Intelligent Control and Automation, 2011, 2, 126-132
doi:10.4236/ica.2011.22015 Published Online May 2011 (http://www.SciRP.org/journal/ica)
Copyright © 2011 SciRes. ICA
Extension Modeling Strategy of Intelligent Detection in
D.huoshanense Photosynthesis Process
Rongde Lu1, Can Qin2, Yunsheng Bao2
1Teaching Center of Physical Experiments, Physics School, University of
Science & Technology of China, Hefei, China
2Department of Materials of Science and Engineering, University of
Science & Technology of China, Hefei, China
E-mail: lrd@ustc.edu.cn, {limbo, yongsbao}@mail.ustc.edu.cn
Received December 9, 2010; revised January 16, 2011; accepted May 7, 2011
Abstract
Aiming at the limitations of the existing knowledge representations in intelligent detection, a new method of
Extension-based Knowledge Representation (EKR) was proposed. The definitions, grammar rules, and stor-
age structure of EKR were presented. An Extension Solving Model (ESM) based on EKR was discussed in
detail, including creation of the extension constraint graph, extended inference, calculation of relevant func-
tions and generation of extension set. A knowledge base system based on EKR and ESM was developed,
which was applied in extension repository system intelligent design of detection in photosynthesis process of
D.huoshanense. More reasonable results were obtained than traditional rule-based system. EKR was feasible
in intelligent design to solve the problem of intelligent detection knowledge representations.
Keywords: Extension-Based Knowledge Representation (EKR), Intelligent Detection, Extension Modeling
Strategy (EMS), Photosynthesis Process of D.huoshanense (PPDH)
1. Introduction
About the formation of creative thinking and the inherent
regularity of the formation, it is a long period of explora-
tion in human social practice. From social science to
natural science, people are trying to find a description
form, but it comes down to a burst of inspiration, or “The
patent of genius” at end. Extenics [1] researches the laws
and the methods of tings exploiting from things exten-
sion nature. As crossing academics, Extenics [1] lies in
philosophy, thinking sciences and mathematics, and is
used to solve a large number of contradictions and
pseudo-contradictions existing in real world. Extension
analysis breaks through old intuition or inspiration mode
of discovery creative work and establishes formalization
road to new discoveries, new inventions. Extension
analysis makes ordinary people complete creative found
work which used to be done only the wise.
Extension Modeling Strategy (EMS) uses to generate
and exploit strategy set in modeling photosynthesis
process of D.huoshanense, be able to provide adequate
options for develop the correct modeling strategy. It can
exploit more new programs to form the optimum strategy
to solve practical problems when existing programs can
not meet the requirements. The object of D.huoshanense
photosynthesis process researched by EMS is variability,
so the use of change and development perspectives to
research practical issues is involved. Analyzing the ob-
ject of D.huoshanense photosynthesis process in a dy-
namic system whose time, space and other factors
change always, generates many programs, which is the
basic form of the optimum modeling strategy, and this
can not be seen directly. EKR [2] combines qualitative
analysis and quantitative calculation. According to the
extension of matter element when conflict between
achieve the objective and constraints, or conflict during
number of strategic objectives, using divergent, conjuga-
tion, relativity, implication and scalability of matter ele-
ment exploits generation strategy set in extension mod-
eling decision-making process. In a broader time and
space to consider strategies of managing conflict, and
through quantitatively calculation of the matter-element
transformation and matter-element theory to improve
strategies in accuracy and operation, EMS [3] does not
exclude other strategy approaches and has a preferable
compatibility with a variety of qualitative or quantitative
R. D. LU ET AL.127
strategy techniques. When meeting contradictions in de-
cision process of EMS, EMS will play its unique advan-
tages, combined with other strategies, in order to gener-
ate the best strategy. The part uses EMS to solve incom-
patible problem of control strategies at different stages of
D.huoshanense photosynthesis process and the ill-posed
problem of gaining empirical experience.
2. Extension-Based Knowledge
Representation
2.1. Divergence Method Generated by
Modeling Strategy
Establish the matter-element of decision objectives and
restrict constraints {P}, {p}.
According to the divergence of matter element (a mat-
ter with multi-feature, one feature with more matter, one
value with more matter) [1], objective matter element is
developed using transformation

,
cN
N
c
TT TT  as
follows.


