Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment
Abstract
1. Introduction
2. Literature Review
2.1. Symmetry in Accessible Restrooms: From Regulation to Socio-Emotional Equity
2.2. Empirical Progress in KE and Machine Learning for Emotion Design
3. Methodological Framework for Applying KE to Accessible Restrooms
3.1. Introduction to RST Methodology and Steps
3.2. Introduction to SVM Methodology and Steps
4. Accessible Restrooms Design Study
4.1. Morphological Feature Samples and Emotional Word Collection
4.2. Downscaling the Emotional Word of Accessible Restroom with FA
4.3. RST Defines Important Design Features
4.4. SVM Algorithm to Build Mapping Models
5. Results and Proposed Design Implementation
6. Discussion
6.1. RST–SVM as a Science-Based Pathway to Emotion–Function Symmetry
6.2. Comparison of the Efficiency of Models for Extracting Key Elements
6.3. Comprehensive Emotional Evaluation and Model Efficiency Comparison
6.4. Pathways Toward Explainability and Cross-Context Generalization
7. Conclusions
7.1. Key Findings and Contributions
- (a)
- Methodological framework. The proposed system bridges the gap between user emotional requirements and design practice, thereby enhancing precision and providing scientific underpinnings for barrier-free facility design;
- (b)
- By integrating cutting-edge AI methods, the decision support system enhances design choices, bringing advanced computer science and data-driven insights into accessible design practices;
- (c)
- Novel RST–SVM integration. By fusing RST-based attribute reduction with SVM modeling, we offer a robust barrier-free design process that addresses diverse emotional needs, thus fostering inclusiveness and user satisfaction.
7.2. Broader Implications and Limitations
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Algorithm | Spatial Application | Fuzzy Expression | Reasoning Complexity | Loss Rate | Data Representation |
---|---|---|---|---|---|
PSO-SVR [38] | Outdoor micro-space form-finding | Medium | Medium | Low | Medium |
RF [39] | Office thermal comfort diagnostics | Low | Medium | Medium | Medium |
CNN [40] | Complex indoor way-finding meshes | Low | High | Medium | High |
LSTM [41] | Smart-building load forecasting | Low | High | Medium | Medium |
KNN [42] | Indoor location | Medium | Low | High | Medium |
SVM [43] | Urban Streetscape Visual | Medium | Medium | Low | Medium |
Comfort | Spacious | Clean | Bright | Organized | Warmth | Durable | Safe | Convenient |
No | Comfort | Spacious | Clean | Bright | Organized | Warmth | Durable | Safe | Convenient |
---|---|---|---|---|---|---|---|---|---|
1 | 2.80 | 1.97 | 2.50 | 2.37 | 2.33 | 2.43 | 2.27 | 2.40 | 2.40 |
2 | 2.43 | 2.53 | 2.60 | 2.47 | 2.50 | 2.07 | 2.43 | 2.33 | 2.30 |
3 | 2.70 | 2.80 | 2.67 | 2.50 | 2.43 | 2.53 | 2.50 | 2.60 | 2.47 |
… | … | … | … | … | … | … | … | … | … |
58 | 2.40 | 2.23 | 2.47 | 2.43 | 2.17 | 2.27 | 2.27 | 2.17 | 2.30 |
59 | 2.47 | 2.10 | 2.27 | 2.43 | 2.27 | 2.40 | 2.20 | 2.17 | 2.43 |
60 | 2.50 | 2.77 | 2.63 | 2.47 | 2.33 | 2.50 | 2.40 | 2.40 | 2.47 |
KMO Sampling Adequacy Measure. | 0.857 | |
Bartlett’s sphericity test | Appro. Chi-Square | 274.684 |
df | 36 | |
Sig. | <0.01 |
IE | Sum of Squared Loadings | Sum of Squared Rotated Loadings | |||||||
---|---|---|---|---|---|---|---|---|---|
Sum | Var./% | Cum./% | Sum | Var./% | Cum./% | Sum | Var./% | Cum./% | |
1 | 4.721 | 52.452 | 52.452 | 4.721 | 52.452 | 52.452 | 2.702 | 30.02 | 30.02 |
2 | 1.314 | 14.601 | 67.054 | 1.314 | 14.601 | 67.054 | 2.135 | 23.728 | 53.748 |
3 | 0.786 | 8.732 | 75.785 | 0.786 | 8.732 | 75.785 | 1.983 | 22.037 | 75.785 |
4 | 0.639 | 7.096 | 82.882 | ||||||
5 | 0.459 | 5.097 | 87.979 | ||||||
6 | 0.354 | 3.933 | 91.912 | ||||||
7 | 0.29 | 3.225 | 95.137 | ||||||
