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A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach

机译:城市公园景观中植物和水形式的美学质量建模方法:人工神经网络方法

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This work presents a simplified method for the application of the Multi-Layer Perceptron (MLP) model that aims to predict the aesthetic quality of the landscape designed by water and plants in different forms and volume. The MLP was prepared by (Rosenblat) in the field of computer science, followed by the application of a MLP in landscape aesthetic quality prediction proposed by (Jahani). In the method of this research, the structure of MLP was structured for aesthetic quality prediction of plants and water in urban park landscapes. The accuracies of designed MLP structures were tested to achieve the most accurate one in aesthetic quality prediction. This method creates an environmental decision support system tool for landscape designers, and it is a platform to predict the quality of environment. In practice, the designed environmental decision support system tool is applied by landscape managers to predict the aesthetic quality of landscape in designing new urban parks.?Applies Multi-Layer Perceptron method in landscape assessment.?Accurate MATLAB extension for landscape aesthetic evaluation.?Defined criteria for aesthetic value of landscape.
机译:该工作提出了一种简化的方法,用于应用多层的Perceptron(MLP)模型,该模型旨在预测水和植物以不同形式和体积设计的景观的美学质量。通过(Rosenblat)在计算机科学领域中制备MLP,然后在(Jahani)提出的景观美学质量预测中的应用。在该研究的方法中,MLP的结构用于城市公园景观中植物和水的美学质量预测。测试了设计的MLP结构的准确性,以实现最准确的审美质量预测。此方法为景观设计人员创建了一个环境决策支持系统工具,它是预测环境质量的平台。在实践中,设计的环境决策支持系统工具由景观经理应用,以预测设计新的城市公园的景观美学质量。在景观评估中的多层Perceptron方法中的景观.?Cocurate Matlab延伸的景观审美评估。?Defined景观审美价值的标准。

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