 
123
,,1,2, ,
,, 1,2,,
iii
jjj
PP Ncviq
Ncvjq
WPW PWP



(2.1)
According to the matter-element conjugation (imagi-
nary-real, hard-soft, appearance-latent, positive-negative),
with transformation T = Tg analyses of material, system-
atic, dynamic and opposite of objective matter element
is:

4
,,,,,, ,
im re sfhr ltap ngpc
PPPPPPPP WPP┤ (2.2)
Analysis method of matter-element relevance and im-
plication:
According to the scalability (additive, integral, divisi-
bility) of matter-element, using transformation
///
to integrate conditions matter-
element r = (N', c', v'):
TT T TT



 
///
///
pppp
WpWpWpWp



p┤ (2.3)
Find all the matter-element or the matter element subset
contain p in the matter-element set

12
WP WP
 


  


 
,
///
1234
///
,,, ;
,,, ;
;
{}
PcNg
Nc
p
P
p
TTTTT
TTTTT
TWPWPWPWP WP
TWpWpWpWpWp




 ;
(2.4)
 

 


,:,:,1,2,,;
,:,:, 1,2,,;
|,1,2,,,
i
i
iiiRRirr
YRRRWR RWRik
TrrWr rWr ik
TTTYTTTTTikR r

 



 
(2.5)
If

1234
WR WR WRWR
and
Wr
///
Wr WrWr
contain a large number of
matter elements, then search of W*(R), W*(r) and the
W(R) may be completed by the computer.
According to the need of EMS, we still can extend
modeling goals R by matter-element scalability, and ex-
tend condition r through the matter-element divergent,
feasibility, relevance and implication. It can make con-
tent of W(R) and W(r) richer, and forms more choices of
strategy, which used to solve the contradictions and
pseudo-contradictions in EMS. Below discusses the ap-
plication of ill-posed problem which was found by em-
pirical experience in D.huoshanense photosynthesis sys-
tem based on matter-element conjugate strategy in detail.
The matter-element conjugated system is a kind of rela-
tively closed system. The commonly met problem is how
to transform a non-coordinated matter-element conjugate
system into coordinated matter-element conjugate system.
In this section we would solve the method of this prob-
lem, and apply it to the comprehensive modeling in
D.huoshanense photosynthesis system, to produce suc-
cessful conjugate strategy.
2.2. The Matter-Element Conjugation and
Conjugate Transformation
constitute W*(P); Find all the matter
element or the matter element subset contain p in the
matter-element set
 
34
WP WP

///
WpWpWp
or the matter element subset can take place of P consti-
tute W*(P), select the element in W*(P) to be able to satisfy
some element request in W*(p) to constitute W(P), cor-
responding element in W*(p) constitutes W(p), this proc-
ess can be described by following transformation [1]:
Wp
The matter-element conjugation scoring structural prop-
erties of the matter element, it understands and analyzes
things N in material, systematic, dynamic and intrinsic
opposition and unity from different angles. The matter-
element conjugate structure presents four forms: imagi-
nary-real, hard-soft, appearance-latent, positive-negative.
Expression for imaginary-real: N = reN imN, where
reN means the real part of N, while imN means the
imaginary part of N;
Expression for hard-soft: N = hr N sf N, where hr N
and sf N denote the hard part of N and the soft part of N
respectively;
Expression for appearance-latent: N = ap N
lt N,
where ap N and lt N correspondingly denote the appear-
Copyright © 2011 SciRes. ICA
R. D. LU ET AL.
128
ance part and the latent part of N;
Expression for positive-negative: N = ps(c)N
ng(c)N,
with ps(c) and Nng (c)N representing the positive part
of N (about characteristic c) and the negative part of N(c)
correspondingly.
When the matter-element transformation φ acts on
certain part of the thing N(e.g. φ (hrN)) which has the
aforementioned structure, it often leads to another part of
the N(e.g. sf N) change, and leads to the change of the
whole N. Here the transformation φ is an initiative trans-
formation, the transformation caused by φ is conduction
transformation, as Tφ. Such conduction transformation
happens in tings conjugate department called conjugation
transformation [4].
2.3. Matter-Element Conjugation System and
ITS Classification
Suppose relative closed system Σ with only two elements
Ni(i =1, 2), and N1//N2, L(N1, N2) is external connection
relation. Under the L(N1, N2) function, if N1 and N2 are
interdependent relations, we call for a matter-element
conjugate system, as = N1L (N1, N2)N2.
Property 1:
 
