Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm

Autor: Nan Du, ChuanDong Yu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
China
Conservation of Natural Resources
General Computer Science
Article Subject
Computer science
General Mathematics
Computer applications to medicine. Medical informatics
Wavelet Analysis
R858-859.7
Neurosciences. Biological psychiatry. Neuropsychiatry
02 engineering and technology
010501 environmental sciences
Machine learning
computer.software_genre
01 natural sciences
Natural (archaeology)
Wavelet
0202 electrical engineering
electronic engineering
information engineering

Humans
0105 earth and related environmental sciences
Artificial neural network
Ecology
business.industry
General Neuroscience
General Medicine
Natural resource
Reference data
Landscape architecture
Sustainability
020201 artificial intelligence & image processing
Artificial intelligence
Neural Networks
Computer

Landscape ecology
business
computer
Algorithms
Research Article
RC321-571
Zdroj: Computational Intelligence and Neuroscience, Vol 2021 (2021)
Computational Intelligence and Neuroscience
ISSN: 1687-5265
DOI: 10.1155/2021/9420532
Popis: 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.
Databáze: OpenAIRE