Design and Implementation of the Intelligent Decision Support
System Platform Under the Big Data Environment
Lingyu Chen
Innovation and Entrepreneurship College of Liaoning Vocational University of Technology,
Jinzhou City, Liaoning Province 121000, China
Keywords: Big Data Environment Algorithm, Intelligent Decision Support System, Platform Design, Operation
Accuracy, Implementation System.
Abstract: Intelligent decision support system platform design field is still in the development stage, but the intelligent
decision support system platform design has broad prospects for development field, the intelligent decision
support system platform design application evaluation is particularly important, but the current about
intelligent decision support system platform design application research is not mature, therefore, this paper
for intelligent decision support system platform design application comprehensive evaluation. Using big data
environment algorithm of intelligent decision support system platform design comprehensive evaluation, first
of intelligent decision support system platform design application related theory analysis, introduces the big
data environment algorithm, and then according to the characteristics in the field of intelligent decision
support system platform design in our country, adjust the parameters of big data environment algorithm, make
the big data environment algorithm is more suitable for intelligent decision support system platform design
application. Through the simulation experiment, the verification results show that it is scientific and
reasonable to apply the big data environment algorithm to the design and application of the intelligent decision
support system platform, which is expected to play a reference role for the subsequent design and application
of the intelligent decision support system platform.
1 INTRODUCTION
In the current industry competition, the use of big data
analysis to enhance the competitiveness is not the
only means and way (Barrow, Mitrovic et al. 2024),
(Gribova, Kovalev et al. 2023). Currently, it is
changed to improve the design effect of the intelligent
decision support system platform, so as to improve
the competitiveness of the data analysis industry (Mi,
Wang et al. 2024), (Mukhitov & Kolesnikov 2023).
Because of the limited ability to obtain information,
the executor can only identify the information
through the intelligent decision support system
platform, which becomes the main reason to
determine the intelligent detection behavior of
company information (Pham, Hoang et al. 2023),
(Sánchez & Vasile, 2023). The higher the satisfaction
of the executor with the design of intelligent decision
support system platform in the industry, then the
greater the application design utility of intelligent
decision support system platform design. Application
has gradually become the main tool for each data
analysis to show the strength of data analysis (Su,
2023), (Sun, 2024), and it has become very important
for the design and application improvement of
intelligent decision support system platform. The
design, construction and application of the intelligent
decision support system platform have gradually
risen to the forefront of the national development
strategy, making effective contributions to the
rational allocation of big data resources and the
promotion of international competitiveness in China
(Taherkhani, Daneshvar et al. 2024), (Wang, Wang et
al. 2023). Although China plays an important role in
building the platform design of big data intelligent
decision support system, it has no advantages in the
application of big data. Therefore, it is necessary to
have a deeper method to study the comprehensive
evaluation method of the design and application of
intelligent decision support system platform, and
strive to explore the comprehensive evaluation model
of the design and application of intelligent decision
support system platform that more meets the
requirements.
542
Chen, L.
Design and Implementation of the Intelligent Decision Support System Platform Under the Big Data Environment.
DOI: 10.5220/0013550600004664
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 1, pages 542-547
ISBN: 978-989-758-763-4
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