8 | 0.251 | 2.785 | 97.922 | ||||||
9 | 0.187 | 2.078 | 100 |
Kansei Word | Component | ||
---|---|---|---|
1 | 2 | 3 | |
1 | 0.038 | 0.201 | 0.845 |
2 | 0.867 | 0.209 | 0.079 |
3 | 0.829 | 0.177 | 0.202 |
4 | 0.733 | 0.243 | 0.180 |
5 | 0.505 | 0.632 | 0.367 |
6 | 0.240 | 0.119 | 0.862 |
7 | 0.528 | 0.616 | −0.058 |
8 | 0.342 | 0.666 | 0.516 |
9 | 0.127 | 0.851 | 0.205 |
No. | Overall Color | Safety Handrail | Handrail Material | Floor Material | Room Brightness | Spatial Layout | Toilet Elevation | Wash Basin Top Side | D |
---|---|---|---|---|---|---|---|---|---|
1 | 3 | 4 | 2 | 2 | 3 | 3 | 4 | 5 | 2 |
2 | 4 | 5 | 5 | 5 | 3 | 4 | 5 | 2 | 3 |
3 | 4 | 2 | 4 | 4 | 3 | 2 | 4 | 3 | 4 |
… | … | … | … | … | … | … | … | … | … |
58 | 3 | 5 | 4 | 4 | 3 | 5 | 4 | 3 | 3 |
59 | 5 | 3 | 5 | 2 | 1 | 4 | 4 | 3 | 3 |
60 | 3 | 3 | 2 | 4 | 4 | 5 | 4 | 4 | 2 |
Expert | Kansei Factor | Utility Factor | Tidiness Factor | Care Factor | Weight (W) | ||||
---|---|---|---|---|---|---|---|---|---|
1 | Utility | 1 | 4 | 5 | 0.67 | Utility | 3.08 | 0.04 | 0.08 |
Tidiness | 1/4 | 1 | 3 | 0.23 | Tidiness | ||||
Care | 1/5 | 1/3 | 1 | 0.10 | Care | ||||
2 | Utility | 1 | 2 | 5 | 0.57 | Utility | 3.02 | 0.01 | 0.02 |
Tidiness | 1/2 | 1 | 4 | 0.33 | Tidiness | ||||
Care | 1/5 | 1/4 | 1 | 0.10 | Care | ||||
3 | Utility | 1 | 3 | 1/4 | 0.23 | Utility | 3.08 | 0.04 | 0.08 |
Tidiness | 1/3 | 1 | 1/5 | 0.10 | Tidiness | ||||
Care | 4 | 5 | 1 | 0.67 | Care | ||||
4 | Utility | 1 | 1 | 2 | 0.25 | Utility | 3 | 0 | 0 |
Tidiness | 1 | 1 | 2 | 0.25 | Tidiness | ||||
Care | 1/2 | 1/2 | 1 | 0.50 | Care |
No. | Overall Color | Floor Material | Room Brightness | Spatial Layout | Toilet Elevation | Wash Basin Top Side | Evaluation Value |
---|---|---|---|---|---|---|---|
1 | 1 | 1 | 4 | 1 | 4 | 1 | 3.0337 |
2 | 4 | 2 | 4 | 2 | 3 | 5 | 2.9866 |
3 | 2 | 3 | 4 | 3 | 1 | 4 | 2.6042 |
… | … | … | … | … | … | … | … |
58 | 1 | 3 | 4 | 4 | 1 | 2 | 3.2265 |
59 | 3 | 1 | 2 | 2 | 4 | 4 | 2.9953 |
60 | 1 | 3 | 3 | 4 | 4 | 3 | 2.9385 |
Parameter | RMSE | MAE | MBE | |
---|---|---|---|---|
Training set | 0.99768 | 0.087851 | 0.0068429 | 0.00048986 |
Test set | 0.93068 | 0.08462 | 0.08462 | 0.08462 |
No. | Overall Color | Floor Material | Room Brightness | Spatial Layout | Toilet Elevation | Wash Basin Top Side | Predictive Value |
---|---|---|---|---|---|---|---|
1 | 1 | 1 | 1 | 1 | 1 | 1 | 2.893248 |
2 | 1 | 1 | 1 | 1 | 1 | 2 | 2.861935 |
3 | 1 | 1 | 1 | 1 | 1 | 3 | 2.861935 |
… | … | … | … | … | … | … | … |
1885 | 1 | 3 | 4 | 1 | 2 | 5 | 3.169948 |
… | … | … | … | … | … | … | … |
4135 | 2 | 3 | 4 | 1 | 2 | 5 | 3.187211 |
… | … | … | … | … | … | … | … |
4260 | 2 | 3 | 5 | 1 | 2 | 5 | 3.147104 |
… | … | … | … | … | … | … | … |
15,748 | 7 | 3 | 6 | 5 | 5 | 3 | 2.877173 |
15,749 | 7 | 3 | 6 | 5 | 5 | 4 | 2.871681 |
15,750 | 7 | 3 | 6 | 5 | 5 | 5 | 2.877758 |
Model | RMSE | MAE | MBE | |
---|---|---|---|---|
SVM | 0.9642 | 0.0862 | 0.0457 | 0.0426 |
BPNN | 0.9439 | 0.1545 | 0.1285 | 0.1495 |
CNN | 0.9380 | 0.1600 | 0.1340 | 0.0250 |
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Chen, Z.; Tian, J.; Zhou, H.; Wu, D. Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment. Buildings 2025, 15, 1567. https://doi.org/10.3390/buildings15091567
Chen Z, Tian J, Zhou H, Wu D. Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment. Buildings. 2025; 15(9):1567. https://doi.org/10.3390/buildings15091567
Chicago/Turabian StyleChen, Zimo, Jingwen Tian, Hongtao Zhou, and Duan Wu. 2025. "Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment" Buildings 15, no. 9: 1567. https://doi.org/10.3390/buildings15091567
APA StyleChen, Z., Tian, J., Zhou, H., & Wu, D. (2025). Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment. Buildings, 15(9), 1567. https://doi.org/10.3390/buildings15091567