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  • 大小: 6KB
    文件類型: .m
    金幣: 1
    下載: 0 次
    發(fā)布日期: 2021-05-28
  • 語言: Matlab
  • 標簽: ARIMA模型??

資源簡介

ARIMA模型-matlab代碼，可以根據自己的實際情況進行參數調節(jié)，實現(xiàn)所需要的效果。

資源截圖

代碼片段和文件信息 

%?y=xlsread（‘D:\2017-研一\金澤1號測亭和吳江水質\test.xlsx‘‘金澤1號測亭COD‘‘B1:B31214‘）
%y=xlsread（‘D:\2017-研一\金澤1號測亭和吳江水質\全市水量數據\全市小時級別水量.xlsx‘‘sheet1‘‘B2:B247‘）

%%%%%%%%%%原始數據：
y=[?842.760000000000?871.460000000000??882.460000000000??977.830000000000?836.960000000000?816.960000000000?803.390000000000?849.050000000000?822.230000000000?828.120000000000?857.100000000000?868.930000000000?874.240000000000?863.710000000000?867.940000000000?863.070000000000?890.460000000000?866.580000000000?874.530000000000?864.900000000000?873.730000000000?864.900000000000?852.420000000000?881.150000000000?866.090000000000?885.250000000000?868.380000000000?860.030000000000?848.830000000000?838.300000000000?869.140000000000?868.900000000000?858.300000000000?828.300000000000?806.330000000000?841.620000000000?847.830000000000?862.340000000000?850.690000000000?850.720000000000?825.410000000000?833.610000000000?842.100000000000?854.890000000000?846.680000000000?842.090000000000?845.230000000000?871.490000000000?868.320000000000?856.340000000000?863.130000000000?863.560000000000?842.170000000000?827.260000000000?828.810000000000];
%%%%%%%%%%預處理后的數據：
%y=[?842.760000000000?871.460000000000??882.460000000000??977.830000000000?836.960000000000?816.960000000000?803.390000000000?849.050000000000?822.230000000000?828.120000000000?857.100000000000?868.930000000000?874.240000000000?863.710000000000?867.940000000000?863.070000000000?890.460000000000?866.580000000000?874.530000000000?864.900000000000?873.730000000000?864.900000000000?852.420000000000?881.150000000000?866.090000000000?885.250000000000?868.380000000000?860.030000000000?848.830000000000?838.300000000000?869.140000000000?868.900000000000?858.300000000000?828.300000000000?806.330000000000?841.620000000000?847.830000000000?862.340000000000?850.690000000000?850.720000000000?825.410000000000?833.610000000000?842.100000000000?854.890000000000?846.680000000000?842.090000000000?845.230000000000?871.490000000000?868.320000000000?856.340000000000?863.130000000000?863.560000000000?842.170000000000?827.260000000000?828.810000000000];
Data=y‘;%共60個數據
%Data=y;%共247個數據
%SourceData=Data（1:2501）;?%前250個訓練集
%SourceData=Data（1:541）;?%前54個訓練集
SourceData=Data（1:491）;?%前54個訓練集
%SourceData=Data（2:2241）;?%前222個訓練集
step=6;%后6個測試
%step=23?;%后23?個測試
TempData=SourceData;
TempData=detrend（TempData）;%去趨勢線
TrendData=SourceData-TempData;%趨勢函數
%--------差分，平穩(wěn)化時間序列---------
H=adftest（TempData）;
difftime=0;
SaveDiffData=[];
while?~H
SaveDiffData=[SaveDiffDataTempData（11）];
TempData=diff（TempData）;%差分，平穩(wěn)化時間序列
difftime=difftime+1;%差分次數
H=adftest（TempData）;%adf檢驗，判斷時間序列是否平穩(wěn)化
end
%---------模型定階或識別--------------
u?=?idda

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