11222 12
,NLNNNNLNNN1
, (2.6)
Now, if regard as a thing, the hard part of
is
, and the soft part of is
12
,hrN N
,
12
s
fLN N. Hence, the structural relationship:
Property 2:

12 12
,hrsfN NLN N 
, (2.7)
For ting Ni(i = 1, 2),examine the matter-element Ri =
(Ni, ci, vi) (i = 1, 2), and the extension relation of matter
element:
 

12121 2
12 12
,, ,,
,,
WRRyRRWW
ykRR kvv


(2.8)
Here

 
,,,, 1,2
iiiiii ii ii
WRRMccMcMVci 
,
is quantity territory of characteristic ci,k(v1,v2) is
correlation function of corresponding in the extension
relations r.

i
Vc
When k(R1, R2) 0, to call for non-coordinating
matter-element conjugate system, as –. Or call
for coordinating matter-element conjugate system, as
+. In particular:
Property 3:

1122
,NLNN N (2.9)
Through property 2 and the meaning of correlation
function, non-coordinating matter-element can be de-
duced to be a conjugate system – which has contra-
diction waiting for solving. In-depth analysis principal
aspect and the non-principal aspect of contradictory,
primary reason causing system’s non-coordinative can be
found. If the non-coordinative of is mainly caused
by the soft ministry sf
, we say for soft contradic-
tion system, as
sf; if the non-coordinative of
mainly caused by the hard ministry hr, we say
for
hard contradiction system, as hr. Non-coordinated
element conjugated system is either the soft contradic-
tory system, or the hard contradictory system.
Our goal is seeking the matter element transformation
T, which transforms the non-coordinated matter-element
conjugated system
– to the coordinated matter-element
conjugated system *
. Namely seeking T, T:
*
. Here,
***
112
,NNN
** *
2
is coordinated
by the matter-element conjugated system. That is to say,
for
NL
jj
v
*
RN,,
ii
c
*
1
R
, (i = 1, 2), and are the
relation of matter-element extension [5].
*
2
R



** **
12121 2
**
12 12
,, ,,
,,
A
WRRyRRWW
ykRRkvv


(2.10)
k(v1,v2) is correlation function of corresponding exten-
sion relations r*,and
**
12
,0kR R.
2.4. The Selection Principle and Conjugate
Strategy of Matter-Element Transformation
Since
– is relatively close to realization of the system,
to realize the
– to *
, we only can seek transform
internal factors and transform way in inter system. The
matter-element conjugation and matter-element trans-
formation method provide a feasibility basis for this. In
fact, the conjugate structure of directly leads to the
transform principle of realizing the transformation
to *
with the matter-element transformation method.
Principle 1: Desire for matter-element transformation T,
preferred matter-element transformation of *
:T

is soft and hard transformation.
Principle 2: if
– is soft contradiction system
sf,
desire for *
:f
Ts
 , We first choose initiative
transformation φ as the matter-element transformation to
put on sf
; if
– is hard contradiction system
hr,
desire for *
:Thr
 , We first choose initiative
transformation φ as the matter-element transformation to
put on hr
.
Suppose initiative transformation ,TT
is the
conduction transformation caused by φ. The mat-
ter-element transformation in above principles can be
expressed:
,
hr
TT
,

,
sf
TT
.
As a result:
Principle 3:
Copyright © 2011 SciRes. ICA
R. D. LU ET AL.129
 
,
hr sf
ThrT sfTT hrsf

 
*
,
(2.11)
Record Thr and Tsf as T*, when the initiative transfor-
mation φ in T* is conjugate transformation, namely when
φ {imaginary-real transformation, hard and soft trans-
formation, appearance-latent Transformation, positive
and negative transformation}, call T* conjugate strategy.
Suppose T* is conjugate strategy, and ,
we call T* successful conjugate strategy, otherwise, T* is
called unsuccessful conjugate strategy. All successful
conjugate strategy constitute the successful conjugate
strategy collection L(T*), correspondingly with coordi-
nated matter-element conjugate system collection L
().Compare various strategies in strategy set L(T*),
the optimal strategy as a final decision can be deter-
mined.
*
:T

