Research on optimal allocation of accounting teaching resources in cloud computing environment based on genetic algorithm framework design
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19. März 2025
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Online veröffentlicht: 19. März 2025
Eingereicht: 15. Nov. 2024
Akzeptiert: 18. Feb. 2025
DOI: https://doi.org/10.2478/amns-2025-0452
Schlüsselwörter
© 2025 Qianbao Zheng et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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AGA group volume information
| Serial number | Iteration number | Group time/ms | Expectation difficulty | Actual difficulty | Accuracy rate |
|---|---|---|---|---|---|
| 1 | 300 | 254 | 48.8 | 44.5 | 91.2% |
| 2 | 300 | 258 | 49.5 | 44.4 | 89.7% |
| 3 | 300 | 265 | 48.8 | 44.1 | 90.4% |
| 4 | 300 | 263 | 49.5 | 44.6 | 90.1% |
Examination paper information sheet
| Serial number | Simplicity | Simpler | Medium | Harder | Difficulty | Expectation difficulty |
|---|---|---|---|---|---|---|
| 1 | 6 | 5 | 10 | 4 | 5 | 48.8 |
| 2 | 6 | 5 | 10 | 4 | 5 | 49.5 |
| 3 | 6 | 15 | 18 | 3 | 3 | 48.8 |
| 4 | 6 | 15 | 18 | 3 | 3 | 49.5 |
System parameter information table
| Classification | Entry | Concretely |
|---|---|---|
| Hardware parameter | Operating system | Windows10 |
| Running memory | 10G | |
| processor | i7-7500U | |
| Software parameter | Running language | Python3 |
| Running tool | Visual Studio Code |
GA group volume information
| Serial number | Iteration number | Group time/ms | Expectation difficulty | Actual difficulty | Accuracy rate |
|---|---|---|---|---|---|
| 1 | 300 | 235 | 48.8 | 42.5 | 87.1% |
| 2 | 300 | 257 | 49.5 | 43.4 | 87.7% |
| 3 | 300 | 256 | 48.8 | 44.1 | 90.4% |
| 4 | 300 | 252 | 49.5 | 42.6 | 86.1% |
This algorithm group volume information
| Serial number | Iteration number | Group time/ms | Expectation difficulty | Actual difficulty | Accuracy rate |
|---|---|---|---|---|---|
| 1 | 300 | 260 | 48.8 | 45.8 | 93.9% |
| 2 | 300 | 268 | 49.5 | 46.4 | 93.7% |
| 3 | 300 | 264 | 48.8 | 46.9 | 96.1% |
| 4 | 300 | 268 | 49.5 | 45.8 | 92.5% |
Model ability estimation accuracy analysis index
| Test category | Two test mean | Last traditional test |
|---|---|---|
| Minimum grade | -0.25 | 51 |
| Average performance | 1.08 | 78 |
| Top score | 2.26 | 100 |
| ABS | 0.265 | / |
| RMSE | 0.158 | / |
| RMSD | 0.144 | / |
Group volume quality analysis index
| Test category | Two test mean | Last traditional test | ||
|---|---|---|---|---|
| Test quantity | 11.56 | 1:1:1 | ||
| Content expectation ratio | 21 | 4:5:1 | ||
| Test overlap | 0.25 | 1 | ||
| The topic is time-consuming (mean) | 0.05s | Over a week | ||
| Panel rationality | Problem difficulty | Mean | 1.02 | 1.25 |
| SD | 0.93 | 13.56 | ||
| Expected capacity | Mean | 1.01 | 125 | |
| SD | 0.95 | 7.58 | ||
| Correlation coefficient | 0.001 | 0.001 | ||