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Service
item
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1.
Building regress model of multi dimension data and special
data for users.
2.
Add the mechanisms model provided by customers to the DRS
software according to their demands.
3.
Develop data regress analysis components (.dll and .ocx
file) to satisfy user′s
requirements of data modeling in software development.
4.
Carry on work in software development of data regress and
engineering computation category. |
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Two
dimensions data model se
rvice demo
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Three
dimensions data model service demo
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Four dimensions data model service demo
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Two
dimensions data model service demo
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The
relating Two dimensions data, as Curve chart 1
From
the data checked in the curve chart, the conclusions of the
recursive model are as follows:
########################
## The
result of data report ##
########################
The
data return
1.0,8.2
2.0,4.6
3.0,4.3
4.0,4.6
5.0,5.1
6.0,5.5
7.0,5.7
8.0,5.5
9.0,5.0
10.0,3.8
The
result of data return
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To
the above data , the enhancement edition of the ‘data
regression analysis system DRS’is
used by you.
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You
do the one element regression in which the sample quantity
of the regression data is 10 groups.
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The
corresponding data in the model chosen by you are the
objective function Y, which are the second dimensional
data in each group and the first dimensional data X1.
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Set
initial value of the power to .49.
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At
present, the best model to regress these data is
the one element nonlinear, three variant Ⅰ.
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Correlation
coefficient(R):0.998440262665158
Statistical variable(F):639.633664360148
Residue standard deviation(S):8.20568908339411E-02
Biggest error:0.100178925962695681378721421
Equal
error:0.0434778
Equal relating error:0.0094209513911285916313423627
The recursive models are as follows
y = a0 + a1 * x1 ^ k1 + a2 * x1 ^ k2 + a3 * x1 ^ k3
Formula middle
a0 = 53.0773524156633
a1 = -111.002257397679
a2 = 68.6071595939835
a3 = -2.48944355659807
k1 = .470000009536
k2 = .710000009536
k3 = 1.470000009536
The
model chart of three data
The
model is used to demonstrate, not use.
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To
top
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The demo of three data
recursive model
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The
relating three dimensions data, as Curve chart 2
From
the data checked in the curve chart, the conclusions of the
recursive model are as follows:
########################
## The
result of data report ##
########################
The
data return
10,20,90
10,40,178
10,60,270
10,80,350
10,100,430
10,120,515
..............(In
the middle the data ellipsis)
70,200,990
80,100,920
80,120,955
80,140,1020
80,160,1055
80,180,1090
80,200,1120
The
result of data return
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To
the above data , the enhancement edition of the ‘data
regression analysis system DRS’is
used by you.
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You
do the one element regression in which the sample quantity
of the regression data is 72 groups.
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The
corresponding data in the model chosen by you are the
objective function Y, which are the three
dimensional data in each group and the first dimensional
data X1
and the second
dimensional data X2.
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Set
initial value of the power to 1.871.
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At
present, the best model to regress these data is the one
element nonlinear, three variant Ⅴ.
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Correlation
coefficient(R):0.999391761013444
Statistical variable(F):8897.36657079412
Residue standard deviation(S):10.0200437606299
Biggest error:3.309665
Equal
error:0.0434778
Equal relating error:.0211348280652982339123964839
The
recursive models are as follows
y = a0 + a1 * x1 ^ k1 + a2 * x1 ^ k2 + a3 * x2 ^ k1 + a4 * x2 ^ k3
+ a5 * x1 ^ k4 * x2 ^ k5 + a6 * x1 ^ k6 * Log(x2)
Formula middle
a0 = 106.74503499072
a1 = -10.5248008279283
a2 = .174240332503716
a3 = 1.7623076630686
a4 = 2.68381176972421
a5 = -3.21815581782274E-06
a6 = -.511646453024215
k1 = .991000051498
k2 = 2.041000051498
k3 = .991000051498
k4 = 1.881000051498
k5 = 1.881000051498
k6 = .781000051498
The
model chart of three data
The
model is used to demonstrate, not use.
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To
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The
demo of four data recursive model
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Four
dimensions data:
65.7,
20, 56, 2.8
65.2, 20, 53, 2.8
65.4, 10, 52, 2.8
66.7, 10, 48, 2.8
67.2, 10, 47, 2.8
71.4, 10, 45, 2.8
73.4, 10, 45, 2.8
..............(In the middle the data ellipsis)
87.8,
10, 9, 1.9
89.6, 10, 8, 1.9
88.6, 10, 8, 1.9
89.6, 10, 7, 1.9
88.8, 10, 6, 1.8
88.6, 10, 6, 1.8
The
result of data return
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To
the above data , the enhancement edition of the ‘data
regression analysis system DRS’is
used by you.
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You
do the one element regression in which the sample quantity
of the regression data is 84 groups.
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The
corresponding data in the model chosen by you are the
objective function Y, which are the three
dimensional data in each group and the first dimensional
data X1
and the second
dimensional data X2 and the three
dimensional data X3.
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Set
initial value of the power to .85.
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At
present, the best model to regress these data is the one
element nonlinear, six variant Ⅳ.
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Correlation
coefficient(R): .978284893845566
Statistical variable(F): 285.903438238213
Residue standard deviation(S): 6.52420615708014E-02
Biggest error: .1576
Equal
error: 4.943928E-02
Equal relating error: 2.11378593605741E-02
The
recursive models are as follows
y = a0 + a1 * x1 ^ k1 + a2 * x2 ^ k2 + a3 * x3 ^ k3 + a4 * x1 ^ k4
* x2 ^ k5 + a5 * x2 ^ k5 * x3 ^ k6 + a6 * x1 ^ k1 * x2 ^ k2 * x3 ^
k3
Formula
middle
a0 = .98681044401583
a1 = 7.06127446632436E-03
a2 = .190801629630409
a3 = 4.10554369554979E-02
a4 = -8.33265112895352E-03
a5 = -6.09571087259014E-03
a6 = 2.28798807062382E-05
k1 = 1.04000002384162
k2 = .940000023841624
k3 = .950000023841624
k4 = .730000023841624
k5 = .880000023841624
k6 = .860000023841624
The
model chart of four data
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Copyright: AiHua
Computer Studio, Create
date: 8/5/2007，
Email: ww_yypp@163.com
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