*
In applications, the implementation of conjugate
transformation depends on conjugate converter. If you
cannot construct suitable conjugate converter, T* is
non-real strategy, no practical significance.
2.5. Application of Extension Comprehensive
Modeling System in Photosynthesis Process
In limited matter element, particularly in the control sys-
tem of D.huoshanense photosynthesis process, we have
two ways to get process information: the data detected by
process sensor and the experience of scene planting ex-
pert. But experts’ experience is descriptive and is diffi-
cult or impossible to describe quantitatively (such as
experts’ experience which is perceivable but indescrib-
able or confidentiality). The system modeling must use
this part of experts’ experience in the D.huoshanense
photosynthesis process. Experts’ experience is affected
by many facts, it is very difficult to ensure experts’ ex-
perience correctly reflecting the true nature of the proc-
ess. This may cause workability process information to
be sometimes serious shortage, sometimes squandered in
D.huoshanense photosynthesis system modeling. We use
the conjugate strategy to solve this problem.
Let be N1 = extension modeling of D.huoshanense
photosynthesis process, N2 = experts’ experience,
L(N1, N2) = experience model, when other factors are not
considered, relatively closed system:

1122 1212
,,N LNNNNNLNN 


1 111
,,QNcvt
is a
matter-element conjugated system. Examine the matter
element and
t
222
,,QNcv
2
Here c1 = available information content in unit time, v1
= a (information entropy and constant), c2 = the offer
information in unit time, v2(t) is the function of time t, in
the period of sufficient information, v2(t) > a; in the pe-
riod of lack information,v2(t) < a.
.
For matter-element extension relations A(W) of Q1 and
Q2, correlation function k(Q1,Q2) < 0. is non-coor-
dinated matter-element conjugated system. Through close
observation of the process of the system and environ-
ment of D.huoshanense photosynthesis process, the ex-
perience model of the system is found to get in long-term
production practice. But when applied to D.huoshanense
actual photosynthesis process, despite of large error with
the actual process of photosynthesis, it contains rich of
on-the-spot experts’ experience information, specially
has the quality experience information of D.huos-
hanenses. If matter-element transformation of extension
theory can be used to blend expert experience model and
the computer intelligent model, thus makes experts’ ex-
perience that perceivable but indescribable or confidenti-
ality give way to the scene plants the empirical model; in
production field that expert is difficult to or is unable to
accurate calculate or determination give way to the
computer intelligence model. Then achieves the effect of
“Cao Chong weighs elephant”, hopefully get the innova-
tion knowledge form it. Using this empirical model, in
the period of sufficient information, the informative
2
()vt a
as information power stores information (in-
formation changes from appearance to latency), while in
the period of lack information, it can timely analyze its
information (information changes from latency to ap-
pearance, to supplement information of the computer
intelligence model when it lacks of information, and get
a new information gain-using system) [4]. Therefore,
choose the initiative transformation φ = appear-
ance-latency transforms, T
,
,T
*T
, then

****
112
,ThrTsf NLNN

 
***
2
N
(2.12)
Here, , 3
(N3 is empirical
model), then
*
11
NN*
22
NNN
*
2
N
**
LN
*
11
QQ
1
, is new system.
Now,
, 22
1,
*
22
QR R

212 2 21
,,RNcvt,
t
22
RN3 2 22
,,cv , and
 
 
21
2
22
2
,
,
0,
,
at
vt vtt
t
vt avtt




(2.13)
where = {period of sufficient }, Ψ = {period of lack}.
For matter-element extension relations A*(W) of
and , correlation function ,
*
1
Q
*
*
2
Q

**
12
,0kQ Q
is
non-coordinated element conjugated system. The conju-
gate converter may take:
It is difficult or impossible to describe experts’ ex-
perience gain empirical model use of experts’ ex-
perience, therefore T* is a successful conjugate strategy.
Copyright © 2011 SciRes. ICA
R. D. LU ET AL.
130
3. Matter-Element Extension Transformation
Method of Modeling Strategy
According to the request of modeling strategy in D.huos-
hanense photosynthesis process, determine purpose mat-
ter-element of D.huoshanense:

