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ISBN 978-952-5726-09-1 (Print)
Proceedings of the Second International Symposium on Networking and Network Security (ISNNS ’10)
Jinggangshan, P. R. China, 2-4, April. 2010, pp. 009-011
Analysis of Uncertainty Information for Several
Kinds of Complex Systems
Jiqin Peng, and Jinfang Han
Science College, Hebei University of Science and Technology, Shijiazhuang 050018 ,Hebei China
pengjiqin8787@126.com , Jfhanemail@126.com
Abstract—In this paper, three kinds of uncertain complex
system are discussed by analyzing uncertainty of
information, and their respective connotation characteristic
along with the main difference and connection are
elaborated from theory method, which make it convenient
for people to best distinguish and handle uncertain problem.
Finally, a kind of uncertain information system just born
and a vital problem remaining to be solved are provided.
Index Terms—uncertainty System, Information, Random,
Fuzzy ,Grey, Unascertained
I. INTRODUCTION
With respect to the uncertainty of complex system,
Professor Wang Qingyin [1] have partly discussed and
inquired. Some study methods and mathematics relation
between four kinds of uncertainty have been provided and
discussed, which open up train of thought, establish basis
for further recognizing and deeply studying complex
system. The uncertainty of system is uncertain
information System contain. Uncertain information is the
information with uncertainty. Some uncertain information
will accompany with the description of system
information characteristic. In this paper, the uncertainty of
system is introduced and discussed in other point of view;
the respective characteristic of various kinds of uncertain
system are expounded. The paper sum up, compare,
contrast in many aspects to explain that which method is
used to solve the uncertain problem of complex system
under what situation (condition).
II. UNCERTAINTY OF SYSTEM INFORMATION
To identify a system is to identify its information
characteristic, information characteristic is mainly the
unity of system’s essential factor, structure, function. A
system can’t be described and expressed without these
information characteristic. But, in respective aspects from
the generation of information to the description of
information characteristic, the information grasped is
uncertain owing to various reasons. For example, in the
process of information generation, transmission and
receiving, owing to the disturbance of outside disturbance
source, some distortion phenomenon usually happen
when source information arrive at clinic information
through channel. When recognizing and describing
system’s information characteristic, owing to the
objective thing’s complexity, people subjective
knowledge’s limitation, natural language’s intrinsic
uncertainty, the quality’s appearance, the quantity’s
provision, relationship’s expression and law’s find, people
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can’t truthfully reflect objectively existing things.
Distortion and no easily exact reflection make information
uncertain. For uncertainty is universal in objective reality,
people have to study, build up and apply uncertain
information system. Via analyzing several kinds of
uncertain information, different uncertain systems are
expounded
Random Information
A lot of actual problems involve the analysis and design
of system disturbed by environment uncertainty. The
uncertain disturbance may be caused by different source.
Among them, a kind of disturbance source is a certain
causality that does not happen between condition and
event because the condition is insufficient. Hence, it is
uncertain whether the event happen or not (namely the
event maybe happen or not). The kind of uncertainty is
called randomness.
For random system, or in handling random problem in
reality, the main mathematics tool adopted is statistical
mathematics, that is, probability statistics (containing
random process). It may be called the theory method of
handling random system.
The characteristic of probability statistics is many data.
Probability statistics faces uncertainty of infinite data but
no law; it solves the problem of “big sample uncertainty”,
the data demanded is classical distribution. For example,
the distribution used frequently is binomial distribution,
Passion distribution, uniform distribution, normal
distribution…etc. Among them, the normal distribution is
used most. The basis of probability statistics is Cantor set,
the set of “1” and “0”. The elements of set have the
property of Yes or not, the means of probability statistics
is “statistical”, namely, acquiring law via statistics. The
goal of probability statistics is historic statistical law. A
big sample studied contains all the data of reality and
unreality time zone, reality time zone is transient relative
to unreality time zone, therefore, via statistical way, all
statistical data embody historic statistical law. Hence, the
thinking way of probability statistics is “appear again”.
The information criterion of probability is infinite
information. Because of footing “big sample uncertainty”,
probability statistics handle problem in infinite
information space.
Fuzzy Information
Owing to the complexity of things, for many things, its
boundary isn’t obvious, characteristic is not explicit, so
the information about them is uncertain, namely fuzzy.
The things that have existed and happened in objective