Open Access

Research on Network Resources Integration of University English Blended Learning Model Based on Multi-Objective Optimization

Ling Sun

Ling Sun

Office of Admission & Employment, Hulunbuir University, Hulunbuir, Inner Mongolia Autonomous RegionChina
Search for this author on
Sciendo|Google Scholar
Sun, Ling
  
Mar 21, 2025
Research on Network Resources Integration of University English Blended Learning Model Based on Multi-Objective Optimization's Cover Image
About this article
Previous Article
Next Article
Cite
Download Cover
Published Online: Mar 21, 2025
Received: Oct 14, 2024
Accepted: Feb 11, 2025
DOI: https://doi.org/10.2478/amns-2025-0575
Keywords
© 2025 Ling Sun, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Comparison of algorithms
Comparison of algorithms

Figure 2.

Achievement interval of control class
Achievement interval of control class

Figure 3.

Achievement interval of experimental class
Achievement interval of experimental class

The results of the model and the algorithm

- Maximum adaptive value Maximum average adaptive value Algorithm running time/ms Finding the probability of a feasible solution
Random extraction algorithm (general model) Indescribable - >1000 81%
Retrospective test method (general model) Indescribable - >1000 97.00%
Standard genetic algorithm (Model of this article) 0.68 0.53 207 100%
Improved genetic algorithm (Model of this article) 0.8 0.71 200 100%

English test results

Test Class Mean Standard deviation T P
Pretest Experimental class 65.11 15.268 0.392 0.721
Control class 66.32 15.174
Posttest Experimental class 67.86 13.739 -3.306 0.016
Control class 77.26 14.956

Test difficulty and distinction

- Pretest Posttest
Difficulty 0.45 0.42
Differentiating 0.36 0.39

Hardware environment

Hardware environment Concrete configuration
Processor Intel core i3 M350 @ 2.27GHz
Memory Samsung DDR3 1067MHz 2G
Hard disk WDC WD3200BEVT-08A23T1 320GB
Operating system Microsoft Windows Server 2010
Compiler Microsoft Visual C++ 6.0

Group results

Alternative solution difficulty Differentiating Usage frequency Completion time Final exposure time Overall quality
1 0.92 0.84 0.73 0.82 0.62 0.82
2 0.77 0.8 0.65 0.93 0.97 0.8
3 0.82 0.84 0.74 0.88 0.89 0.8
4 0.61 0.91 0.63 0.85 0.77 0.82
5 0.42 0.81 0.71 0.81 0.8 0.8
Language:
English
Publication timeframe:
1 times per year
Journal Subjects:
Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
Journal RSS Feed