1. A New Study of DSS Based on Neural Network and
Data Mining
Xianyi Qian Xianjun Wang
School of Electronic Information & Electric Engineering School of Electronic Information & Electric Engineering
Changzhou Institute of Technology Changzhou Institute of Technology
Changzhou, China Changzhou, China
hbxfqxyqxy_123@163.com
Abstract—Authors have studied a new method in which DSS has
been supported based on neural network and data mining. There II. INTELLIGENT DECISION SUPPORT SYSTEM
are three subjects which have been studied in the paper. How to As shown in Fig. 1, it is the general configuration of DSS.
make use of neural network to support DSS is the first. The There are three departments of DSS. They are language system
second is how to make use of data mining to support DSS. And (LS), problem process system (PPS) and knowledge system
the third is how to make use of neural network and data mining
(KS). Problem process system is composed of reasoning
to support DSS. Authors presented and answered some questions
system (RS), model base management system (MBMS),
of study of DSS. And we studied the principle of supporting DSS
based on neural network and data mining. The application of knowledge base management system (KBMS) and data base
IDSS based on neural network and data mining in making use of management system (DBMS). Knowledge system is composed
energy and protection of resources have been worked out in the of model base (MB), knowledge base (KB) and data base (DB).
end. [2]
Keywords-Neural Network; Data Mining; DSS; counter
spreading
I. INTRODUCTION
DSS was brought forward first in 1970s by American
scientist Scott Morton. And it had a great development in
1980s. A new subject and study has been produced. Its
functions are the integration of making use of mass data, the
organization of many patterns and the realization of scientific
decision by assistance of all directors through man-machine
alteration system. Intelligentizing is one of the developmental
directions of the study of DSS.
Neural network is a highly nonlinear constant time power
system with super great scale. Its main specials are the
complete function of network, the ability of parallel
distributing process with super great scale, the highly robust
quality and the ability of learning and associating. And it is of
the common as same as the ordinary nonlinear system. These Figure 1. Configuration Block Drawing of DSS
are attractability, dissipation, non-balance, non-reversibility,
many factors, wide connection and adaptability. It is a top Although there is a great development of the application
crossing subject which is of wide application. And the study of and theory of DSS, there is a great counterwork of DSS
IDSS based on neural network is of great application valve of because of the processing of serial program symbol. The main
practice and theory. It is one of the latest studies of DSS. problems of DSS are as following.
Data mining is knowledge discovery in database. It is a 1)Bottle-neck of knowledge learning. The way of
non-common process that effective, novel and valuable data knowledge learning of DSS generally is the man-transplanting
have been mined out among the mass data. It is that data which knowledge engineers transplant the expert knowledge to
mining is the mining of knowledge among the mass data. computer. It is of low efficiency and long time.
2)Low Ability of Problem Solution；
978-1-4244-4589-9/09/$25.00 ©2009 IEEE

2. 3)No Creation and self-learning of DSS. It is only of the There are three levels of CP network which are import
functions which programmed by developer. arrangement of ideas, argue unexpectedly arrangement of ideas
and output arrangement of ideas. The self-configuration
4)Bad ability of real time. reflecting neural network is composed of import arrangement
In order to solve the above problems of DSS, the bionics of and argue unexpectedly arrangement. The basic argument
neural network and the intelligence of mining system are made network is composed of argue arrangement and output
use of to explore the solutions in theory. arrangement. The argue arrangement of ideas which is between
the import arrangement of ideas and output arrangement of
III. FUNCTION OF NEURAL NETWORK TO DSS ideas reflects the statistics characteristics of import mode and
output mode. Then there is a reflecting between import mode
The function of neural network to DSS is as following by and output mode through argue arrangement of ideas. CP
means of analyzing of characteristic of neural network and network has been widely used in lots of fields such as modes
problems of DSS. The learning function, the parallel clustering, statistics analysis, data compressing and so on.
distributing processing function with large scale, non-linear
dynamics with constant time and the collectivity of neural
network are made use of to have a realization of automation of
knowledge learning, self-learning of natural language
processing system, overcoming the difficulties of “assembled
blast” and “infinite recursion”, adaptive parallel associating
reasoning, promotion of deciding ability of DSS and processing
of real time.
As shown in Fig. 2, a intelligent decision support system of
neural network is composed of knowledge, data and model. It
is of main four sub-systems, neural network, reasoning system,
data mining system of neural network and natural language
alteration system. [3]
Figure 3. Configuration Drawing of CP Network
There are two kinds of data mining which are directly data
mining and indirectly data mining. The aim of directly data
mining is that a model is built up by means of available data
and a special variable is described. The definition of indirectly
data mining is that no some real variable is described with a
model but some kind of relationship has been built up. [4]
B. Reasoning of Neural Network
Figure 2. Block Drawing of IDSS of Neural Network
A. Data Mining of Neural Network
Data mining of neural network is a data mining mode based
on neural network technology. There are five basic tasks of
data mining, relative analysis, clustering, concept description,
error monitoring and forecast. The forward feeding neural
network, for example BP network, is usually worked in concept
Figure 4. Sketch Map of Repeat Reasoning of Neural Network
description and forecast. The counter spreading (CP) neural
network can be worked in statistics analysis and clustering. As The main research of neural network system is the double
shown in Fig. 3, it is a configuration drawing of CP network directions reasoning method based on the data driving and aim
which created by American neural calculating expert Robert driving of neural network. Reasoning is the main method of
Hecht－Nielsen solutions. The course of knowledge reasoning is the process of
solutions. There are some problems such as “assembled blast”

