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- W4293238418 abstract "The visual aesthetics of villages are remarkably affected by the exterior quality of traditional residences, influencing the impression and assessment of local culture. A proper scientific assessment of exterior quality can protect traditional cultures and improve the development of villages. This research was conducted in a village consisting of 115 residences (Mengjinglai village, which is on the border between China and Myanmar). The backpropagation (BP) neural network model with genetic algorithm (GA) was applied to evaluate the quality of the dwellings. All the evaluation values of the dwellings were defined by scores. Meanwhile, the score of each residence was affected by three main factors: architectural spatial elements, architectural construction elements, and historical and cultural elements. The results show that the village’s dwellings are well preserved and clearly express the traditional Dai style. Moreover, the GA–BP approach is more suitable than the traditional BP method for the assessment of the exterior quality. The quantitative machine learning model would be useful for other aspects of the assessment of similar villages in the future." @default.
- W4293238418 created "2022-08-27" @default.
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- W4293238418 date "2022-04-27" @default.
- W4293238418 modified "2023-10-14" @default.
- W4293238418 title "Assessment of the Exterior Quality of Traditional Residences: A Genetic Algorithm–Backpropagation Approach" @default.
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- W4293238418 doi "https://doi.org/10.3390/buildings12050559" @default.
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