,, ,,WRRNcvNUvV 
.
And appropriate correlation function,
y
Kv,
, , establishes the matter-element
extension set in W:
vV
,y
 
,
A
RRyyKRKv (3.1)
Production strategy, also can say seeking transforma-
tion T, makes negative field matter-element R(K(R) 0)
transform into positive field matter-element (K(R) 0).
That is to say determine transformation T which can de-
termine A+(R)(T), seek transformation TR, TK, TW from
three angles that matter-element R, correlation function
K and the universe of discourse W to formation positive
extension field of matter-element:
 
  



 
,0,0
,0,0
,0,(),
RR
KK
WW
ART RRWKRKTR
ARTRRWKR KTR
ARTRRWKR RTWKR
 

 
0
(3.2)
According to the current research of the extension
theory, we can make choice mainly in displacement
transformation, additions and deletions transformation,
extend and reduce transformation, decomposition trans-
formation, transition transformation, catalytic transfor-
mation and recover loss transformation, also can consists
transformation combination
1, 2,,
i
TTi k
us-
ing four operations (product, and, or, inverse) of trans-
formation [1].
Start with method of generating strategy set from ex-
tension matter-element extension field, mainly aimed at
incompatibility issues of target and conditions during
modeling strategy, we can exploit more practical model-
ing strategies to meet the needs of the right strategies
using extension analysis method.
3.1. Transforming Bridge Method of Modeling
Strategy
Opposition problems (the same conditions contradiction
between two groups target strategy under the same con-
ditions) can be seen everywhere in real-life .In the con-
flict of the area, often use the struggle method (It may
cause new conflict), or use balance method (can defer
outbreak of conflict). If choosing transform bridge
method, setting appropriate transforming bridge, we
transform each index system (or operation rules) of con-
tradiction target form opposition system into coexisting
in combination areas. That is a new method of formaliza-
tion of creative thinking process .Microclimate environ-
ment of greenhouse has three stages of control strategy to
planting process of D.huoshanense: switch control strat-
egy of the stage transplanting seedling of D.huoshanense
to field, predictive control and feed-forward control
strategy of survival stage of seedling, tracking control
strategy at stable growth phase. The third groups of
strategy are in the same microclimate environment of
greenhouse, but the goal of three strategies under the
condition is different. In the conflict the area, setting
appropriate transforming bridge, we transform index
system (or operation rules) of three strategies goals into
coexisting in combination areas. We make them exist in
greenhouse microclimate environment, and achieved the
effect that operates separately, takes their want.
First discusses two group of opposition strategies [4]:
let be two opposing strategy targets as system L1 and
system L2, index system is expressed as multidimen-
sional dynamic matter-element S1(d, t) and S2(d, t), M =
(S1(d, t), S2(d, t)), then S1 and S2 is a opposing system of
M: (L1L2, M).
Setting combination areas Ai(L1, L2), (i = 1, 2, , k)
in the conflict the area of L1 and L2, establishing: L =
L1Ai(L1, L2)L2, Index system of system:



11
12 1
22.
,in;
,,,on
,in
i
Sdt L
SdtSdtSdtA LL
Sdt L

2
,
.
;
(3.3)
L is compatible system of L1 and L2 which is a oppos-
ing system of M, Ai(L1, L2) (i = 1, 2,, k) is the trans-
forming bridge of L1 and L2.
Let be Ai(L1, L2) = (O1 and O2 respectively are move-
ment track of L1 and L2),index system of Ai(L1, L2) is
 

11
12
22
,on
,,, ,on
Sdt L
SdtS dtSdtSdt L

(3.4)
On the transforming bridge Ai(L1, L2), movement track
is O = O1O2, we usual use space passage k(d) or time
channel k(t) to insulate O1 and O2.
Then discusses three group of opposition strategies: let
be three opposing strategy targets as system L1, system
L2 and system L3, index system is expressed as multidi-
mensional dynamic matter-element S1(d, t), S2(d, t), and
S3(d, t), then S1, S2 and S3 is a opposing system of M:
(L1L2L3, M).
Setting combination areas Aij(L1, L2, L3), (i = 1, 2, ,
k, j = 1, 2, 3) in the conflict the area of L1, L2 and L3. es-
tablishing: L = L1Ai1(L1, L2)L2Ai2(L2, L3)L3
Ai3(L2, L3)L1, index system of system:
 
