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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Main Authors: ChuanDong Yu, Nan Du
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Computational Intelligence and Neuroscience
Online Access:http://dx.doi.org/10.1155/2021/9420532
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spelling 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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