CAMA），即在原有成本法、市場比較法和收益法評估原理的基礎(chǔ)上，結(jié)合計算機(jī)技術(shù)和統(tǒng)計分析技術(shù)，對大批量特定類型的物業(yè)的市場價值進(jìn)行快速、高效地評估的一種方法。如今在歐美發(fā)達(dá)國家，批量評估已經(jīng)逐步取代了單宗評估，廣泛地應(yīng)用于不動產(chǎn)的稅基評估中。與之相比，我國的批量評估技術(shù)還處于應(yīng)用起步階段。得益于2009年下半年財政部和稅務(wù)總局在各個地區(qū)開始進(jìn)行的存量房批量評估試點和推廣工作，目前我國大多數(shù)地區(qū)已經(jīng)初步建立了CAMA系統(tǒng)，并已于2012年7月1日起正式對納稅人申報的存量房交易價格進(jìn)行全面的評估。但由于各國不動產(chǎn)稅基評估體系的設(shè)計與本國的經(jīng)濟(jì)結(jié)構(gòu)、政府職能部門的設(shè)置、稅制發(fā)展改革、法律體系等都有著密切關(guān)系，我國的CAMA系統(tǒng)建設(shè)不能照搬照抄國外的理論，特別是批量評估的核心——自動評估模型（Automated Valuation Model，AVM），，應(yīng)考慮我國的實際情況，對國外成熟的批量評估技術(shù)進(jìn)行本地化改進(jìn)。 本文首先詳細(xì)介紹了批量評估技術(shù)的概念與方法原理，分析了國內(nèi)外的發(fā)展情況，并系統(tǒng)總結(jié)了實施批量評估的具體步驟。實施CAMA系統(tǒng)有兩個非常重要的關(guān)鍵點，一是構(gòu)建數(shù)據(jù)全面、真實、準(zhǔn)確的房地產(chǎn)基礎(chǔ)信息數(shù)據(jù)庫；二是構(gòu)建一個合適特定物業(yè)類型的自動評估模型。本文對以上兩個關(guān)鍵點的實施進(jìn)行了相關(guān)論述，并著重介紹了自動評估模型理論。 然后，本文提出了適合我國的批量評估技術(shù)方案，依據(jù)我國各地CAMA系統(tǒng)實際建設(shè)與運(yùn)行中存在的問題，提出并構(gòu)建了綜合特征價格模型和交易案例的自動評估模型，利用多元線性回歸分析對模型進(jìn)行校準(zhǔn)。并以某市的存量房為研究對象對上述自動評估模型進(jìn)行實證檢驗。通過一系列評估檢驗標(biāo)準(zhǔn)，本文驗證了該批量評估技術(shù)方案適用我國的存量房市場，并且評估效果良好。 接著，本文對神經(jīng)網(wǎng)絡(luò)中的一種計算模型——反向傳播神經(jīng)網(wǎng)絡(luò)（BP神經(jīng)網(wǎng)絡(luò)）在房地產(chǎn)批量評估中的應(yīng)用進(jìn)行了深入的研究。根據(jù)房地產(chǎn)批量評估領(lǐng)域特征向量多、數(shù)據(jù)量大的特點，本文對反向傳播算法固有的“收斂速度慢”的缺陷進(jìn)行了改進(jìn)，并對反向傳播神經(jīng)網(wǎng)絡(luò)計算模型進(jìn)行了實證檢驗，取得了良好的效果。 最后，本文基于綜合特征價格模型和交易案例的自動評估模型，采用J2EE/Java EE技術(shù)，實現(xiàn)了存量房批量評估系統(tǒng)，并詳細(xì)介紹了系統(tǒng)中采用的關(guān)鍵技術(shù)。
[Abstract]:In the process of real estate value evaluation, there are many problems, such as different evaluation criteria, excessive cost and so on, which lead to the phenomenon of tax loss and social injustice to a certain extent. Many developed countries in Europe and America began to use computer-aided batch evaluation method many years ago. Computer-assisted Mass Appraisal evaluation (CAMA), which is based on the original cost method, market comparison method and income method evaluation principle, combines computer technology and statistical analysis technology to speed up the market value of a certain type of property in large quantities. A method of efficient evaluation. Now in developed countries in Europe and America, batch evaluation has gradually replaced single assessment and is widely used in tax base assessment of real estate. In contrast, batch evaluation technology in China is still in the initial stage of application. Thanks to the batch evaluation and promotion of stock housing started by the Ministry of Finance and the General Administration of Taxation in various regions in the second half of 2009, at present, CAMA systems have been initially established in most regions of our country. And on July 1, 2012, the transaction price of stock house declared by taxpayers has been comprehensively evaluated. However, the design of real estate tax base assessment system in various countries is closely related to the national economic structure, the establishment of government functional departments, the reform of tax system development, the legal system, and so on. The construction of CAMA system in China cannot copy the theory of foreign countries. In particular, the core of batch evaluation, automatic evaluation model (Automated Valuation Model), should consider the actual situation of our country, and localize and improve the mature batch evaluation technology abroad. In this paper, the concept and principle of batch evaluation technology are introduced in detail, the development situation at home and abroad is analyzed, and the concrete steps to implement batch evaluation are summarized systematically. The implementation of CAMA system has two very important key points, one is to build a comprehensive, true and accurate real estate information database, the other is to build an automatic evaluation model suitable for a specific property type. In this paper, the implementation of the above two key points is discussed, and the theory of automatic evaluation model is emphatically introduced. Then, this paper puts forward the batch evaluation technology scheme suitable for our country. According to the problems existing in the actual construction and operation of CAMA system in various parts of our country, this paper puts forward and constructs a comprehensive feature price model and an automatic evaluation model of transaction cases. Multiple linear regression analysis was used to calibrate the model. Taking the stock house of a certain city as the research object, this paper makes an empirical test on the above automatic evaluation model. Through a series of evaluation and inspection criteria, this paper verifies that the batch evaluation scheme is suitable for the stock housing market in China, and the evaluation effect is good. Then, the application of backpropagation neural network (BP neural network), a computational model of neural network, in real estate batch evaluation is studied in this paper. According to the characteristics of large amount of data and more feature vectors in the field of real estate batch evaluation, this paper improves the inherent "slow convergence speed" of back propagation algorithm, and makes an empirical test on the calculation model of back propagation neural network. Good results have been achieved. Finally, based on the integrated feature price model and the automatic evaluation model of transaction cases, this paper uses J2EE/Java EE technology to realize the stock house batch evaluation system, and introduces the key technologies in the system in detail.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP311.52;TP183

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本文編號：2154854