Copyright © 2011 SciRes. ICA
R. D. LU ET AL.
Copyright © 2011 SciRes. ICA
131
2
3
1
;
;
;
3.2. Evaluation and Selection of Modeling
Strategies


 


 



11
12 11
23 22
31 33
22
33
,in;
,,on,
,,on,
,,,on,
,in;
,in;
i
i
i
Sdt L
SdtS dtA LL
SdtSdtA LL
SdtSdtSdtALL
Sdt L
Sdt L
(3.5)
We should value each strategy in D.huoshanense photo-
synthesis process strategy set, and chose a better strategy
for use. We can take superiority evaluation method in the
process of evaluation and selection, (see Figure 1) [6]:
1) According to technical indexes of D.huoshanense
photosynthesis process control, the economic value and
quality determine of Chinese medicine experts, we can
ensure conditions set which is used to measure: r = {r1,
r2, , rn}, ri = (ci, vi), vi is quantity range, i = 1, 2, , n.  
L is compatible system of L1, L2 and L3 which is a op-
posing system of M, Aij(L1, L2, L3)(i = 1, 2, , k, j = 1,
2, 3) is the transforming bridge of L1, L2 and L3.
2) Selecting the conditions satisfy with D.huoshanense
photosynthesis process, as m = {m1, m2, , ms}, we
uses it to sift concentrate strategy in strategy set; then
bestow the weighting factor between [0,1] to the rest
measure condition according to its important degree: α =
{α1, α2, , αn},
1
i
.
Let be Aij(L1, L2, L3) = (O1, O2 and O3 respectively are
movement track of L1, L2 and L3), index system of Ai(L1,
L2, L3) is:
 




123
11
22
3
3
,,,
,on ;
,;
on
;
on
,
SdtS dtSdtSdt
Sdt L
Sdt L
L
Sdt

,
(3.6) According to the condition α, through primary selec-
tion of produces strategy, the strategy accord with the
requirement for α is:
1, 2,,
jj
UUj m.
3) Establishing correlation function ki(x) on Vi, calcu-
lating standard qualified degree of Uj respect to ri:ki = (ri1,
ri2, , rim), i = 1, 2, , n.  
On the transforming bridge Aij(L1, L2, L3), movement
track is O = O1O2O3, we usual use space passage
k(d) or time channel k(t) to insulate O1, O2 and O3.
4) Computation goodness of fit:
Figure 1. The extension solving model (ESM) based on EKR [6].
R. D. LU ET AL.
Copyright © 2011 SciRes. ICA
132
1
,1,2,,
n
jiij
i
BUk jm



. (3.7)
Best strategy:


0max1, 2,,
j
BUBU jm
(3.8)
4. Conclusions
Since the limitations of the existing knowledge repre-
sentations in intelligent detection, this article proposes a
new representation based on multi-level Extension Mod-
eling Strategy and develops a corresponding detection
system of D.huoshanense photosynthesis process, which
has positively be carried on the new exploration to the
intellectualized modeling strategy. Compared with the
previous modeling strategies, choosing different selec-
tion size according to features of different growth phase,
this method not only can avoid the phenomenon that the
explosion of elements reorganization in modeling strate-
gies, still can make the innovation of new strategy set in
higher levels. At the same time, with the formalized in-
ference technology of extension theory, combining with
quantitatively reasoning, and it successful realize the
transition between concept model and detailed model of
detection strategy in D.huoshanense photosynthesis pro-
cess. Further work is research algorithm complexity of
POADES (Problem Oriented Analysis and Decision Ex-
pert System) [7]; Increases the structure operator on the
basic of POADES to strengthen the ability that descrip-
tion model concept or relational, make the description
logic be adapted to the needs of various applications.
5. Acknowledgements
This work has been supported by Financed project of
NSFC, under 60974038 grants.
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