<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to promote the development of the Chinese gardening field, this paper proposes a data-driven, multi-sensory design for Chinese gardens. The multisensory design of Chinese gardens, which combines data-driven technology and VR technology, is explored from two perspectives: the visual and auditory senses. It is found that the design easily leads to the loss of the natural beauty of the garden. For this reason, the layout optimization model is constructed using the improved PSO algorithm, and the corresponding analysis method is applied to analyze the effect of the multi-sensory design of the garden. The results show that the model in this paper is better than the other two control models in terms of weighted mean (4.078) and convergence time (0–4 ms). It was also found that the basis for visitors to make experience visual satisfaction evaluations was basically whether the floral landscape was beautiful (39.18%) and whether the field of view was open (23.27%), and the auditory experience design evaluation scores were higher for acacia forests (5.436), red-leafed ridges (4.091), snapdragon forests (3.872), and metasequoia forests (3.657) in the gardens. The research in this paper reveals the focus of multi-sensory design in Chinese gardens, which can provide theoretical references for research in the field of Chinese garden design.</p>
</abstract>

In order to promote the development of the Chinese gardening field, this paper proposes a data-driven, multi-sensory design for Chinese gardens. The multisensory design of Chinese gardens, which combines data-driven technology and VR technology, is explored from two perspectives: the visual and auditory senses. It is found that the design easily leads to the loss of the natural beauty of the garden. For this reason, the layout optimization model is constructed using the improved PSO algorithm, and the corresponding analysis method is applied to analyze the effect of the multi-sensory design of the garden. The results show that the model in this paper is better than the other two control models in terms of weighted mean (4.078) and convergence time (0–4 ms). It was also found that the basis for visitors to make experience visual satisfaction evaluations was basically whether the floral landscape was beautiful (39.18%) and whether the field of view was open (23.27%), and the auditory experience design evaluation scores were higher for acacia forests (5.436), red-leafed ridges (4.091), snapdragon forests (3.872), and metasequoia forests (3.657) in the gardens. The research in this paper reveals the focus of multi-sensory design in Chinese gardens, which can provide theoretical references for research in the field of Chinese garden design.

Research on data-driven multi-sensory design path based on Chinese gardens under the perspective of AI big data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In order to promote the development of the Chinese gardening field, this paper proposes a data-driven, multi-sensory design for Chinese gardens. The...

Research on data-driven multi-sensory design path based on Chinese gardens under the perspective of AI big data

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 29. März 2024

Akzeptiert: 22. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2069

Schlüsselwörter
Improved PSO algorithm, Multisensory design, Layout optimization model, Chinese gardens

© 2024 Na Xie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on data-driven multi-sensory design path based on Chinese gardens under the perspective of AI big data

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 29. März 2024

Akzeptiert: 22. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2069

SchlüsselwörterImproved PSO algorithm, Multisensory design, Layout optimization model, Chinese gardens

© 2024 Na Xie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Improved PSO algorithm, Multisensory design, Layout optimization model, Chinese gardens