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Aiming the problem of low accuracy during establishing grey model in which monotonically decreasing sequence data and traditional modeling methods are used, this paper applied the reciprocal accumulated generating and the approach optimizing grey derivative which is based on three points to deduce the calculation formulas for model parameters, established grey GRM(1, 1) model based on reciprocal accumulated generating. It provides a new method for the grey modeling. The example validates the practicability and reliability of the proposed model.

The main characteristic of grey system theory is the research about small data and uncertainty, and the basic tool is grey generation. Behavioral data of the system may be chaotic and complex, but there is always some kind of law among them. Grey generation is to find the law from these behavioral data, and establish grey model according to the law, further predict the system by solving the model [

Definition 1. Supposed the original sequence

,

let, , then

is named for reciprocal sequence of.

Definition 2. Supposed the original sequence

let where,

then is called as one-time reciprocal accumulated generation of.

Definition 3. Supposed the original sequence

let, where, then

is called as one-time reciprocal regressive generation of. The inverse accumulated generation is the inverse of accumulated generation, and they meet that

.

It is known that the solution of equation

is. When this curve is used to fit, the key is how to deal with the derivative signal of discrete points. We take three points, and in the exponential curve with monotone decreasing and up-concave. It is known easily that the slope of the curve at the point is between the ones of and, namely,

The albino equation of grey differential equation is, so it can be discretized into:

where, is the related coefficient with a, a is development coefficient and b is the control coefficient.

Supposed

,

and. Equation (3) can be expressed as. The following equation can be obtained by using the least squares method:

When the first component of is taken as initial condition of grey differential equation, the continuous solution of albino differential equation in the initial conditions is:

Its discrete solution is:

The model value of the originnal sequence can be obtained by regressive generation.

Then the model value of the original sequence by using Definition 1 is obtained.

Presumed that is in the exponential curve, the accurate conditions during modeling is that two equations between Equation (3) and Equation (7) are satisfied at the same time. Equation (3) substituted by Equation (7) is simplificated, and then a relationship between and a can be established as:

Since that Y is the function of in Equation (4) and is the function of a in Equation (8), as long as giving an initial value of a, can be obtained in Equation (8). Substituting again into Equation (8) will obtain and into Equation (4) calculate a. After iterating several times the exact value will be found. After defining the absolute error, the relative error and the mean relative error, we wrote the Matlab program named as GRM for grey GRM(1, 1) model based on reciprocal accumulated generating, where as long as inputting the known data, the corresponding error and accuracy of the model can be obtained.

There are the fatigue experimental data (Mpa) in [

.

The fitting value of the data is

= [560, 540.8374, 19.4263, 498.8629, 479.1135].

The relative error (%) is

= [0, −0.15508, 0.6833, 0.22743, −0.86599].

The mean of the relative error is 0.38636%.

This model has high precision.

The mean relative error in the non-homogeneous model based on traditional accumulated generating in reference [

in reference [

This paper applied the reciprocal accumulated generating and the approach optimizing grey derivative which is based on three points to deduce the calculation formulas for model parameters in the condition that the first component of was taken as initial condition of grey differential equation, established homogeneous GRM(1, 1) model based on reciprocal accumulated generating. This model with high precision has better theoretical and practical significance. Example validates the practicability and reliability of the proposed model.