【作者】 李刚；

【导师】 杨志强；

【作者基本信息】 长安大学 ， 土地资源管理， 2006， 硕士

【摘要】 随着我国房地产市场体系逐步确立并走向完善，作为中介服务行业的房地产估价工作在房地产市场中扮演着越来越重要的角色，并且服务范围越来越广；房地产估价有助于推动房地产价格正常化，保障房地产公平交易，建立健康的房地产市场体系和公正合理的交易秩序。目前我国房地产估价理论仍处在探索阶段，房地产估价需要多元化拓展，因而积极探索更为科学的估价方法具有重要的理论意义和现实意义。 本文在对国内外房地产估价研究现状、房地产价格特征以及房地产价格的影响因素分析研究的基础上，系统地论述了目前房地产价格评估中应用较为广泛的三种方法——市场比较法、收益法、成本法的内容体系，对各类估价方法的理论依据、适用条件和范围等进行了较为系统的比较分析。根据房地产估价的特点与对现有技术方法的分析，在前人研究的基础上充分论证了人工神经网络理论在房地产估价应用的理论和方法，利用神经网络超强的学习能力和处理非线性关系的能力，从大量的训练样本(房地产交易案例)中发现客观规律(即房地产价格与其影响因素之间的客观规律)，建立了房地产估价的神经网络模型。 在神经网络估价模型的实现中，以MATLAB为工具建立了以房地产价格的影响因素作为输入神经元，房地产价格作为输出神经元的三层BP神经网络模型，并且采用Levenberg-Marquardt算法对BP神经网络进行了优化。经过从市场调研得到的一组房地产成交案例对房地产估价的神经网络模型进行了训练和验证，取得了令人满意的结果。 理论与实践研究表明，采用Levenberg-Marquardt优化方法的BP神经网络估价模型可以快速准确的得到满意的结果，是一套较为科学实用和有效的房地产估价方法，是对房地产估价方法的重要拓展。更多还原

【Abstract】 With the establishment and gradual perfection of the system of the real estate market in China, exercise of appraisal, as the agent in the real estate industry, plays an increasingly important role and serves in the increasingly broader scope in the real estate market. Real estate appraisal goes a long way to promote the normalization of the real estate price, to ensure the fair transaction in the real estate market, and to set up sound market system and reasonable order of transaction. Currently, the theories of real estate appraisal are still at the probing stage in our country; moreover, real estate appraisal calls for multi-dimensional development, therefore, the probe into the more scientific approaches is of both theoretical and practical significance.The thesis, on the basis of analyses and studies on the real estate appraisal in terms of its status quo at home and abroad, and the price property, and the factors influencing the real estate prices, systematically explicates three appraisal approaches widely-used at present — market comparison approach, income approach and cost approach, analyzing respectively the theoretical grounds, the application scope and the evaluation procedures of each approach. On the basis of the review and tests of plenty of relevant literature, the thesis introduces the theories of ANN into the field of real estate appraisal, and by employing its super-powerful abilities of learning and handling non-linear relationship, finds out the objective law (i.e. the law between the real estate price and its influencing factors) through the analyses of plenty of training samples — real estate de facto transactions, and establishes a model of ANN real estate appraisal.In the realization of the model of ANN real estate appraisal, this thesis, using MATLAB as a tool, sets up a three-layer neural network model with the factors influencing the real estate price as the input artificial neuron and the real estate prices as the output artificial neuron, in which the BP neural network is optimized by using Levenberg-Marquardt method. Satisfactory results are achieved in the training and confirmation of ANN model of real estate appraisal with a group of real estate transactions in the current market.Both the theories and practice indicate that the adoption of BP neural network and Levenberg-Marquardt optimization method can help achieve promptly the accurate and satisfactory results in the real estate appraisal. It is a set of scientific and efficient approach to real estate appraisal and indicates a significant development in theory in this field.更多还原