School of Art Design, Xi'an FanYi University, Xi'an 710105, Shaanxi, China.
Comput Intell Neurosci. 2022 Jul 31;2022:3150371. doi: 10.1155/2022/3150371. eCollection 2022.
Greenery are the parks in the urban areas and it becomes progressively most significant as cities grow more crowded. In the end, urban parks contribute to the population's healthiness and welfare by providing opportunities intended for physical and social activity, leisure, and relaxation. In order to construct "Digital Land," computer and system software and hardware were used. Computer simulations are used to examine the value of a city garden's landscape design. Digital models and multimedia performances are being built using computer-aided design (CAD), this underlines the need for digitizing data for landscape design. A region's landscapes can only be accurately assessed if sufficient information is available on the elements that influence the people's awareness of landscape quality, as well as the kind, method, and effective rate of each of them. We use an LVQANN (artificial neural network) to forecast the landscape aesthetic assessment of urban parks and priorities the model's significant factors in this research. User viewpoint and artificial neural network modelling were utilized in conjunction to assess the aesthetic quality of the urban park's environment. This was done for two reasons. The design of urban parks decision support system is known as MATLAB software's multilayer perceptions model, which gives the ability to anticipate landscape visual significance in innovative parks. In this study, the ANN LVQ model is used to execute an ageing design of an urban park landscape based on a computer virtual simulation application. An example land is selected as input and area linked to sunny spot, top view, and so on is fixed. The ANN tool box is used to develop this application in MATLAB 2018b software. The following approach is used to create the ideal urban park landscape model. An accuracy of 89.23 percent, a sensitivity of 87.34 percent, and a recall of 78.93 percent were achieved, outperforming the approach and competing with the current model.
绿色空间是城市中的公园，随着城市变得更加拥挤，它变得越来越重要。最终，城市公园通过提供体育和社交活动、休闲和放松的机会，为人们的健康和福利做出了贡献。为了构建“数字土地”，使用了计算机和系统软件和硬件。计算机模拟用于检查城市花园景观设计的价值。正在使用计算机辅助设计 (CAD) 构建数字模型和多媒体表演，这强调了为景观设计数字化数据的必要性。只有在有足够的信息可用于影响人们对景观质量的认识的元素，以及它们各自的种类、方法和有效率的情况下，才能准确评估一个地区的景观。我们使用 LVQANN（人工神经网络）来预测城市公园的景观美学评估，并在本研究中确定模型的重要因素。在这项研究中，结合用户观点和人工神经网络建模来评估城市公园环境的美学质量。这样做有两个原因。城市公园决策支持系统的设计是众所周知的 MATLAB 软件的多层感知模型，它具有预测创新公园景观视觉重要性的能力。在本研究中，ANN LVQ 模型用于根据计算机虚拟模拟应用执行城市公园景观的老化设计。选择一个示例土地作为输入，并固定与阳光点、顶视图等相关的区域。ANN 工具箱用于在 MATLAB 2018b 软件中开发此应用程序。采用以下方法创建理想的城市公园景观模型。该方法的准确率为 89.23%，灵敏度为 87.34%，召回率为 78.93%，优于该方法和现有模型。