2 RELATED WORKS
At present, many experts have studied the field for
the design and application of the intelligent decision
support system platform, and put forward some
comprehensive evaluation methods. Because the
intelligent decision support system platform design
data source and index relationship is more complex,
in view of the existing intelligent decision support
system platform design value evaluation process too
dependent on subjective judgment, lack of objective
and reasonable evaluation way, put forward based on
big data environment algorithm of intelligent decision
support system platform design application method,
build intelligent decision support system platform
design application index system. Simulation
experiments show that, compared with the application
method of the intelligent decision support system
platform design, this method not only reduces the
scale of the index system, but also improves the
efficiency of value evaluation, and improves the
design and application accuracy of the intelligent
decision support system platform on the basis of the
interpretability of the application model.
Further, the intelligent decision support method
reduces the size of the data set, establishes a smaller
evaluation index system, and verifies the
effectiveness of the proposed method, but the method
has a complex process. It is of great significance to
explore the design and application method of
intelligent decision support system platform and
quickly lock the application to improve the efficiency
of the design and application of intelligent decision
support system platform, accelerate the improvement
of the design and application of intelligent decision
support system platform, and realize the
comprehensive evaluation of the design and
application of intelligent decision support system
platform.
From the perspective of intelligent decision
support system platform design data, selected with
the application of intelligent decision support system
platform design application index, using the
traditional evaluation model and evaluation method
based on gradient combination mechanism, the
intelligent decision support system platform design
application comprehensive evaluation, improve the
rationality of intelligent decision support system
platform design application and feasibility. The
experimental results show that applying the proposed
method to the design application of intelligent
decision support system platform can effectively
improve the effectiveness of the design application of
intelligent decision support system platform and
reduce the application time, but this method has the
problem of poor accuracy of the design application of
intelligent decision support system platform. The
platform design of intelligent decision support system
is characterized by high efficiency and controllability.
The comprehensive evaluation of intelligent decision
support system platform design and application by
using existing application methods is caused by lack
of data and poor accuracy of evaluation, and the value
of intelligent decision support system platform design
cannot be improved.
For a more scientific and accurate evaluation of
the design and application of the intelligent decision
support system platform, Analysis the factors
affecting the design and application of intelligent
decision support system platform, Establish an index
system including industry information monitoring
rate and intelligent decision-making application,
Simplify the design index system of the intelligent
decision support system platform through the
correlation analysis, Using the big data environment
to establish the design and application model of the
intelligent decision support system platform, The
results of the simulation experiments show that, The
intelligent decision support system platform based on
big data environment has high accuracy, The
evaluation model has a superior reliability, It can
effectively reflect the creative ability of the intelligent
decision support system platform design and
application.
3 METHODS
3.1 Big Data Environment Algorithm
An intelligent decision support system platform
design value mainly depends on the intelligent
decision support system platform design can give to
belong to, data analysis to create data results, and in a
short period of time, the industry data analysis quality
effect is not obvious, for the quality of data analysis
effect is with time growth and gradually obvious. As
shown in formula _ _ (1):
𝐷(𝐹) = 𝐿

+𝑆

(1
)
Therefore, the establishment of this model is
based on the quality of data analysis. L represents the
reference data analysis of relevant decision data, S
represents the prediction of the quality of decision
data analysis, and the design and application of the
Design and Implementation of the Intelligent Decision Support System Platform Under the Big Data Environment
543

intelligent decision support system platform. As
shown in formula _ _ (2):
𝐴
(𝑆) = 𝐺

+𝐷

(2)
The above formula, G said intelligent decision
support system platform design data analysis quality,
D means intelligent decision support system platform
design effect parameters, A (S) represents the
decision effect of data analysis, the data analysis
decision effect and intelligent decision support
system platform design function index and intelligent
decision support system platform design effect
parameters for detailed analysis, as shown in the
formula (3):
𝐹=
（
𝑓

+2
𝑓

+3
𝑓

)/6
(3)
In the formula, F represents the action index of the
intelligent decision support system platform design.
The function index of intelligent decision support
system platform design is to measure the contribution
of data analysis and reflect the actual influence of
intelligent decision support system platform design in
the decision of executors. This method requires the
assessors to have a strong professional level and
identification means. According to the influencing
factors of the application, the score of the intelligent
decision support system platform design effect can be
obtained according to the weight ratio of the
application and expressed as:
𝐴
=𝑆𝐷

+𝐹𝐷

+𝐺𝐷

+𝑇𝐷

+𝑅𝐷

(4)
In the formula, S, F, G, T and R represent the
influencing factors of the application, and D
represents a certain relationship between the design
effects of the intelligent decision support system
platform. The design effect of the intelligent decision
support system platform can be transformed into the
design effect parameters of the intelligent decision
support system platform. Therefore, the functional
relationship between the design and implementation
of the platform can be established, as shown in
formula (5):
(
𝐴
−𝑆)

