Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm
Landscape architecture has both natural and social properties, which is the embodiment of people protecting the natural environment. Since the industrial revolution, the modern industry has developed rapidly. It has increased the living standard of people and consumed a lot of natural resources such...
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Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2021/9420532 |
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doaj-e796ee0b394447eaa407c2ac0fc13a152021-08-02T00:00:59ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52732021-01-01202110.1155/2021/9420532Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network AlgorithmChuanDong Yu0Nan Du1The Art Design and Public Administration DepartmentDepartment of Radio and Television DirectingLandscape architecture has both natural and social properties, which is the embodiment of people protecting the natural environment. Since the industrial revolution, the modern industry has developed rapidly. It has increased the living standard of people and consumed a lot of natural resources such as forest and energy. The ecological environment has been greatly damaged, and the landscape of gardens has been affected. Therefore, it is of great significance to find a method to evaluate the landscape ecology and plan the landscape ecology. This paper proposes a new high-order wavelet neural network algorithm combining wavelet analysis and artificial neural network. A model of ecological evaluation of landscape based on high-order wavelet neural network algorithm is proposed to evaluate the landscape ecology and provide reference data for the ecological planning of the landscape. The results show that the training times of the wavelet neural network to achieve the target accuracy are 3600 times less than those of the BP neural network. The MSE and MAE of the WNN are 0.0639 and 0.1501, respectively. The average error of the model to the comprehensive evaluation index of the landscape ecology is 0.005. The accuracy of the model to evaluate the sustainability of landscape land resources is 98.67%. The above results show that the model based on the wavelet neural network can effectively and accurately complete the evaluation of landscape ecology and then provide a decision-making basis for landscape ecological planning, which is of high practicability.http://dx.doi.org/10.1155/2021/9420532 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
ChuanDong Yu Nan Du |
spellingShingle |
ChuanDong Yu Nan Du Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm Computational Intelligence and Neuroscience |
author_facet |
ChuanDong Yu Nan Du |
author_sort |
ChuanDong Yu |
title |
Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm |
title_short |
Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm |
title_full |
Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm |
title_fullStr |
Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm |
title_full_unstemmed |
Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm |
title_sort |
analysis of landscape ecological planning based on the high-order multiwavelet neural network algorithm |
publisher |
Hindawi Limited |
series |
Computational Intelligence and Neuroscience |
issn |
1687-5273 |
publishDate |
2021-01-01 |
description |
Landscape architecture has both natural and social properties, which is the embodiment of people protecting the natural environment. Since the industrial revolution, the modern industry has developed rapidly. It has increased the living standard of people and consumed a lot of natural resources such as forest and energy. The ecological environment has been greatly damaged, and the landscape of gardens has been affected. Therefore, it is of great significance to find a method to evaluate the landscape ecology and plan the landscape ecology. This paper proposes a new high-order wavelet neural network algorithm combining wavelet analysis and artificial neural network. A model of ecological evaluation of landscape based on high-order wavelet neural network algorithm is proposed to evaluate the landscape ecology and provide reference data for the ecological planning of the landscape. The results show that the training times of the wavelet neural network to achieve the target accuracy are 3600 times less than those of the BP neural network. The MSE and MAE of the WNN are 0.0639 and 0.1501, respectively. The average error of the model to the comprehensive evaluation index of the landscape ecology is 0.005. The accuracy of the model to evaluate the sustainability of landscape land resources is 98.67%. The above results show that the model based on the wavelet neural network can effectively and accurately complete the evaluation of landscape ecology and then provide a decision-making basis for landscape ecological planning, which is of high practicability. |
url |
http://dx.doi.org/10.1155/2021/9420532 |
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