基于改进PSO-BP的房地产投资风险评价研究

发布时间：2018-04-17 20:14

本文选题：房地产投资 + 粒子群算法　；参考：《河北工程大学》2013年硕士论文

【摘要】：房地产开发是一项高投入、高收益、高风险的投资活动，在开发过程中会受到社会、政治、经济、技术等很多不确定因素的影响，在当前我国房地产业宏观调控力度加大的形势下，投资者如果仅仅依靠经验进行投资，则会具有较大的盲目性，必然会加大房地产投资风险。因而，科学合理的房地产投资风险评价系统的研究迫在眉睫，运用科学方法对房地产投资风险进行评价，在理论和实践方面都具有重要的价值。本文首先，对房地产投资风险的相关理论进行了归纳和总结，并从房地产投资的各个阶段出发，对房地产投资风险因素进行了具体分析，建立了房地产投资风险评价指标体系；其次，阐述了基于改进PSO优化BP神经网络的相关理论；最后，建立了改进PSO-BP的房地产投资风险评价模型，通过训练与检测验证了改进PSO-BP模型的评价效果优于一般传统方法，并将该模型应用到房地产投资风险评价的实际案例中，得出了有效的评价结果。本文针对BP神经网络的缺陷，利用改进PSO优化BP神经网络，，实现了BP神经网络仅在已接近最优解的基础上进行参数寻优的目的，有效的提高了网络的寻优精度和速度，使房地产投资风险评价效果更好。同时结合天津市房地产投资的实际案例，重点探讨了改进PSO-BP神经网络在房地产投资风险评价中的应用，对提高我国的房地产投资企业以及相关决策部门的决策水平具有现实意义。
[Abstract]:Real estate development is an investment activity with high investment, high income and high risk, which will be influenced by many uncertain factors, such as society, politics, economy, technology and so on.Under the situation of increasing macro-control of real estate industry in our country, if investors only rely on experience to invest, it will be blind and will inevitably increase the risk of real estate investment.Therefore, the research of scientific and reasonable real estate investment risk evaluation system is urgent. It is of great value in theory and practice to use scientific methods to evaluate real estate investment risk.First of all, this paper summarizes the theory of real estate investment risk, and analyzes the risk factors of real estate investment from each stage of real estate investment, and establishes the evaluation index system of real estate investment risk.Secondly, the related theory of BP neural network optimization based on improved PSO is expounded. Finally, the risk evaluation model of real estate investment based on improved PSO-BP is established, and the evaluation effect of improved PSO-BP model is proved to be better than that of traditional methods through training and testing.The model is applied to the real estate investment risk evaluation, and the effective evaluation results are obtained.Aiming at the defects of BP neural network, this paper optimizes BP neural network by using improved PSO, realizes the goal of parameter optimization only on the basis of approaching the optimal solution, and effectively improves the precision and speed of optimization.So that real estate investment risk evaluation effect is better.At the same time, the application of improved PSO-BP neural network in real estate investment risk evaluation is discussed in the light of the real estate investment cases in Tianjin.It is of practical significance to improve the level of decision-making of real estate investment enterprises and relevant decision-making departments in our country.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP18;F299.23

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