利用灰色理论数据预测及MATLAB代码(数学建模)
Building feasible models
It recognizes that there exist a few models to estimate of future performance
using currently-available data. For these different methods, each model has
some advantages or disadvantages. According to the existing forecasting
theory, two models can be offered here:
polynomial fitting model
During the engineering and scientific research, people usually represent the
relationship between two different variables and the variation tendency with
the aid of smooth curve on the condition that several reliable data are known.
It is supposed that all the original data has several noisy records, as the
result ,the function we get only presents the variation trend. Fitted curve is not
required to pass all the known data. We use Minimum variance function to
assure that the global error during the fitting progress is the minimum.
Grey Theory Prediction Model
Within the grey system, some of the data are known and the others are
unknown. In addition, their relationships are uncertain. The coral of the model
is to find regular pattern after the Handling Processing of the original data.
Comparison of the two model:
We choose the PH of the Suzhou Xishan from week 25 to 34 as the
original data.
Suzhou Xishan
WEEK PH
25 7.56
26 7.26
27 7.31
28 7.47
29 7.6
30 7.41
31 7.55
32 8.0
33 7.55
From: China's Ministry of
Environmental Protection (MEP)
1.grey system
according to this, after the Accumulated Generating Operation to the original
data, new rec
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