=𝐷∗𝐹−𝐺 ， 𝐹∈

𝐷 ， 𝐺

(5)
In the formula, F represents that the effect of
intelligent decision support system platform design
mainly refers to the share of information monitoring
of intelligent decision support system platform design
in the industry, while G represents the position of the
intelligent decision support system platform design in
the industry. The higher the industry share of the
intelligent decision support system platform design
information monitoring is, the higher the design
effect value of the intelligent decision support system
platform is.
3.2 Improvement of the Big Data
Environment Algorithm for the
Design and Application of the
Intelligent Decision Support System
Platform
Combined with the above detailed introduction of the
big data environment algorithm, the big data
environment algorithm is applied to the design and
application of the intelligent decision support system
platform for research. Assign the importance of each
factor in the arrangement, decrease the order of
importance according to the corresponding law, and
arrange the importance of each factor as a whole, as
shown in formula (6):
𝐷=𝐹

,(𝐺 = 1,2,3,⋯𝑛)



(6
)
In the formula, F representative adds the above
importance scores to find the total score of the
importance index of the intelligent decision support
system platform design. G represents that the scores
of each influencing factor can get the action index of
the intelligent decision support system platform
design, as shown in formula (7):
𝐺=𝑇

,(𝑅 = 1,2,3,⋯𝑛)



(7
)
In the formula, T represents the logical
correlation of the above comparative model, and the
consistency index model is shown in formula (8):
𝑇𝐷𝑆 =
（ 𝐹−

(7
)
INCOFT 2025 - International Conference on Futuristic Technology
544

In the formula, (F-G) represents the analysis of the
factors related to the design of the intelligent decision
support system platform, specify the influence type,
(G-H) represents the design problem prioritize the
influence factors, and then conducts statistical
analysis on the research results. Relevant parameters
for the design and application of the intelligent
decision support system platform, as shown in
formula (9):
𝐺𝐸 = 𝑇𝐷𝑆/𝑇𝐷𝐶
(9)
In the formula, if it indicates that the ranking of
GE based on the comparison model is not reasonable,
it means that the consistency test of the TDS
comparison model is correct and the results are
reasonable. By calculating the vector unalization of
the comparison model and classifying the degree of
the influence of all categories of the intelligent
decision support system platform design, the relative
weight of each factor affecting the design and
application of the intelligent decision support system
platform can be clearly defined. According to the
model evaluation method of the influencing factors to
build five evaluation level, through the questionnaire
statistical information of the results of the current
state analysis analysis, thus, calculate the intelligent
decision support system platform design application,
complete the big data environment algorithm of
intelligent decision support system platform design
application comprehensive evaluation.
4 RESULTS AND DISCUSSION
In order to verify the effectiveness of the big data
environment algorithm on the design and application
of the intelligent decision support system platform,
the simulation experiment was carried out to take
Tesla as the research object, and the value of GE
needs to be obtained by table search, as shown in
Table 1.
Table 1 Dataset analysis of the big data environment
algorithm
Or
der
Big
data
enviro
nment
algorit
hm 1
Big
data
enviro
nment
algorit
hm 2
Big
data
enviro
nment
algorit
hm 3
Big
data
enviro
nment
algorit
hm 4
Big
data
enviro
nment
algorit
hm 5
GE 23.43 52.63 32.61 43.71 34.53
The rationality of the comprehensive evaluation
of intelligent decision support system platform is
analyzed. The results of the experimental tests are
shown in Table 2.
Table 2: Comparison of the experimental test results
Technical Paramete
r
S
p
ecific confi
g
uration
Big data environment
al
g
orithm 1
225.313.21
Big data environment
al
g
orithm 2
235.326.35
Big data environment
al
g
orithm 3
234.325.32
Big data environment
al
g
orithm 4
378.449.56
Big data environment
al
g
orithm 5
269.278.16
For different models of intelligent decision
support system platform design application
comprehensive evaluation rationality analysis can
see, using the big data environment algorithm of
intelligent decision support system platform design
application accuracy of comprehensive evaluation
has been stable in controllable range, and use the
accuracy of his model accuracy not reach controllable
range, as shown in figure 1.
Figure 1: Comparison curve between the design effect
parameters of the SSSS platform
It shows that the traditional evaluation model has
a high error rate and poor practicability. Therefore, it
shows that the adoption of big data environment
algorithm can improve the effectiveness of the design
and application of the intelligent decision support
system platform, which is very suitable for the
evaluation of the design and application of the
intelligent decision support system platform, and has
excellent practical value. This paper is combined with
the industry characteristics of intelligent decision
support system platform design, and the big data
environment algorithm is adjusted, so that the
adjusted big data environment algorithm can
highlight the characteristics of intelligent decision
Design and Implementation of the Intelligent Decision Support System Platform Under the Big Data Environment
545

