基于支持向量机的房地产投资全过程风险预测研究

W. Li, Yong Zhao, Wenqing Meng, Shipeng Xu
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引用次数: 5

摘要

随着房地产业的快速发展,投资风险也在迅速增加。因此,对房地产投资项目风险的预测和控制已成为决定项目成败的关键。摘要支持向量机(SVM)建模方法提出了房地产投资风险预测,利用其优点是结构风险最小化原则,小研究样本和非线性分析风险因素在房地产项目投资的每一个阶段,然后基于支持向量机的模型在建立房地产投资风险,最后,给出了一个例子来证明这个模型是有效的和实用的。为今后房地产投资风险的控制和管理提供有益的帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the Risk Prediction of Real Estate Investment Whole Process Based on Support Vector Machine
With the rapid development of real estate, the risk of investment is also increasing rapidly. So the risk of predicting and controlling the real estate investment has become the key to the success or failure of the project. In this paper, a support vector machine (SVM) modeling approach for real estate investment risk prediction is proposed at first, which is made use of its merits of structural risk minimization principle, the small study sample and non-linear to analyze the risk factors during investment every stage in real estate projects, then a model based on support vector machines in real estate investment risk is built up, at last, an example is given to prove that this model is effective and practical. All these are used of providing useful help of the future of real estate investment risk control and management.
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