时间序列平滑预测法实验报告

应用数学 540910020111 李增辉预测决策实验报告时间序列平滑预测法实验报告实验课题:已知一个时间序列如图1-1,请选择自适应过滤法对下一期的值进行预测；实验目的:熟练掌握自适应过滤法；并能够熟练运用自适应过滤法处理一些实际问题；实验内容:原始数据图:期数12345678910数据3.212.654.124.34.724.193.852.523.913.361.根据原始数据做散点图: 3-12.对数据经行标准化处理如图3-2；期数x13.21010.30422.6507.02334.12016.97417.3274.1630.7710.6370.99044.30018.49023.9974.8990.5410.8410.87854.72022.27835.4645.9550.6920.7220.79364.19017.55640.7686.3850.6730.7390.65673.85014.82339.8356.3110.7480.6640.61082.5206.35032.3795.6900.7360.6770.44393.91015.28821.1734.6010.8370.5480.850103.36011.29021.6394.6520.5420.8410.7223-22.权数调整过程及结果如图3-3；取p=2,可得初始权数
；由于
=
=0.366,故取学习常数k=0.35；循环次数txt*xt2*xt1*1t2tfxtetf1tf2tT=1MSE=0.28830.9900.7710.6370.5000.5000.7040.2860.6980.65440.8780.5410.8410.6980.6540.928-0.0500.6670.63550.7930.6920.7220.6670.6350.920-0.1280.5960.57360.6560.6730.7390.5960.5730.826-0.1690.5190.49470.6100.7480.6640.5190.4940.716-0.1060.4740.43880.4430.7360.6770.4740.4380.645-0.2020.4110.33490.8500.8370.5480.4110.3340.5270.3230.6030.523100.7220.5420.8410.6030.5230.766-0.0440.5810.507T=2MSE=0.25130.9900.7710.6370.5810.5070.7700.2200.7330.62540.8780.5410.8410.7330.6250.922-0.0440.7060.60850.7930.6920.7220.7060.6080.927-0.1350.6310.54360.6560.6730.7390.6310.5430.826-0.1700.5530.46370.6100.7480.6640.5530.4630.721-0.1110.5050.40580.4430.7360.6770.5050.4050.646-0.2030.4420.30090.8500.8370.5480.4420.3000.5350.3150.6300.485100.7220.5420.8410.6300.4850.749-0.0260.6170.475T=3MSE=0.24430.9900.7710.6370.6170.4750.7780.2120.7630.58940.8780.5410.8410.7630.5890.909-0.0310.7450.57850.7930.6920.7220.7450.5780.932-0.1400.6670.51060.6560.6730.7390.6670.5100.826-0.1700.5890.43070.6100.7480.6640.5890.4300.726-0.1160.5400.36980.4430.7360.6770.5400.3690.647-0.2040.4760.26490.8500.8370.5480.4760.2640.5430.3070.6590.444100.7220.5420.8410.6590.4440.730-0.0070.6550.441T=4MSE=0.23730.9900.7710.6370.6550.4410.7860.2040.7960.55140.8780.5410.8410.7960.5510.894-0.0160.7860.54550.7930.6920.7220.7860.5450.937-0.1450.7060.47560.6560.6730.7390.7060.4750.826-0.1700.6280.39470.6100.7480.6640.6280.3940.731-0.1210.5760.33180.4430.7360.6770.5760.3310.648-0.2050.5120.22590.8500.8370.5480.5120.2250.5520.2980.6890.400100.7220.5420.8410.6890.4000.7090.0130.6960.404T=5MSE=0.23330.9900.7710.6370.6960.4040.7940.1960.8320.51040.8780.5410.8410.8320.5100.879-0.0010.8310.51050.7930.6920.7220.8310.5100.943-0.1500.7480.43760.6560.6730.7390.7480.4370.826-0.1700.6690.35770.6100.7480.6640.6690.3570.737-0.1270.6150.29080.4430.7360.6770.6150.2900.649-0.2060.5510.18490.8500.8370.5480.5510.1840.5620.2880.7220.352100.7220.5420.8410.7220.3520.6880.0350.7400.366T=6MSE=0.23030.9900.7710.6370.7400.3660.8030.1860.8690.46640.8780.5410.8410.8690.4660.8620.0160.8790.47250.7930.6920.7220.8790.4720.949-0.1560.7920.39660.6560.6730.7390.7920.3960.826-0.1700.7140.31670.6100.7480.6640.7140.3160.744-0.1340.6570.24680.4430.7360.6770.6570.2460.650-0.2070.5920.13990.8500.8370.5480.5920.1390.5720.2780.7580.302100.7220.5420.8410.7580.3020.6640.0580.7870.324T=7MSE=0.22930.9900.7710.6370.7870.3240.8130.1770.9090.41940.8780.5410.8410.9090.4190.8450.0330.9300.43250.7930.6920.7220.9300.4320.955-0.1630.8400.35360.6560.6730.7390.8400.3530.827-0.1700.7610.27370.6100.7480.6640.7610.2730.751-0.1410.7010.19980.4430.7360.6770.7010.1990.651-0.2080.6370.09290.8500.8370.5480.6370.0920.5830.2670.7950.248100.7220.5420.8410.7950.2480.6390.0830.8370.280T=8MSE=0.23130.9900.7710.6370.8370.2800.8240.1660.9520.36940.8780.5410.8410.9520.3690.8260.0520.9840.38950.7930.6920.7220.9840.3890.962-0.1690.8900.30760.6560.6730.7390.8900.3070.827-0.1700.8120.22770.6100.7480.6640.8120.2270.758-0.1480.7490.14980.4430.7