This PPT is about the GREY SYSTEM THEORY which is some what relayed with the data mining subject

1. INTRODUCTION

2. • Data mining is an interesting focus in
computer science field now.
• Current data mining research is focused
almost exclusively on big data.
• Data mining with limited and incomplete
data offers valuable supplement yet to date
has attracted little attention.

3. • A well defined data mining method for
small and incomplete data does not yet
exist.
• The Grey System Theory provides such an
alternative for data mining with small and
incomplete data.
• Grey Systems have delivered great success
in China but has not yet obtained
significant attention in Europe.

4. • As an emerging subject, the models
in grey systems can be further
improved and there is considerable
work to be done to make it more
accessible for ordinary users who
know little about it.

5. • In the view of data mining techniques
with embedded knowledge, we think
that modeling of Grey system itself is
a kind of KDD and the data of
economic
phenomena are often regard as the
time sequence data.

6. • Projects which have been successfully
completed with the Grey System theory
and its applications are as follows:
• 1. Regional economic planning for several
provinces in China.
• 2. To analyze agricultural economy in
China

7. • 3. To build models available for biological
protection.
• 4. To control the water level for boilors by
grey prediction control.
• 5. To estimate the economic effect;
• 6. To build a diagnosis model available for
medicine;
• 7. To forecast weather.

8. • The essential contents and topics of Grey
System theory encompass the following
areas:
• grey relational space
• grey generating space
• grey forecasting
• grey decision making
• grey control
• grey mathematics

9. • A grey system means that a system in which
part of information is known and part of
information is unknown.
• With this definition, information,
quantity and quality form a continuum from a
total lack of information to complete
information – from black through grey to
white.

10. • Grey analysis then comes to a clear set of
statements about system solutions . At one
extreme, no solution can be defined for a
system with no information. At the other
extreme, a system with perfect information has
a unique solution. In the middle, grey systems
will give a variety of available solutions.

11. APPLICATIONS
• The theory has been applied in various field of
engineering and management. Initially, the
grey method was adapted to effectively study
air pollution and subsequently used to
investigate the nonlinear multiple-dimensional
model of the socio-economic activities’ impact
on the city air pollution . It has also been used
to study the research output and growth of
countries.

12. Mathematical Presentation Of
Prediction Models

13. Mathematical Presentation Of
Prediction Models

14. Mathematical Presentation Of
Prediction Models

15. Mathematical Presentation Of
Prediction Models

16. Case Study
• The GM (1, 1) , the Verhulst model and the GM
(2, 1) are used for comparison. The woman
suicide data [1, 2] in India from 2008 to 2013 is
used to demonstrate the effectiveness and
practicability of the models. The data of women
suicide in 2006-2010 is presented to form the
three grey prediction models and the data of
women suicide from 2011 to 2013 is used as data
set to compare the accuracy of the three
prediction models.

17. Case Study