Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 3
784-788

Housing prices evaluation using random forest algorithm combing with simulated annealing

Ding Yangjuntian
Cao Huaihu
School of Information, Central University Finance & Economics, Beijing 100081, China
DOI: 10.19734/j.issn.1001-3695.2018.07.0613

Abstract

The traditional housing prices evaluation which is using random forest algorithm has a large number of parameter selection problems and the parameters has great influence on the accuracy of the algorithm. In order to solve the above problem, this paper proposed a new algorithm combined the random forest algorithm and simulated annealing algorithm about the housing prices evaluation. Firstly, this paper tested the sensitivity of parameters by 10 times 10-cross-validation method and selected the parameters which were sensitive of the random forest algorithm. Secondly, it used the simulated annealing algorithm to optimize the sensitive parameters iteratively. Through comparing to the grid search algorithm and random search algorithm, it found the simulated annealing algorithm was better in the running time and algorithm accuracy, which made up the defects of the time-consuming and the low-accuracy of the random search algorithm in the grid search when selecting parameters. At last, this paper applied the random forest algorithm combing with simulated annealing to the housing prices evaluation, and formed a new evaluation algorithm. Compared with the traditional random forest price estimation algorithms, the results show that the proposed algorithm reduces the error value, increases the goodness of fit value, and improves markedly the accuracy of the evaluation.

Foundation Support

北京市社会科学重点项目(16YJA001)
国家自然科学基金资助项目(61671030)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0613
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Algorithm Research & Explore
Pages: 784-788
Serial Number: 1001-3695(2020)03-031-0784-05

Publish History

[2020-03-05] Printed Article

Cite This Article

丁旸钧天, 曹怀虎. 融合模拟退火的随机森林房价评估算法 [J]. 计算机应用研究, 2020, 37 (3): 784-788. (Ding Yangjuntian, Cao Huaihu. Housing prices evaluation using random forest algorithm combing with simulated annealing [J]. Application Research of Computers, 2020, 37 (3): 784-788. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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