Real estate price prediction in Nanning based on grey model
- DOI
- 10.2991/978-94-6463-260-6_72How to use a DOI?
- Keywords
- linear regression moving average method GM(0,N) model posterior difference test
- Abstract
With the rapid development of society and economy, the development of the real estate industry has always been in a leading position, but the change of housing prices has led to housing problems affecting every Chinese people. This paper predicts the trend of real estate prices in Nanning in the next 10 years. Firstly, a grey model is established, the simulation sequence is obtained by substituting the serial number of the relevant year, and the predicted value is compared with the original value by the posterior difference test method. Then, a grey GM(1, 1) model is established for the four main factors affecting housing prices respectively to predict the statistical values of these four factors in the next ten years. For the overfitting phenomenon existing in the prediction of some factors, linear regression fitting is used to predict the data in the next ten years after verifying the correlation. Finally, GM(0, N) estimation formula is used to forecast the real estate price in Nanning in the next ten years.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hao Cheng AU - Jian Yang AU - Chengyuan Fan AU - Hengfeng Xiang AU - Wenli Zhou AU - Ren Lin PY - 2023 DA - 2023/09/28 TI - Real estate price prediction in Nanning based on grey model BT - Proceedings of the 2023 International Conference on Management Innovation and Economy Development (MIED 2023) PB - Atlantis Press SP - 575 EP - 583 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-260-6_72 DO - 10.2991/978-94-6463-260-6_72 ID - Cheng2023 ER -