Research Article

An Optimization Grey Bernoulli Model and Its Application in Forecasting Oil Consumption

Table 2

Metrics of models for fitting in Case 2.

YearRaw dataONGBMAPENGBMAPEGMAPENGMAPETDGMAPEVerhulstAPEAR-GMAPE
(1,1)(%)(1,1)(%)(1,1)(%)(1,1)(%)(1,1)(%)(%)(1,1)(%)

200412.412.4012.4012.4012.4012.4012.4012.40
200512.913.23282.579613.99218.465915.2246−18.02017.8722−38.975012.76641.03586.4967−49.638214.583413.0500
200614.415.04464.476615.82689.908615.7179−9.152213.6896−4.933615.977110.95199.3351−35.173215.953810.7902
200718.516.2433−12.198416.9431−8.415716.227212.285316.2658−12.076717.32946.327412.7894−30.868416.8138−9.1144
200819.217.0617−11.136917.6239−8.208916.753012.744617.4067−9.340017.89916.775816.4237−14.459817.3536−9.6166
200918.717.6170−5.791718.0100−3.690117.29597.508717.912−4.214118.13903.000119.42323.867117.6924−5.3884
201016.617.97858.304318.18449.544517.8563−7.568218.13579.251318.24009.879720.852925.619717.90507.8614
201118.118.19210.508618.2050.560918.4349−1.850418.23480.744818.28261.008820.187111.530818.0384−0.3402
201218.118.28961.047418.0992−0.004219.0322−5.150618.27870.987318.30051.107917.6770−2.337318.12220.1225
MAPEFIT (%)5.75546.09989.285010.06535.010921.68687.0355
201317.518.29464.540617.90522.315419.6490−12.279818.29814.560718.30814.617614.1695−19.031618.17473.8556
201417.018.22517.206217.64023.766020.2856−19.327318.30677.686718.31137.713310.5746−37.796418.20777.1042
201517.118.09495.818017.32041.289120.9430−22.473418.31057.079218.31267.09127.4784−56.267018.22846.5989
201618.217.9152−1.564616.9585−6.821521.6216−18.799818.31220.616718.31320.62185.0897−72.034718.24140.2275
201717.717.6952−0.027316.5645−6.415422.3222−26.114018.3133.4631818.31343.46563.3742−80.936718.24963.1049
201818.117.4421−3.634916.1466−10.792423.0455−27.323118.31331.178518.31351.17962.1982−87.855518.25470.8546
MAPEPRE (%)3.79865.233321.05294.09754.114858.98703.6243