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The design of an optimisation algorithm for musical performance guided by constructivist theory in musical theatre

Dan Wu

Dan Wu

Music College, Communication University of ChinaNanjing, China
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Wu, Dan
  
05 févr. 2025
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Publié en ligne: 05 févr. 2025
Reçu: 12 oct. 2024
Accepté: 10 janv. 2025
DOI: https://doi.org/10.2478/amns-2025-0078
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© 2025 Dan Wu, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Flowchart of genetic algorithm
Flowchart of genetic algorithm

Figure 2.

Ten fold cross-validation parameter selection
Ten fold cross-validation parameter selection

Figure 3.

The training set confusion matrix
The training set confusion matrix

Figure 4.

Test set confusion matrix
Test set confusion matrix

Music stage lighting color emotion type

Serial number Color Affective connotation Quantity
1 Red Passion, love, energy, positive 579
2 Orange Bright, spiritual, carefree, excited 483
3 Yellow Happy, cheerful, bright, intelligent 259
4 Green Peace, peace, sound ,freshness 135
5 Blue Calm, honest, extensive and harmonious 122
6 Purple Mysterious, happy, elegant, romantic 192

Key frame lighting intensity analysis

Keyframe ldef ηl ηq fl fq Ik
1 34 0.023 0.037 10 16 33.638
2 39 0.062 0.058 27 25 39.224
3 38 0.046 0.065 20 28 37.1
4 28 0.068 0.065 30 28 28.22
5 34 0.027 0.035 12 15 33.799
6 22 0.048 0.042 21 18 22.252
7 20 0.064 0.054 28 23 20.55
8 33 0.034 0.049 15 21 32.481
9 28 0.055 0.042 24 18 28.564
10 39 0.030 0.047 13 20 38.45
11 31 0.037 0.030 16 13 31.202
12 28 0.066 0.065 29 28 28.094
13 29 0.059 0.068 26 29 28.562
14 40 0.053 0.063 23 27 39.518
15 34 0.057 0.042 25 18 34.669
16 31 0.046 0.042 20 18 31.164
17 29 0.062 0.068 27 29 28.702
18 21 0.057 0.033 25 14 21.963
19 30 0.062 0.040 27 17 30.994
20 30 0.046 0.056 20 24 29.576
Total 30.9 0.0501 0.05005 21.9 21.45 30.9361
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