【摘要】：文章在回顧誘導(dǎo)有序加權(quán)調(diào)和平均(IOWHA)算子組合預(yù)測模型的基礎(chǔ)上,分別用指數(shù)平滑法、ARIMA模型、回歸與時(shí)間序列組合模型對我國商品房均價(jià)進(jìn)行預(yù)測,然后建立基于IOWHA算子的組合預(yù)測模型及評價(jià)指標(biāo)體系。結(jié)果表明,IOWHA組合預(yù)測模型比其他三種單項(xiàng)預(yù)測效果顯著更優(yōu),且三種單項(xiàng)預(yù)測之間具有信息互補(bǔ)性。并基于IOWHA算子得到的最優(yōu)權(quán)系數(shù),預(yù)測我國2012-2015年的商品房均價(jià)。
[Abstract]:On the basis of reviewing the combined prediction model of induced ordered weighted harmonic average (IOWHA) operators, the paper uses exponential smoothing method to predict the average price of commercial housing in China by using Arima model, regression model and time series combination model, respectively. Then the combined prediction model and evaluation index system based on IOWHA operator are established. The results show that the combined forecasting model of IOWHA is more effective than the other three individual prediction models, and the information complementarity among the three individual forecasting models is obvious. Based on the optimal weight coefficient obtained by IOWHA operator, the average price of commercial housing in China from 2012 to 2015 is predicted.
【作者單位】： 安徽財(cái)經(jīng)大學(xué)數(shù)量經(jīng)濟(jì)研究所;
【基金】：國家社科基金資助項(xiàng)目(12BTJ008) 安徽財(cái)經(jīng)大學(xué)研究生創(chuàng)新基金資助項(xiàng)目(ACYC2012039)
【分類號】：F224;F293.3

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本文編號：2206756