Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model

Aiming at the shortcomings of a single machine learning model with low model prediction accuracy and insufficient generalization ability in house price index prediction, a whale algorithm optimized support vector regression model based on bagging ensemble learning method is proposed. Firstly, gray c...

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Autores principales:	Xiang Wang, Shen Gao, Shiyu Zhou, Yibin Guo, Yonghui Duan, Daqing Wu
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/8d5ab2e36dc24544981040d7f03f2ea7
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spelling	oai:doaj.org-article:8d5ab2e36dc24544981040d7f03f2ea72021-11-08T02:36:46ZPrediction of House Price Index Based on Bagging Integrated WOA-SVR Model1563-514710.1155/2021/3744320https://doaj.org/article/8d5ab2e36dc24544981040d7f03f2ea72021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3744320https://doaj.org/toc/1563-5147Aiming at the shortcomings of a single machine learning model with low model prediction accuracy and insufficient generalization ability in house price index prediction, a whale algorithm optimized support vector regression model based on bagging ensemble learning method is proposed. Firstly, gray correlation analysis is used to obtain the main influencing factors of house prices, and the segmentation forecasting method is used to divide the data set and forecast the house prices in the coming year using the data of the past ten years. Secondly, the whale optimization algorithm is used to find the optimal parameters of the penalty factor and kernel function in the SVR model, and then, the WOA-SVR model is established. Finally, in order to further improve the model generalization capability, a bagging integration strategy is used to further integrate and optimize the WOA-SVR model. The experiments are conducted to forecast the house price indices of four regions, Beijing, Shanghai, Tianjin, and Chongqing, respectively, and the results show that the prediction accuracy of the proposed integrated model is better than the comparison model in all cases.Xiang WangShen GaoShiyu ZhouYibin GuoYonghui DuanDaqing WuHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Xiang Wang Shen Gao Shiyu Zhou Yibin Guo Yonghui Duan Daqing Wu Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
description	Aiming at the shortcomings of a single machine learning model with low model prediction accuracy and insufficient generalization ability in house price index prediction, a whale algorithm optimized support vector regression model based on bagging ensemble learning method is proposed. Firstly, gray correlation analysis is used to obtain the main influencing factors of house prices, and the segmentation forecasting method is used to divide the data set and forecast the house prices in the coming year using the data of the past ten years. Secondly, the whale optimization algorithm is used to find the optimal parameters of the penalty factor and kernel function in the SVR model, and then, the WOA-SVR model is established. Finally, in order to further improve the model generalization capability, a bagging integration strategy is used to further integrate and optimize the WOA-SVR model. The experiments are conducted to forecast the house price indices of four regions, Beijing, Shanghai, Tianjin, and Chongqing, respectively, and the results show that the prediction accuracy of the proposed integrated model is better than the comparison model in all cases.
format	article
author	Xiang Wang Shen Gao Shiyu Zhou Yibin Guo Yonghui Duan Daqing Wu
author_facet	Xiang Wang Shen Gao Shiyu Zhou Yibin Guo Yonghui Duan Daqing Wu
author_sort	Xiang Wang
title	Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
title_short	Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
title_full	Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
title_fullStr	Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
title_full_unstemmed	Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model
title_sort	prediction of house price index based on bagging integrated woa-svr model
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/8d5ab2e36dc24544981040d7f03f2ea7
work_keys_str_mv	AT xiangwang predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel AT shengao predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel AT shiyuzhou predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel AT yibinguo predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel AT yonghuiduan predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel AT daqingwu predictionofhousepriceindexbasedonbaggingintegratedwoasvrmodel
_version_	1718443116122341376

Prediction of House Price Index Based on Bagging Integrated WOA-SVR Model

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