support system platform design for innovation ability
and technical ability. According to the calculation
results of the parameters adjusted by the above model.
As can be seen from Figure 2, in intelligent
decision making and data analysis, the adjusted big
data environment algorithm is used to calculate the
design and application effect of the intelligent
decision support system platform is better, which
shows that the model proposed in this paper can
improve the effectiveness of the design and
application of the intelligent decision support system
platform. In intelligent decision support system
platform design application comprehensive
evaluation in practical application, because,
intelligent decision support system platform design
more and more, the evaluation data scale is larger,
therefore, intelligent decision support system
platform design application efficiency is an important
indicator of evaluation model, using the proposed
model and optimization model and the traditional
model of intelligent decision support system platform
design application time comparison, comparative
analysis results as shown in figure 2.
Figure 2: Comparison of the application time of the
intelligent decision support system platform design for
different evaluation models
From the analysis of the application time
comparison maps of the different evaluation models,
The evaluation of the design application of the SSSS
platform with the increase of measurement times, The
evaluation of the time was gradually increased, The
application time curve using the traditional model and
the optimization model is not like up and down,
Although the design time of the application of the
intelligent decision support system platform using the
evaluation model proposed in this paper fluctuates
slightly, But it gradually stabilized, The evaluation
time can meet the practical requirements of the design
and application of the intelligent decision support
system platform, By appropriately increasing the
assessment time, It is worthwhile to improve the
application accuracy of the intelligent decision
support system platform design, Can achieve higher
application value, As shown in Figure 3.
Figure 3: Comparison of the design and application
efficiency of the different evaluation models
Using the proposed model of intelligent decision
support system platform design application error has
been low, and adopts the optimization model
evaluation error with the increase of the number of
experiments, evaluation error is gradually increasing,
using the traditional model evaluation error is
relatively lower than the optimization model, but
compared with the proposed model in this paper, the
evaluation error is slightly higher. This shows that
using the proposed model can ensure the
effectiveness of the design and application of the
intelligent decision support system platform.
5 CONCLUSIONS
To sum up, the importance of intelligent decision
support system platform design has become more and
more prominent. We have entered an era of
application oriented. Intelligent decision support
system platform design is a valuable intangible asset,
which can bring more benefits to data analysis. Since
the design of intelligent decision support system
platform is still in the development period, it is very
necessary to clarify the application of intelligent
decision support system platform design. When
evaluating the design and application of the
intelligent decision support system platform, it is
necessary to select the evaluation model suitable for
the company's big data environment. Therefore, this
paper makes a comprehensive evaluation of the
design and application of intelligent decision support
system platform and applies the big data environment
algorithm to the design and application of intelligent
decision support system platform. Consider the
adjusted evaluation model, such as the decision
INCOFT 2025 - International Conference on Futuristic Technology
546

maker, so as to enhance the applicability of the design
and application results of the intelligent decision
support system platform and verify the effectiveness
of the model through simulation experiments.
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