CAJ | 학술논문

针对商品住宅价格预测问题，分析整理了与房价相关的经济因素，首次提出将BP-Boosting回归算法运用到商品住宅价格的预测中。以郑州市房地产相关数据为实例，进行学习预测。模型结果表明，该方法简单有效，较为准确地预测出下一个季度的房价，与BP神经网络及灰色-马尔柯夫模型相比具有较为理想的预测精度。
침대상품주택개격예측문제，분석정리료여방개상관적경제인소，수차제출장BP-Boosting회귀산법운용도상품주택개격적예측중。이정주시방지산상관수거위실례，진행학습예측。모형결과표명，해방법간단유효，교위준학지예측출하일개계도적방개，여BP신경망락급회색-마이가부모형상비구유교위이상적예측정도。
For commodity housing price forecast problems,we analyzed the economic factors related to housing prices. The paper firstly proposed BP-Boosting regression algorithm to be applied in the commodity housing price forecast. We carried out a simulative prediction with relevant data of Zhengzhou real estate and achieved good results,then more accurate predict prices in the next quarter were got. Compared with BP neural network and grey markov model,it is more effective and accurate.