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

<p>This Article aims at the current high idle rate of landscaped gardens and a single overall style. The article inputs the quantitative relationship programming of the dynamic model of the urban landscape ecological city system into the Grasshopper software to obtain the urban landscape parameter growth curve, and at the same time applies the nonlinear parameterized model method to the landscape design. The research found that the feature form of the landscape garden presented in the thesis is mainly based on the nonlinear transformation of the local analysis structure feature. In the end, the thesis deeply researches the existing operating modes based on the concept of nonlinear thinking. Furthermore, it combines with information technology to supplement and update the traditional landscape construction from different perspectives.</p>
</abstract>

This Article aims at the current high idle rate of landscaped gardens and a single overall style. The article inputs the quantitative relationship programming of the dynamic model of the urban landscape ecological city system into the Grasshopper software to obtain the urban landscape parameter growth curve, and at the same time applies the nonlinear parameterized model method to the landscape design. The research found that the feature form of the landscape garden presented in the thesis is mainly based on the nonlinear transformation of the local analysis structure feature. In the end, the thesis deeply researches the existing operating modes based on the concept of nonlinear thinking. Furthermore, it combines with information technology to supplement and update the traditional landscape construction from different perspectives.

The Optimal Solution of Feature Decomposition Based on the Mathematical Model of Nonlinear Landscape Garden Features

Applied Mathematics and Nonlinear Sciences

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

This Article aims at the current high idle rate of landscaped gardens and a single overall style. The article inputs the quantitative relationship programming...

Position	Value
h0	0.483
h1	0.837
h2	0.224
h3	-0.129

Landscape type	city View	Farmland landscape	Urban landscape sub-area
Nugget variance	461	77	264
Variation	135	152	15
Structure variance	367	78	230
Abutment value	828	155	494
The ratio of nugget variance to base station value n/s (%)	55	49	53

The Optimal Solution of Feature Decomposition Based on the Mathematical Model of Nonlinear Landscape Garden Features

Published Online: Dec 15, 2021

Page range: 751 - 760

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00070

Keywords
Nonlinear, landscape garden features, wavelet transformation, mathematical variance model, feature decomposition, the optimal solution

© 2021 Hu et al., published by Sciendo.

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

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Daubechies wavelet transform coefficients

Theoretical semivariance parameters of the experimental semivariance fitting for each landscape type

The Optimal Solution of Feature Decomposition Based on the Mathematical Model of Nonlinear Landscape Garden Features

Published Online: Dec 15, 2021

Page range: 751 - 760

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00070

KeywordsNonlinear, landscape garden features, wavelet transformation, mathematical variance model, feature decomposition, the optimal solution

© 2021 Hu et al., published by Sciendo.

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

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Daubechies wavelet transform coefficients

Theoretical semivariance parameters of the experimental semivariance fitting for each landscape type

Keywords
Nonlinear, landscape garden features, wavelet transformation, mathematical variance model, feature decomposition, the optimal solution