3. and “infinite recursion” in the traditional reasoning method. A. Man-machine Alteration System
The parallel processing of neural network is the best method of The alteration structure has been established by man-
solving above problems. An explanation of reasoning course of machine alteration system which has input and output between
double directions associate memory (BAM) network is shown system and user. Man-machine alteration system is the
in the next. As shown in Fig. 4, the first arrangement of repeat important part of IDSS which is of all functions as shown in
reasoning of neural network is of no calculate function, but of Fig. 5.
fan-out function which is distributed the output to input. An
input vector A is applied up to power matrix and an output
vector B is turn out. And vector B is applied to the turn matrix
ＷＴ of power matrix W, then a new output vector A is turn
out. The course is repeated until a steady point of network
which A and B are constant. The steady point is called as
homeostasis. [5]
There is a formula of the repeat course as following.
B=F(AW) (1)
A=F(BWT) (2)
A is output vector of the first arrangement, herein, B is
output vector of the second arrangement, W is the power
matrix between the first arrangement and the second, and F is
power function. [6]
Equation (1) can be used to fulfill the reasoning of data
driving and Equation (2) can be used to fulfill the reasoning of
Figure 5. Configuration of IDSS Based on Neural Network and Data Mining
aim driving. Double directions reasoning can be realized by
homeostasis of BAM. The homeostasis is the crossing point of
data driving and aim driving of BAM. And it is the decision B. Neural Network, Data Mining, Solutions
solution. Neural network, data mining and solutions include two
modules which are solutions module and data mining module.
C. Natural Language Alteration System of Neural Network Data mining module works up in order to gain knowledge
The main research of natural language process (LS) is the needed through making use of the model of models base,
syntax analysis and meaning analysis based on neural network. method of methods base and knowledge of knowledge base.
Natural language is belonged to non-numerical valve symbol Solutions module works up in order to configure or half-
which is symbol flow with different numbers. It is of its own configure the problems through making use of the
syntax and means system and its data structure, means corresponding model of models base, method of methods base,
expression and calculation rules are rather different from knowledge of knowledge base and data of data base. Reasoning
numerical valve information. The core of natural language can be made use of for the non-configuration problems.
processing system of neural network is how to understand the
knowledge and the expression of natural language. The basic V. APPLICATION OF IDSS BASED ON NEURAL NETWORK
tasks of syntax analysis system based on neural network are (1) AND DATA MINING IN USING OF ENERGY AND PROTECTION OF
confirmation of syntax structure of input sentence, which is a RESOURCES
identification course based on neural network, (2)
standardization of syntax structure, which is a conclusion There is a lack of natural gas and oil in China. And there is
course that lots of input structures turn into a few of input a great air pollution of coal burning. There is a kind of new
structures according to some syntax exchanging relationships. energy，so far, biological energy , that is grain alcohol, for the
substitute of oil and natural gas. But grain alcohol is made from
grain. Therefore, it is not suitable to develop grain alcohol in
IV. IDSS SUPPORTED BY NEURAL NETWORK AND DATA
stead of oil and natural gas. Some experts suggest that marsh
MINING gas should be developed in order to replace the oil and natural
IDSS supported by neural network and data mining is gas.
shown in Fig. 5. It is derived from the combination of
traditional DSS with data mining technology in order to For the above problems, we make a research on whether
increase the intelligence of system. It is composed of man- marsh gas can be made use of in stead of oil and natural gas by
machine alteration system based on neural network, data means of IDSS based on neural network and data mining.。
mining, reasoning and solutions, data base management, The main researching movements are as following.
knowledge base management, methods base management and 1) Man-machine Alteration System which is of
models base management. convenience to users.

4. 2) Building up data base which is composed of oil, natural neural network technology into IDSS. And there are lots of
gas, coal, grain alcohol petrol, cost of marsh gas, using valve, problems which should be studied deeply in the future.
pollution, cost of over pollution, health cost and so on.
3) Building up knowledge base which derived from the REFERENCES
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