| id |
sigradi2021_97 |
| authors |
Pires, Júlio César Pinheiro, Avalone Neto, Olavo and Cenci, Laline Elisângela |
| year |
2021 |
| title |
Color Selection System Based on Linear Regression and ANN |
| source |
Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 327–338 |
| summary |
Color selection is one of several abilities necessary for architectural design. This study presents a web-based JavaScript application capable of foreseeing a color scheme combination that matches a client’s choice pattern based on previous choices made by them. It uses linear regression and Adapted Artificial Neural Network (ANN) for color and shade selection. First, it estimates users’ choice patterns through least mean squares and applies that in the generation of other patterns. It then considers the least square means through a weight factor for the training stage. This study presents the validation of the first process and the correlation between the application’s estimated results and users’ color match expectations. 81.9% of participants found estimated responses to be similar or very similar to the choices they would make; 88% found usage intuitive or very intuitive, and 88.6% agrees the application has some utility to their professional life. |
| keywords |
Cores, regressao linear, sistema de informaçao, análise estatística, moodboard. |
| series |
SIGraDi |
| email |
|
| full text |
 file.pdf (577,649 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/05/23 12:10 |
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