中國住宅商品房平均銷售價(jià)格的預(yù)測研究

陳睿玉

摘要：本文使用基于IOWA誘導(dǎo)有序加權(quán)算術(shù)平均算子的變權(quán)組合預(yù)測模型，基于ARIMA（0，2，2）、指數(shù)平滑模型、多元線性回歸模型三種單項(xiàng)預(yù)測模型構(gòu)建誤差平方和最小的誘導(dǎo)有序加權(quán)算術(shù)平均組合預(yù)測模型。本文首先對其概念及基本原理作簡要介紹，再通過對2000-2018年住宅商品房平均銷售價(jià)格進(jìn)行擬合預(yù)測，并說明其有效性和可行性。結(jié)果表明，組合預(yù)測模型的平均精度和各項(xiàng)誤差度量相對于單項(xiàng)預(yù)測而言更好，未來五年的住宅商品房平均銷售價(jià)格依然呈較快的增長趨勢，因此，對住宅商品房銷售價(jià)格進(jìn)行調(diào)控是非常必要的。

Abstract： In this paper， the variable weight combination forecasting model based on IOWA induced ordered weighted arithmetic mean operator is used， and the least sum of square error induced ordered weighted arithmetic mean combination forecasting model is constructed based on ARIMA （0，2，2）， exponential smoothing model and multiple linear regression model. This paper first introduces its concept and basic principle， and then through the fitting prediction of the average sales price of residential commercial housing in 2000-2018， and explains its effectiveness and feasibility. The results show that the average accuracy and various error measures of the combined forecasting model are better than the single forecasting model， and the average sales price of residential commercial housing in the next five years still shows a rapid growth trend， so it is very necessary to regulate the sales price of residential commercial housing.

關(guān)鍵詞：IOWA算子;組合預(yù)測模型;住宅商品房平均銷售價(jià)格